ANOVA analysis and T-test
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Nzznenybjn
Mathematics
759
Mount Aloysius College
Description
i am doing my thesis and i need some help in the results part, i have two groups the control and the experiments group, i need statistical analysis of the 3 days to show if the differences are significant or not ?
i need to run ANOVA and T-test then write around 1 page about these results
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Goal Setting and GPACetin (2015) was interested in individual differences in goal setting behavior and performance in college students. To investigate the hypothesized association between the two variables, Cetin collected goal setting and grade point average (GPA) data from 166 college students. Goal setting was measured with a subscale from the Academic Self-Regulated Learning Scale. Students' GPA was measured via self-report. The goal_setting_gpa.csv data set simulates some of the data so that it corresponds to the results in the original study. We can use it to (a) the null hypothesis that there is no association between self-reported goal setting behavior and self-reported academic performance, and (b) construct a regression equation for predicting GPA from goal setting behavior.Cetin, B. (2015). Academic motivation and self-regulated learning in predicting academic achievement in college. Journal of International Education Research, 11(2), 95-106.(1) Download goal_setting_gpa.csv and open it in Jamovi.(2) Make sure the measure type and data type of the variables are correct.(3) From the Regression menu select Correlation Matrix. (4) In the Analysis panel, move gpa into the Variables box first and then goal_setting. We do it in this order because gpa is the variable we want to predict, which means that on a scatterplot, it should appear on the Y axis.(5) From the Correlation Coefficients menu select Pearson.(6) From the Hypothesis menu select Correlated.This specifies the alternative hypothesis, that the two varoables are correlated.(7) From the Additional Options menu select Report significance and N.(8) From the Plot menu select Correlation Matrix.(9) While still in the Analysis panel, from the Regression menu at the top, select Linear Regression.(10) Move gpa to the Dependent Variable box and move goal-setting to the Covariates box.(11) From the Model Fit menu select R, R2, and RMSE (which is the same thing as standard error of estimate).(12) Save the Jamovi file as Ch14_YourLastName.omv and use it to answer the questions on the worksheet.Instructions for submitting this assignment.(1) Locate Ch14_YourLastName.omv, and Ch14 Homework.docx where you saved them on your computer.(2) Click the title of this assignment (Ch14 Homework) to open the Upload Assignment page.(3) In the ASSIGNMENT SUBMISSION section, attach Ch14_YourLastName.omv and the Ch14 Homework file. Click Submit.(4) If you submit this assignment early enough, I might have time to provide feedback that you can use to improve it and possibly improve your grade. So soon after you submit it, return to this assignment to see if I've given you any feedback. Click the assignment title and on the Review Submission History page you'll see the details of your prior submissions. To revise a prior submission, click Start New, download and revise, be sure to save it, and upload it as previously.
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As a new employee in the finance department, imagine that you have been assigned to a major investigation of the firm’s credit policies designed to reduce bad debt losses. You are requested to investigate the relationship between marital status at the time the card is issued and the subsequent payment record of the individual.You randomly select 100 credit cards issued three years previously. Of the 70 individuals that were married at the time the cards were issued, 11 have defaulted on a payment. Of the 30 individuals who were single when the cards were issued, 7 have defaulted. Do these data present sufficient evidence to indicate that marital status affects credit-worthiness? Use Alpha = 0.05.(Source: Unknown – 326RL?)The National Restaurant Association is interested in determining if there is a relationship between the type of pizza pie which Americans prefer and the region of the country in which they live. 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What is your recommendation to the owner regarding the status of the promotion?With Wine DiscountW/O Wine Discount354635443629362948292960366443472447134936535051224432366. A major distillery for alcoholic beverages is interested in gaining a large share of the market composed of people aged 18-23 (in those states where 18 is the legal drinking age). Beer and wine are the traditional favorites of this age group. However, Bill Schuessler, the firm’s marketing manager, and Carol Pringle, manager of research and development, feel that a new version of distilled apple cider will appeal to this younger market. While they are sure that the alcohol content should remain below 5 percent, they are not sure exactly what it should be. Therefore, five versions of the cider have been prepared and each version has been tasted by a random sample of 25 young consumers. Each consumer has evaluated the drink on a 100-point scale, with the higher scores representing a greater liking for the product. 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PSY 2317 University of Houston Regression Equation of the Regression Model Questions
Goal Setting and GPACetin (2015) was interested in individual differences in goal setting behavior and performance in coll ...
PSY 2317 University of Houston Regression Equation of the Regression Model Questions
Goal Setting and GPACetin (2015) was interested in individual differences in goal setting behavior and performance in college students. To investigate the hypothesized association between the two variables, Cetin collected goal setting and grade point average (GPA) data from 166 college students. Goal setting was measured with a subscale from the Academic Self-Regulated Learning Scale. Students' GPA was measured via self-report. The goal_setting_gpa.csv data set simulates some of the data so that it corresponds to the results in the original study. We can use it to (a) the null hypothesis that there is no association between self-reported goal setting behavior and self-reported academic performance, and (b) construct a regression equation for predicting GPA from goal setting behavior.Cetin, B. (2015). Academic motivation and self-regulated learning in predicting academic achievement in college. Journal of International Education Research, 11(2), 95-106.(1) Download goal_setting_gpa.csv and open it in Jamovi.(2) Make sure the measure type and data type of the variables are correct.(3) From the Regression menu select Correlation Matrix. (4) In the Analysis panel, move gpa into the Variables box first and then goal_setting. We do it in this order because gpa is the variable we want to predict, which means that on a scatterplot, it should appear on the Y axis.(5) From the Correlation Coefficients menu select Pearson.(6) From the Hypothesis menu select Correlated.This specifies the alternative hypothesis, that the two varoables are correlated.(7) From the Additional Options menu select Report significance and N.(8) From the Plot menu select Correlation Matrix.(9) While still in the Analysis panel, from the Regression menu at the top, select Linear Regression.(10) Move gpa to the Dependent Variable box and move goal-setting to the Covariates box.(11) From the Model Fit menu select R, R2, and RMSE (which is the same thing as standard error of estimate).(12) Save the Jamovi file as Ch14_YourLastName.omv and use it to answer the questions on the worksheet.Instructions for submitting this assignment.(1) Locate Ch14_YourLastName.omv, and Ch14 Homework.docx where you saved them on your computer.(2) Click the title of this assignment (Ch14 Homework) to open the Upload Assignment page.(3) In the ASSIGNMENT SUBMISSION section, attach Ch14_YourLastName.omv and the Ch14 Homework file. Click Submit.(4) If you submit this assignment early enough, I might have time to provide feedback that you can use to improve it and possibly improve your grade. So soon after you submit it, return to this assignment to see if I've given you any feedback. Click the assignment title and on the Review Submission History page you'll see the details of your prior submissions. To revise a prior submission, click Start New, download and revise, be sure to save it, and upload it as previously.
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Please use excel not minitab Instructions (please read and follow the instructions):Please solve the problems using excel ...
Central Ohio Technical College Data Driven Decision Making Paper
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Had they left one day earlier, the average hospital cost would have been $322.44 less, and the standard deviation was found to be $21.71. Construct a 95% confidence interval for the mean net savings for the hospital, per patient, for the larger population of recent patients.The Glen Valley Steel Company manufactures steel bars. If the production process is working properly, it turns out steel bars with lengths that are normally distributed with a mean of at least 2.8 feet, with a standard deviation of 0.20 foot (as determined by the engineering specifications on the production equipment involved). Longer steel bars can be used or altered, but shorter steel bars must be scrapped. You select a sample of 25 bars, and the mean length is 2.73 feet. Do you need to adjust the production equipment? (use a significance level of 0.05.(Source: LSKB-5)Meier and Frank is a chain of department stores located in the Northwest. The company has issued its own credit cards for a number of years. As a new employee in the finance department, imagine that you have been assigned to a major investigation of the firm’s credit policies designed to reduce bad debt losses. You are requested to investigate the relationship between marital status at the time the card is issued and the subsequent payment record of the individual.You randomly select 100 credit cards issued three years previously. Of the 70 individuals that were married at the time the cards were issued, 11 have defaulted on a payment. Of the 30 individuals who were single when the cards were issued, 7 have defaulted. Do these data present sufficient evidence to indicate that marital status affects credit-worthiness? Use Alpha = 0.05.(Source: Unknown – 326RL?)The National Restaurant Association is interested in determining if there is a relationship between the type of pizza pie which Americans prefer and the region of the country in which they live. 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The owner began offering “Saturday - Half-off Bottled Wine Night” in 2010 as an incentive for guests to dine at Fancy Fish when the economy was in a recession. Now that the economy is booming, the owner is considering whether the promotion should be continued, or even expanded. One concern is the effect that the promotion is having on the overall revenue generated from sales to the participants.A random sample of 28 checks was collected over the course of one month of Saturday nights. Fourteen checks were from customers participating in the half-off promotion, and the other 14 checks were from customers not participating. The total revenue from each check (less alcohol, tax, and tip) is presented below. Do these data present sufficient evidence that the checks of participants is significantly different from checks of non-participants? What is your recommendation to the owner regarding the status of the promotion?With Wine DiscountW/O Wine Discount354635443629362948292960366443472447134936535051224432366. A major distillery for alcoholic beverages is interested in gaining a large share of the market composed of people aged 18-23 (in those states where 18 is the legal drinking age). Beer and wine are the traditional favorites of this age group. However, Bill Schuessler, the firm’s marketing manager, and Carol Pringle, manager of research and development, feel that a new version of distilled apple cider will appeal to this younger market. While they are sure that the alcohol content should remain below 5 percent, they are not sure exactly what it should be. Therefore, five versions of the cider have been prepared and each version has been tasted by a random sample of 25 young consumers. Each consumer has evaluated the drink on a 100-point scale, with the higher scores representing a greater liking for the product. The results of the test appear below. What should Schuessler and Pringle conclude?Version1% 2% 3% 4% 5%16 40 81 89 5318 62 81 95 2072 11 35 10 9857 49 16 70 6730 40 83 94 9216 63 35 06 0896 77 20 20 5939 93 64 20 4931 62 76 38 0378 91 19 47 3203 93 33 30 4774 42 33 28 7209 06 09 90 9542 23 12 42 2516 15 08 02 0421 45 40 74 2021 58 57 80 5056 61 78 95 9745 65 66 99 2491 34 84 98 4991 22 21 20 3550 07 38 14 2165 39 05 22 5827 50 96 13 4437 16 94 85 17(Source: Unknown)7. Morning House is a mail-order firm which carries a wide range of rather expensive art objects for homes and offices. It operates by advertising a particular item either in selected magazines or in a direct-mail program. Suppose the sales response varies widely by item and the firm’s management has been unable to predict in advance which items will sell well and which will not. Consequently the firm frequently experiences either stock-outs or excessive inventories.For many of the products Morning House sells, it is possible to order a limited amount for inventory and to place a subsequent order for delivery within two weeks. Thus, if the firm could make a early prediction of the ultimate sales of a product, its inventory problems would be greatly reduced. Since it takes approximately six weeks to receive 90% of the response to a given campaign, an accurate prediction of total sales made as late as the end of the first week of receiving orders would be useful.The first week’s sales and total sales of the last 12 campaigns of the firm are shown below. Can the first week’s sales be used to predict total sales? First week’s TotalCampaign Sales Sales 1 32 1672 20 913 114 5604 66 3355 18 706 125 6507 83 4018 65 3209 94 47010 5 1511 39 21012 50 265 -------------------------------------------- (Source: Unknown)Questions?
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For me to be able to read and make comments on the assignments, they will have to be in the Word format.StatCrunch Softwar ...
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