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September 2019
WEEK 2: HOMEWORK
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Problems dealing with Confidence Interval Estimation and Hypothesis Testing
There are actually 9 problems broken down to individual components to identify key steps required to solve the problem. Th ...
Problems dealing with Confidence Interval Estimation and Hypothesis Testing
There are actually 9 problems broken down to individual components to identify key steps required to solve the problem. They appear as multiple chioce questions. For example the 1st 8 questions are dealing with one problem.The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. A random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating a 95% confidence interval estimate of the average number of days absent for the company's workers last year what will be the standard error?4.0.16.80.0251.8 points QUESTION 2The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating a 95% confidence interval estimate of the average number of days absent for the company's workers last year should you use a z or t value in the formula?zt1.8 points QUESTION 3The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating a 95% confidence interval estimate of the average number of days absent for the company's workers last year what would be the value of your UPPER limit?17.9610.0311.358.0491.8 points QUESTION 4The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year what is the sample proportion used in the formula?.12.10.480401.9 points QUESTION 5The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year would you use a z or t in the formula?zt1.9 points QUESTION 6The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year what is the value of the Z used in the formula?1.7081.7111.651.961.9 points QUESTION 7The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year what is the upper limit of the confidence interval?.516.6445.284.6761.9 points QUESTION 8You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. Is this a 1 or 2 tail test?1 tail2 tailindeterminatenone of the above1 points QUESTION 9You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. What are your critical values?+- 1.65+- 2.045+-1.96+-1.651.8 points QUESTION 10You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. What is the value of your test statistic?.30-.308.98-1.641.9 points QUESTION 11You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. If your test statistic is -1.64 what will be your decision?Reject HoReject H1Do not reject H1Do not reject Ho1.9 points QUESTION 12You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. What is your conclusion?There is evidence of a difference in the average return.There is no evidecne of a difference in the average returnIndeterminateInconclusive1.9 points QUESTION 13A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. Is this a 1 or 2 tail test?1 tail2 tail1.9 points QUESTION 14A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. Is this a one sample or two sample test?one sampletwo sample1.9 points QUESTION 15A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. Is this a test of sample means or sample proportions?sample proportionssample meansbothneither1 points QUESTION 16A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What are your critical values?+- 1.65+-1.961.741.791.9 points QUESTION 17A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What is the value of your pooled proportion?.27.73.55.051.9 points QUESTION 18A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What is the value of your test statistic?1.961.651.74.051.9 points QUESTION 19A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What is your decision?Reject HoReject H1Do not reject Honone of the above1.9 points QUESTION 20A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. If you determine not to reject the null hypothesis what is your conclusion?There is evidence of a difference in the proportions of college aged students and non college aged students having accidentsThere is no evidence of a difference in the proportions of college aged students and non college aged students having accidentsthe data is inconclusivenone of the above1.9 points QUESTION 21A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. Is this a 1 or 2 tail test?1 tail2 tail1.9 points QUESTION 22A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is the H1?H1: U< 90H1 not equal to 90H1: U>90Ho: U > or equal to 901.9 points QUESTION 23A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. Is this a Z or t test?tZ1.9 points QUESTION 24A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. Assuming we are using a t test what will be the critical value"?1.28-1.281.29-1.291.9 points QUESTION 25A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is the value of your test statistic?1.281.791.82-1.821.9 points QUESTION 26A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is your decision?reject Hodo not reject Horeject H1none of the above1.9 points QUESTION 27A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is your conclusion?there is no evidence that there has been an increase in the average selling timethere is evidence that there has been an increase in the average selling timethere is no evidence that there has been a decrease in the average selling timethere is evidence that there has been a decrease increase in the average selling time1.9 points QUESTION 28The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. Is this a one or two tail test?1 tail2 tailbothneither1.9 points QUESTION 29The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. Is this a Z, t, or F test?ZtF1.9 points QUESTION 30The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is the alternate hypothesis?Ho: proportion > .55H1: proportion > .55H1: proportion < .55H1: proportion > .601.9 points QUESTION 31The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is the value of your critical value?1.96-1.961.645-1.6451.9 points QUESTION 32The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is the value of your test statistic?.60.85.05.551.9 points QUESTION 33The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is your decision?reject H1do not reject Horeject Hoindeterminate1.9 points QUESTION 34The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is your conclusion?There is evidence that more than 55% would use the route and therefore the STA criteria is met.There is no evidence that more than 55% would use the route and therefore the STA criteria was not met..60 is greater than .55 so the criteria is metindeterminant1.9 points QUESTION 35An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. Is this a one sample test or a two sample test?one sample testtwo sample testneitherboth1.9 points QUESTION 36An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. Is this a one tail or two tail test?neitherone tailtwo tail1.5 points QUESTION 37An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is H1?Ua < Um where "m" is morning and "a" is afternoonUm > UaUa > UmUa not equal to Um1.9 points QUESTION 38An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is your critical value?1.961.281.645.051.9 points QUESTION 39An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is your test statistic?1.6451.28.0561.9 points QUESTION 40An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. If your critical value is on the right of your curve and your test statistic is less than the critical value what will be your decision?reject H1do not reject Horeject Hoit depends1.9 points QUESTION 41An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is your conclusion?There is evidence that the mean number of units produced by the afternoon shift is larger.There is evidence that the mean number of units produced by the morning shift is larger.There is no evidence that the mean number of units produced by the afternoon shift is larger.There is evidence that the mean number of units produced by the morning shift is smaller.1.9 points QUESTION 42The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is the alternate hypothesisUe < Ub where e =end of month and b=begining of monthUe > UbUb > UeUb = Ue1.9 points QUESTION 43The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is your critical value?1.7010.501.6451.961.9 points QUESTION 44The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is the value of your test statistic?-2.0311.752.03-11.051.9 points QUESTION 45The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is your decision?reject Hodo not reject Hoindeterminatereject H11.9 points QUESTION 46The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is your conclusion?There is no evidence of a difference in the mean weightthere is no evidence that the packages shipped at the end of the month weigh morethere is evidence that the packages shipped at the end of the month weigh morethere is evidence that the packages shipped at the end of the month weigh less1.9 points QUESTION 47A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is the alternate hypothesis?Uf does not equal Um, where f=final and m=midtermUf < UmUm > UfUf > Um1.9 points QUESTION 48A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is the critical value?1.963.52.283.14271.9 points QUESTION 49A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is your test statistic?10.579.273.5041.961.9 points QUESTION 50A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is your decision?do not reject Horeject Horeject H1inconclusive1.9 points QUESTION 51A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is your conclusion?There is no difference between the scoresthere is no evidence of a significant improvement on the finalthere is evidence of a significant improvement on the finalstudents scored better on the midterm1.9 points QUESTION 52There are two car dealerships in a particular area. The mean monthly sales at the two dealerships are about the same. However, one of the dealerships (dealership A) is boasting to corporate headquarters that his dealership’s monthly sales are more consistent. An industry analyst reviews the last seven months at dealership A and finds the standard deviation of the seven monthly sales to be 14.79. He reviews the last eight months at dealership B and finds the standard deviation of the eight monthly sales to be 22.95. Using the .01 significance level you will test to conclude if the analyst finds evidence that the boast of dealership A is correct. What will be your critical value?1.1.552.1.353.2.414.8.261.9 points QUESTION 53There are two car dealerships in a particular area. The mean monthly sales at the two dealerships are about the same. However, one of the dealerships (dealership A) is boasting to corporate headquarters that his dealership’s monthly sales are more consistent. An industry analyst reviews the last seven months at dealership A and finds the standard deviation of the seven monthly sales to be 14.79. He reviews the last eight months at dealership B and finds the standard deviation of the eight monthly sales to be 22.95. Using the .01 significance level you will test to see if the analyst finds evidence that the boast of dealership A is correct. What is the value of the test statistic?2.418.261.551.961.9 points QUESTION 54There are two car dealerships in a particular area. The mean monthly sales at the two dealerships are about the same. However, one of the dealerships (dealership A) is boasting to corporate headquarters that his dealership’s monthly sales are more consistent. An industry analyst reviews the last seven months at dealership A and finds the standard deviation of the seven monthly sales to be 14.79. He reviews the last eight months at dealership B and finds the standard deviation of the eight monthly sales to be 22.95. Using the .01 significance level does the analyst find evidence that the boast of dealership A is correct?yesnoindeterminant
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, an ...
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, and justify business predictions based upon the analysis.For this assignment, you will use the "Strength" dataset. You will use SPSS to analyze the dataset and address the questions presented. Findings should be presented in a Word document along with the SPSS outputs.The compressive strength (Y) of concrete is influenced by the mixing proportions and by the time that it is allowed to cure, although the exact relationship between the strength and the components is unknown. The provided data includes the results of n = 1030 concrete strength experiments that include the following:Strength (in MPa): The compressive strength of the concrete.Age (in days): The number of days the concrete was allowed to cured.Coarse_Aggregate (in kg/m3): The proportion of coarse aggregate in the mix.Fine_Aggregate (in kg/m3): The proportion of fine aggregate in the mix.Cement (in kg/m3): The proportion of cement in the mix.Slag (in kg/m3): The proportion of furnace slag in the mix.Superplasticizer (in kg/m3): The proportion of plasticizer in the mix.Water (in kg/m3): The proportion of water in the mix.Ash (in kg/m3): The proportion of fly ash in the mix.Part 1:Derive various transformations of compressive strength to determine which transformation, if any, results in a variable that most closely mimics a normal distribution. To do this, plot Q-Q plots after each transformation listed below, and decide which one should be used to build a multiple linear model. Explain your answer and provide the SPSS output as an illustration.Strength (no transformation)Square root of StrengthSquared Strength(Natural) Log of StrengthReciprocal of StrengthPart 2:Based on the transformation selected in Part 1, build a multiple linear regression model with all eight predictors.Use t-tests to determine if any of the predictors significantly affect the compressive strength of concrete. Explain why each variable should or should not be included in the model. Assume α = 0.05. Show the appropriate model results to explain your answer.If any predictors from question 1 are found to be not significant, remove them and re-run the model to create a reduced model (RM). Are all the remaining variables still statistically significant? Show the appropriate model results to explain your answer.Based on the RM, should there be concern about multicollinearity among the predictors selected? Show the appropriate model results to explain your answer.After fitting the RM, derive the residual plot (standardized residuals vs. standardized predicted values) and normal probability plot. Interpret each plot.What is the coefficient of determination, R2, of the RM? How would you interpret the R2?Based on the RM, what would be the new estimated compressive strength that is currently 50 MPa, after a 10-day increase in curing time? Assume all other predictors are held constant.How would you interpret the intercept (constant) in the RM? Does the interpretation make sense given the data you used to build the RM?Part 3:Given the following components and aging time below, what is the estimated compressive strength based on the RM?Age: 50 daysCoarse_Aggregate: 900 kg/m3Fine_Aggregate: 600 kg/m3Cement: 300 kg/m3Slag: 200 kg/m3Superplasticizer: 7 kg/m3Water: 190 kg/m3Ash: 70 kg/m3Part 4:What is a 95% confidence interval of the estimate in Part 3? How would you interpret the 95% confidence interval? (Hint: Use the SPSS scoring wizard to address this question.)
Walden University Statistics Multiple Regression Paper
Review this week 9 and 10 Learning Resources and media program related to multiple regressio ...
Walden University Statistics Multiple Regression Paper
Review this week 9 and 10 Learning Resources and media program related to multiple regression.
Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in the Learning Resources for this week.
Based on the dataset you chose, construct a research question that can be answered with a multiple regression analysis.
Once you perform your multiple regression analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Part 1 Assignment:
Write a 1- to 2-page analysis of your multiple regression results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.
Part 2
To prepare for this Part 2 of your Assignment:
Review Warner’s Chapter 12 and Chapter 2 of the Wagner course text and the media program found in this week’s Learning Resources and consider the use of dummy variables.
Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in this week’s Learning Resources.
Consider the following:
Create a research question with metric variables and one variable that requires dummy coding. Estimate the model and report results. Note: You are expected to perform regression diagnostics and report that as well.
Once you perform your analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Part 2 Assignment:
Write a 2- to 3-page analysis of your multiple regression using dummy variables results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.
Required Readings
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
Chapter 2, “Transforming Variables”
Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, 8, and 9)
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press/Sage Publications.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center..
Chapter 6, “What are the Assumptions of Multiple Regression?” (pp. 119–136)
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press/Sage Publications.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Chapter 7, “What can be done about Multicollinearity?” (pp. 137–152)
Warner, R. M. (2012). Applied statistics from bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Non-Normally Distributed Errors. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 41-49). Thousand Oaks, CA: SAGE Publications, Inc.
Fox, J. (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
Discrete Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 62-67). Thousand Oaks, CA: SAGE Publications, Inc.
Nonconstant Error Variance. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 49-54). Thousand Oaks, CA: SAGE Publications, Inc.
Nonlinearity. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 54-62). Thousand Oaks, CA: SAGE Publications, Inc.
Outlying and Influential Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 22-41). Thousand Oaks, CA: SAGE Publications, Inc.
Fox, J. (Ed.). (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
Chapter 3, “Outlying and Influential Data” (pp. 22–41)
Chapter 4, “Non-Normally Distributed Errors” (pp. 41–49)
Chapter 5, “Nonconstant Error Variance” (pp. 49–54)
Chapter 6, “Nonlinearity” (pp. 54–62)
Chapter 7, “Discrete Data” (pp. 62–67)
Note: You will access these chapters through the Walden Library databases.
Document: Walden University: Research Design Alignment Table
Required Media
Laureate Education (Producer). (2016m). Regression diagnostics and model evaluation [Video file]. Baltimore, MD: Author.
Note: The approximate length of this media piece is 7 minutes.
In this media program, Dr. Matt Jones demonstrates regression diagnostics and model evaluation using the SPSS software.
Accessible player --Downloads-- Download Video w/CC Download Audio Download Transcript
Laureate Education (Producer). (2016). Dummy variables [Video file]. Baltimore, MD: Author.
Note: This media program is approximately 12 minutes.
In this media program, Dr. Matt Jones demonstrates dummy variables using the SPSS software.
MATH 180 Grossmont Find the Area of Region Bounded Between the Curves Questions
few more questions I have and shall post them for review before bidding. please check them out before you bid.
MATH 180 Grossmont Find the Area of Region Bounded Between the Curves Questions
few more questions I have and shall post them for review before bidding. please check them out before you bid.
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Problems dealing with Confidence Interval Estimation and Hypothesis Testing
There are actually 9 problems broken down to individual components to identify key steps required to solve the problem. Th ...
Problems dealing with Confidence Interval Estimation and Hypothesis Testing
There are actually 9 problems broken down to individual components to identify key steps required to solve the problem. They appear as multiple chioce questions. For example the 1st 8 questions are dealing with one problem.The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. A random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating a 95% confidence interval estimate of the average number of days absent for the company's workers last year what will be the standard error?4.0.16.80.0251.8 points QUESTION 2The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating a 95% confidence interval estimate of the average number of days absent for the company's workers last year should you use a z or t value in the formula?zt1.8 points QUESTION 3The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating a 95% confidence interval estimate of the average number of days absent for the company's workers last year what would be the value of your UPPER limit?17.9610.0311.358.0491.8 points QUESTION 4The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year what is the sample proportion used in the formula?.12.10.480401.9 points QUESTION 5The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year would you use a z or t in the formula?zt1.9 points QUESTION 6The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year what is the value of the Z used in the formula?1.7081.7111.651.961.9 points QUESTION 7The labor relations manager of a large corporation wished to study the absenteeism among workers at the company's central office during the last year. a random sample of 25 workers revealed the following: an average of 9.7 days; a standard deviation of 4.0 days; and 12 employees were absent more than 10 days. In estimating the 95% confidence interval estimate of the proportion of workers absent more than 10 days last year what is the upper limit of the confidence interval?.516.6445.284.6761.9 points QUESTION 8You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. Is this a 1 or 2 tail test?1 tail2 tailindeterminatenone of the above1 points QUESTION 9You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. What are your critical values?+- 1.65+- 2.045+-1.96+-1.651.8 points QUESTION 10You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. What is the value of your test statistic?.30-.308.98-1.641.9 points QUESTION 11You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. If your test statistic is -1.64 what will be your decision?Reject HoReject H1Do not reject H1Do not reject Ho1.9 points QUESTION 12You are considering investing in a company. The company claims for the past few years the average monthly return on such an investment has been $870 with a standard deviation of $50. You sample 30 investors and determine the sample average return to be $855. Using a .05 level of significance you will test to determine if there is evidence that the true average return is different from $870. What is your conclusion?There is evidence of a difference in the average return.There is no evidecne of a difference in the average returnIndeterminateInconclusive1.9 points QUESTION 13A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. Is this a 1 or 2 tail test?1 tail2 tail1.9 points QUESTION 14A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. Is this a one sample or two sample test?one sampletwo sample1.9 points QUESTION 15A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. Is this a test of sample means or sample proportions?sample proportionssample meansbothneither1 points QUESTION 16A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What are your critical values?+- 1.65+-1.961.741.791.9 points QUESTION 17A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What is the value of your pooled proportion?.27.73.55.051.9 points QUESTION 18A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What is the value of your test statistic?1.961.651.74.051.9 points QUESTION 19A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. What is your decision?Reject HoReject H1Do not reject Honone of the above1.9 points QUESTION 20A random sample of 400 college students was selected and 120 of them had at least one motor vehicle accident in the previous two years. A random sample of 600 young adults not enrolled in college was selected and 150 of them had at least one motor vehicle accident in the previous two years. At the .05 level, you are testing whether there is a significant difference in the proportions of college students and similar aged non college students having accidents during the two year period. If you determine not to reject the null hypothesis what is your conclusion?There is evidence of a difference in the proportions of college aged students and non college aged students having accidentsThere is no evidence of a difference in the proportions of college aged students and non college aged students having accidentsthe data is inconclusivenone of the above1.9 points QUESTION 21A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. Is this a 1 or 2 tail test?1 tail2 tail1.9 points QUESTION 22A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is the H1?H1: U< 90H1 not equal to 90H1: U>90Ho: U > or equal to 901.9 points QUESTION 23A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. Is this a Z or t test?tZ1.9 points QUESTION 24A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. Assuming we are using a t test what will be the critical value"?1.28-1.281.29-1.291.9 points QUESTION 25A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is the value of your test statistic?1.281.791.82-1.821.9 points QUESTION 26A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is your decision?reject Hodo not reject Horeject H1none of the above1.9 points QUESTION 27A statewide real estate company specializes in selling farm property in the state of Nebraska. Their records indicate that the mean selling time of farm property is 90 days. Because of recent drought conditions, they believe that the mean selling time is now greater than 90 days. A statewide survey of 100 farms sold recently revealed that the mean selling time was 94 days, with a standard deviation of 22 days. At the .10 significance level you will test to determine if there has been an increase in selling time. What is your conclusion?there is no evidence that there has been an increase in the average selling timethere is evidence that there has been an increase in the average selling timethere is no evidence that there has been a decrease in the average selling timethere is evidence that there has been a decrease increase in the average selling time1.9 points QUESTION 28The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. Is this a one or two tail test?1 tail2 tailbothneither1.9 points QUESTION 29The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. Is this a Z, t, or F test?ZtF1.9 points QUESTION 30The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is the alternate hypothesis?Ho: proportion > .55H1: proportion > .55H1: proportion < .55H1: proportion > .601.9 points QUESTION 31The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is the value of your critical value?1.96-1.961.645-1.6451.9 points QUESTION 32The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is the value of your test statistic?.60.85.05.551.9 points QUESTION 33The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is your decision?reject H1do not reject Horeject Hoindeterminate1.9 points QUESTION 34The policy of the Suburban Transit authority is to add a bus route if more than 55 percent of the potential commuters indicate they would use the particular route. A sample of 70 commuters revealed that 42 would use a proposed route from Bowman Park to the downtown area. You will be testing to determine if the Bowman-to-downtown route meets the STA criterion using the .05 significance level. What is your conclusion?There is evidence that more than 55% would use the route and therefore the STA criteria is met.There is no evidence that more than 55% would use the route and therefore the STA criteria was not met..60 is greater than .55 so the criteria is metindeterminant1.9 points QUESTION 35An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. Is this a one sample test or a two sample test?one sample testtwo sample testneitherboth1.9 points QUESTION 36An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. Is this a one tail or two tail test?neitherone tailtwo tail1.5 points QUESTION 37An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is H1?Ua < Um where "m" is morning and "a" is afternoonUm > UaUa > UmUa not equal to Um1.9 points QUESTION 38An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is your critical value?1.961.281.645.051.9 points QUESTION 39An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is your test statistic?1.6451.28.0561.9 points QUESTION 40An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. If your critical value is on the right of your curve and your test statistic is less than the critical value what will be your decision?reject H1do not reject Horeject Hoit depends1.9 points QUESTION 41An industrial engineer would like to determine whether there are more units produced on the afternoon shift than on the morning shift. A sample of 50 morning-shift workers showed that the mean number of units produced was 345, with a standard deviation of 21. A sample of 60 afternoon-shift workers showed the mean number of units produced was 351, with a standard deviation of 28 units. At the .05 significance level we will test if the mean number of units produced on the afternoon-shift is larger. What is your conclusion?There is evidence that the mean number of units produced by the afternoon shift is larger.There is evidence that the mean number of units produced by the morning shift is larger.There is no evidence that the mean number of units produced by the afternoon shift is larger.There is evidence that the mean number of units produced by the morning shift is smaller.1.9 points QUESTION 42The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is the alternate hypothesisUe < Ub where e =end of month and b=begining of monthUe > UbUb > UeUb = Ue1.9 points QUESTION 43The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is your critical value?1.7010.501.6451.961.9 points QUESTION 44The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is the value of your test statistic?-2.0311.752.03-11.051.9 points QUESTION 45The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is your decision?reject Hodo not reject Hoindeterminatereject H11.9 points QUESTION 46The manager of a package courier service believes that packages shipped at the end of the month are heavier than those shipped early in the month. As an experiment, he weighed a random sample of 20 packages at the beginning of the month. He found that the mean weight was 20.25 pounds and the standard deviation was 5.84 pounds. Ten packages randomly selected at the end of the month had a mean weight of 24.80 pounds and a standard deviation of 5.67 pounds. At the .05 significance level, we will test to see if we can we conclude that the packages shipped at the end of the month weigh more. What is your conclusion?There is no evidence of a difference in the mean weightthere is no evidence that the packages shipped at the end of the month weigh morethere is evidence that the packages shipped at the end of the month weigh morethere is evidence that the packages shipped at the end of the month weigh less1.9 points QUESTION 47A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is the alternate hypothesis?Uf does not equal Um, where f=final and m=midtermUf < UmUm > UfUf > Um1.9 points QUESTION 48A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is the critical value?1.963.52.283.14271.9 points QUESTION 49A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is your test statistic?10.579.273.5041.961.9 points QUESTION 50A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is your decision?do not reject Horeject Horeject H1inconclusive1.9 points QUESTION 51A statistics professor would like to determine whether students in the class showed improved performance on the final exam as compared to the midterm examination. A random sample of 7 students selected from a large class revealed the following scores: midterm 70, 62, 57, 68, 89, 63, 82 and on the final 80, 79, 87, 88, 85, 79, 91. We will test to determine if there evidence of an improvement on the final examination, at the 1% significance level. What is your conclusion?There is no difference between the scoresthere is no evidence of a significant improvement on the finalthere is evidence of a significant improvement on the finalstudents scored better on the midterm1.9 points QUESTION 52There are two car dealerships in a particular area. The mean monthly sales at the two dealerships are about the same. However, one of the dealerships (dealership A) is boasting to corporate headquarters that his dealership’s monthly sales are more consistent. An industry analyst reviews the last seven months at dealership A and finds the standard deviation of the seven monthly sales to be 14.79. He reviews the last eight months at dealership B and finds the standard deviation of the eight monthly sales to be 22.95. Using the .01 significance level you will test to conclude if the analyst finds evidence that the boast of dealership A is correct. What will be your critical value?1.1.552.1.353.2.414.8.261.9 points QUESTION 53There are two car dealerships in a particular area. The mean monthly sales at the two dealerships are about the same. However, one of the dealerships (dealership A) is boasting to corporate headquarters that his dealership’s monthly sales are more consistent. An industry analyst reviews the last seven months at dealership A and finds the standard deviation of the seven monthly sales to be 14.79. He reviews the last eight months at dealership B and finds the standard deviation of the eight monthly sales to be 22.95. Using the .01 significance level you will test to see if the analyst finds evidence that the boast of dealership A is correct. What is the value of the test statistic?2.418.261.551.961.9 points QUESTION 54There are two car dealerships in a particular area. The mean monthly sales at the two dealerships are about the same. However, one of the dealerships (dealership A) is boasting to corporate headquarters that his dealership’s monthly sales are more consistent. An industry analyst reviews the last seven months at dealership A and finds the standard deviation of the seven monthly sales to be 14.79. He reviews the last eight months at dealership B and finds the standard deviation of the eight monthly sales to be 22.95. Using the .01 significance level does the analyst find evidence that the boast of dealership A is correct?yesnoindeterminant
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, an ...
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, and justify business predictions based upon the analysis.For this assignment, you will use the "Strength" dataset. You will use SPSS to analyze the dataset and address the questions presented. Findings should be presented in a Word document along with the SPSS outputs.The compressive strength (Y) of concrete is influenced by the mixing proportions and by the time that it is allowed to cure, although the exact relationship between the strength and the components is unknown. The provided data includes the results of n = 1030 concrete strength experiments that include the following:Strength (in MPa): The compressive strength of the concrete.Age (in days): The number of days the concrete was allowed to cured.Coarse_Aggregate (in kg/m3): The proportion of coarse aggregate in the mix.Fine_Aggregate (in kg/m3): The proportion of fine aggregate in the mix.Cement (in kg/m3): The proportion of cement in the mix.Slag (in kg/m3): The proportion of furnace slag in the mix.Superplasticizer (in kg/m3): The proportion of plasticizer in the mix.Water (in kg/m3): The proportion of water in the mix.Ash (in kg/m3): The proportion of fly ash in the mix.Part 1:Derive various transformations of compressive strength to determine which transformation, if any, results in a variable that most closely mimics a normal distribution. To do this, plot Q-Q plots after each transformation listed below, and decide which one should be used to build a multiple linear model. Explain your answer and provide the SPSS output as an illustration.Strength (no transformation)Square root of StrengthSquared Strength(Natural) Log of StrengthReciprocal of StrengthPart 2:Based on the transformation selected in Part 1, build a multiple linear regression model with all eight predictors.Use t-tests to determine if any of the predictors significantly affect the compressive strength of concrete. Explain why each variable should or should not be included in the model. Assume α = 0.05. Show the appropriate model results to explain your answer.If any predictors from question 1 are found to be not significant, remove them and re-run the model to create a reduced model (RM). Are all the remaining variables still statistically significant? Show the appropriate model results to explain your answer.Based on the RM, should there be concern about multicollinearity among the predictors selected? Show the appropriate model results to explain your answer.After fitting the RM, derive the residual plot (standardized residuals vs. standardized predicted values) and normal probability plot. Interpret each plot.What is the coefficient of determination, R2, of the RM? How would you interpret the R2?Based on the RM, what would be the new estimated compressive strength that is currently 50 MPa, after a 10-day increase in curing time? Assume all other predictors are held constant.How would you interpret the intercept (constant) in the RM? Does the interpretation make sense given the data you used to build the RM?Part 3:Given the following components and aging time below, what is the estimated compressive strength based on the RM?Age: 50 daysCoarse_Aggregate: 900 kg/m3Fine_Aggregate: 600 kg/m3Cement: 300 kg/m3Slag: 200 kg/m3Superplasticizer: 7 kg/m3Water: 190 kg/m3Ash: 70 kg/m3Part 4:What is a 95% confidence interval of the estimate in Part 3? How would you interpret the 95% confidence interval? (Hint: Use the SPSS scoring wizard to address this question.)
Walden University Statistics Multiple Regression Paper
Review this week 9 and 10 Learning Resources and media program related to multiple regressio ...
Walden University Statistics Multiple Regression Paper
Review this week 9 and 10 Learning Resources and media program related to multiple regression.
Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in the Learning Resources for this week.
Based on the dataset you chose, construct a research question that can be answered with a multiple regression analysis.
Once you perform your multiple regression analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Part 1 Assignment:
Write a 1- to 2-page analysis of your multiple regression results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.
Part 2
To prepare for this Part 2 of your Assignment:
Review Warner’s Chapter 12 and Chapter 2 of the Wagner course text and the media program found in this week’s Learning Resources and consider the use of dummy variables.
Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in this week’s Learning Resources.
Consider the following:
Create a research question with metric variables and one variable that requires dummy coding. Estimate the model and report results. Note: You are expected to perform regression diagnostics and report that as well.
Once you perform your analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Part 2 Assignment:
Write a 2- to 3-page analysis of your multiple regression using dummy variables results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.
Required Readings
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
Chapter 2, “Transforming Variables”
Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, 8, and 9)
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press/Sage Publications.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center..
Chapter 6, “What are the Assumptions of Multiple Regression?” (pp. 119–136)
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press/Sage Publications.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Chapter 7, “What can be done about Multicollinearity?” (pp. 137–152)
Warner, R. M. (2012). Applied statistics from bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Non-Normally Distributed Errors. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 41-49). Thousand Oaks, CA: SAGE Publications, Inc.
Fox, J. (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
Discrete Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 62-67). Thousand Oaks, CA: SAGE Publications, Inc.
Nonconstant Error Variance. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 49-54). Thousand Oaks, CA: SAGE Publications, Inc.
Nonlinearity. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 54-62). Thousand Oaks, CA: SAGE Publications, Inc.
Outlying and Influential Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 22-41). Thousand Oaks, CA: SAGE Publications, Inc.
Fox, J. (Ed.). (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
Chapter 3, “Outlying and Influential Data” (pp. 22–41)
Chapter 4, “Non-Normally Distributed Errors” (pp. 41–49)
Chapter 5, “Nonconstant Error Variance” (pp. 49–54)
Chapter 6, “Nonlinearity” (pp. 54–62)
Chapter 7, “Discrete Data” (pp. 62–67)
Note: You will access these chapters through the Walden Library databases.
Document: Walden University: Research Design Alignment Table
Required Media
Laureate Education (Producer). (2016m). Regression diagnostics and model evaluation [Video file]. Baltimore, MD: Author.
Note: The approximate length of this media piece is 7 minutes.
In this media program, Dr. Matt Jones demonstrates regression diagnostics and model evaluation using the SPSS software.
Accessible player --Downloads-- Download Video w/CC Download Audio Download Transcript
Laureate Education (Producer). (2016). Dummy variables [Video file]. Baltimore, MD: Author.
Note: This media program is approximately 12 minutes.
In this media program, Dr. Matt Jones demonstrates dummy variables using the SPSS software.
MATH 180 Grossmont Find the Area of Region Bounded Between the Curves Questions
few more questions I have and shall post them for review before bidding. please check them out before you bid.
MATH 180 Grossmont Find the Area of Region Bounded Between the Curves Questions
few more questions I have and shall post them for review before bidding. please check them out before you bid.
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