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Spss Data Analysis
1 Compare the means of 2 different groups: use two different continuous variable items. -1a. Display two t-test statistics ...
Spss Data Analysis
1 Compare the means of 2 different groups: use two different continuous variable items. -1a. Display two t-test statistics (ex. Fig. 9.5, Marston) and ...
1 page
Explain Why The Parabola Shown In The Figure Below Is Not A Good Fit For The Data
Explain why the parabola shown in the figure below is not a good fit for the data. The line of best fit is a line that is ...
Explain Why The Parabola Shown In The Figure Below Is Not A Good Fit For The Data
Explain why the parabola shown in the figure below is not a good fit for the data. The line of best fit is a line that is closer to most of the point. ...
Weighting Secondary Data
Post a 3-paragraph analysis of weighting in secondary data that includes the following:An explanation about the importanc ...
Weighting Secondary Data
Post a 3-paragraph analysis of weighting in secondary data that includes the following:An explanation about the importance of weighting in secondary dataTwo examples of how you might use weighting. (For each example, provide a rationale for the weighting.)Support your post with the Learning Resources and current literature. Use APA formatting for your Discussion and to cite your resources.Resources Fuller, C. H. (1974). Weighting to adjust for survey nonresponse. Public Opinion Quarterly, 38(2), 239–246.Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. (2009). Can differences in medical drug compliance between European countries be explained by social factors: Analyses based on data from the European Social Survey, round 2. BMC Public Health, 9, 145–150.Pike, G. R. (2008). Using weighting adjustments to compensate for survey nonresponse. Research in Higher Education, 49(2), 153–171.
7 pages
Principles for School Mathematics
Mathematics: The abstract science of number, quantity, and space. Mathematics may be studied in its own right called pure ...
Principles for School Mathematics
Mathematics: The abstract science of number, quantity, and space. Mathematics may be studied in its own right called pure mathematics, or as it is applied to other disciplines such as physics and engineering called applied mathematics.It is affirmed that high-quality, challenging, and accessible mathe¬matics education for 3- to 6-year-old children
MAT 240 SNHU Hypothesis Testing for Regional Real Estate Company Paper
ScenarioYou have been hired by the Regional Real Estate Company to help them analyze real estate data. One of the company� ...
MAT 240 SNHU Hypothesis Testing for Regional Real Estate Company Paper
ScenarioYou have been hired by the Regional Real Estate Company to help them analyze real estate data. One of the company’s Pacific region salespeople just returned to the office with a newly designed advertisement. The average cost per square foot of home sales based on this advertisement is $280. The salesperson claims that the average cost per square foot in the Pacific region is less than $280. In other words, he claims that the newly designed advertisement would result in higher average cost per square foot in the Pacific Region. He wants you to make sure he can make that statement before approving the use of the advertisement. In order to test his claim, you will generate a random sample size of 750 using data for the Pacific region and use this data to perform a hypothesis test. PromptGenerate a sample of size 750 using data for the Pacific region. Then, design a hypothesis test and interpret the results using significance level α = .05. You will work with this sample in the assignment. Briefly describe how you generated your random sample.Use the House Listing Price by Region document and the National Summary Statistics and Graphs House Listing Price by Region documents to help support your work on this assignment. You may also use the Descriptive Statistics in Excel and Creating Histograms in Excel tutorials for support.Specifically, you must address the following rubric criteria, using the Module Five Assignment TemplateHypothesis Test Setup: Define your population parameter, including hypothesis statements, and specify the appropriate test.Define your population parameter.Write the null and alternative hypotheses. Note: Remember, the salesperson believes that his sales are higher.Specify the name of the test you will use.Identify whether it is a left-tailed, right-tailed, or two-tailed test.Identify your significance level.Data Analysis Preparations: Describe sample summary statistics, provide a histogram and summary, check assumptions, and find the test statistic and significance level.Provide the descriptive statistics (sample size, mean, median, and standard deviation).Provide a histogram of your sample.Describe your sample by writing a sentence describing the shape, center, and spread of your sample.Determine whether the conditions to perform your identified test have been met.Calculations: Calculate the p value, describe the p value and test statistic in regard to the normal curve graph, discuss how the p value relates to the significance level, and compare the p value to the significance level to reject or fail to reject the null hypothesis.
Calculate the sample mean and standard error.Determine the appropriate test statistic, then calculate the test statistic.Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean (Pacific), and the target is 280.Calculate the p value.Note: For right-tailed, use the T.DIST.RT function in Excel, left-tailed is the T.DIST function, and two-tailed is the T.DIST.2T function. The degree of freedom is calculated by subtracting 1 from your sample size.Choose your test from the following:=T.DIST.RT([test statistic], [degree of freedom])=T.DIST([test statistic], [degree of freedom], 1)=T.DIST.2T([test statistic], [degree of freedom])Using the normal curve graph as a reference, describe where the p value and test statistic would be placed.Test Decision: Discuss the relationship between the p value and the significance level, including a comparison between the two, and decide to reject or fail to reject the null hypothesis.Discuss how the p value relates to the significance level.Compare the p value and significance level, and make a decision to reject or fail to reject the null hypothesis.Conclusion: Discuss how your test relates to the hypothesis and discuss the statistical significance.Explain in one paragraph how your test decision relates to your hypothesis and whether your conclusions are statistically significant.You can use the following tutorial that is specifically about this assignment:MAT-240 Module 5 Assignment
Describing Data Sets Discussion
Describing Data SetsAs you have seen in several examples in class, we can understand a lot about a data set based on infor ...
Describing Data Sets Discussion
Describing Data SetsAs you have seen in several examples in class, we can understand a lot about a data set based on information that is given to us in a study about the central tendency and variation of a data set.Describe the following terms in your own words:MeanStandard DeviationZ-ScoresCorrelationFinally, if someone told you that the average of a data set was 40, and that standard deviation was 10, what else could you derive from that information?
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Most Popular Content
7 pages
Spss Data Analysis
1 Compare the means of 2 different groups: use two different continuous variable items. -1a. Display two t-test statistics ...
Spss Data Analysis
1 Compare the means of 2 different groups: use two different continuous variable items. -1a. Display two t-test statistics (ex. Fig. 9.5, Marston) and ...
1 page
Explain Why The Parabola Shown In The Figure Below Is Not A Good Fit For The Data
Explain why the parabola shown in the figure below is not a good fit for the data. The line of best fit is a line that is ...
Explain Why The Parabola Shown In The Figure Below Is Not A Good Fit For The Data
Explain why the parabola shown in the figure below is not a good fit for the data. The line of best fit is a line that is closer to most of the point. ...
Weighting Secondary Data
Post a 3-paragraph analysis of weighting in secondary data that includes the following:An explanation about the importanc ...
Weighting Secondary Data
Post a 3-paragraph analysis of weighting in secondary data that includes the following:An explanation about the importance of weighting in secondary dataTwo examples of how you might use weighting. (For each example, provide a rationale for the weighting.)Support your post with the Learning Resources and current literature. Use APA formatting for your Discussion and to cite your resources.Resources Fuller, C. H. (1974). Weighting to adjust for survey nonresponse. Public Opinion Quarterly, 38(2), 239–246.Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. (2009). Can differences in medical drug compliance between European countries be explained by social factors: Analyses based on data from the European Social Survey, round 2. BMC Public Health, 9, 145–150.Pike, G. R. (2008). Using weighting adjustments to compensate for survey nonresponse. Research in Higher Education, 49(2), 153–171.
7 pages
Principles for School Mathematics
Mathematics: The abstract science of number, quantity, and space. Mathematics may be studied in its own right called pure ...
Principles for School Mathematics
Mathematics: The abstract science of number, quantity, and space. Mathematics may be studied in its own right called pure mathematics, or as it is applied to other disciplines such as physics and engineering called applied mathematics.It is affirmed that high-quality, challenging, and accessible mathe¬matics education for 3- to 6-year-old children
MAT 240 SNHU Hypothesis Testing for Regional Real Estate Company Paper
ScenarioYou have been hired by the Regional Real Estate Company to help them analyze real estate data. One of the company� ...
MAT 240 SNHU Hypothesis Testing for Regional Real Estate Company Paper
ScenarioYou have been hired by the Regional Real Estate Company to help them analyze real estate data. One of the company’s Pacific region salespeople just returned to the office with a newly designed advertisement. The average cost per square foot of home sales based on this advertisement is $280. The salesperson claims that the average cost per square foot in the Pacific region is less than $280. In other words, he claims that the newly designed advertisement would result in higher average cost per square foot in the Pacific Region. He wants you to make sure he can make that statement before approving the use of the advertisement. In order to test his claim, you will generate a random sample size of 750 using data for the Pacific region and use this data to perform a hypothesis test. PromptGenerate a sample of size 750 using data for the Pacific region. Then, design a hypothesis test and interpret the results using significance level α = .05. You will work with this sample in the assignment. Briefly describe how you generated your random sample.Use the House Listing Price by Region document and the National Summary Statistics and Graphs House Listing Price by Region documents to help support your work on this assignment. You may also use the Descriptive Statistics in Excel and Creating Histograms in Excel tutorials for support.Specifically, you must address the following rubric criteria, using the Module Five Assignment TemplateHypothesis Test Setup: Define your population parameter, including hypothesis statements, and specify the appropriate test.Define your population parameter.Write the null and alternative hypotheses. Note: Remember, the salesperson believes that his sales are higher.Specify the name of the test you will use.Identify whether it is a left-tailed, right-tailed, or two-tailed test.Identify your significance level.Data Analysis Preparations: Describe sample summary statistics, provide a histogram and summary, check assumptions, and find the test statistic and significance level.Provide the descriptive statistics (sample size, mean, median, and standard deviation).Provide a histogram of your sample.Describe your sample by writing a sentence describing the shape, center, and spread of your sample.Determine whether the conditions to perform your identified test have been met.Calculations: Calculate the p value, describe the p value and test statistic in regard to the normal curve graph, discuss how the p value relates to the significance level, and compare the p value to the significance level to reject or fail to reject the null hypothesis.
Calculate the sample mean and standard error.Determine the appropriate test statistic, then calculate the test statistic.Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean (Pacific), and the target is 280.Calculate the p value.Note: For right-tailed, use the T.DIST.RT function in Excel, left-tailed is the T.DIST function, and two-tailed is the T.DIST.2T function. The degree of freedom is calculated by subtracting 1 from your sample size.Choose your test from the following:=T.DIST.RT([test statistic], [degree of freedom])=T.DIST([test statistic], [degree of freedom], 1)=T.DIST.2T([test statistic], [degree of freedom])Using the normal curve graph as a reference, describe where the p value and test statistic would be placed.Test Decision: Discuss the relationship between the p value and the significance level, including a comparison between the two, and decide to reject or fail to reject the null hypothesis.Discuss how the p value relates to the significance level.Compare the p value and significance level, and make a decision to reject or fail to reject the null hypothesis.Conclusion: Discuss how your test relates to the hypothesis and discuss the statistical significance.Explain in one paragraph how your test decision relates to your hypothesis and whether your conclusions are statistically significant.You can use the following tutorial that is specifically about this assignment:MAT-240 Module 5 Assignment
Describing Data Sets Discussion
Describing Data SetsAs you have seen in several examples in class, we can understand a lot about a data set based on infor ...
Describing Data Sets Discussion
Describing Data SetsAs you have seen in several examples in class, we can understand a lot about a data set based on information that is given to us in a study about the central tendency and variation of a data set.Describe the following terms in your own words:MeanStandard DeviationZ-ScoresCorrelationFinally, if someone told you that the average of a data set was 40, and that standard deviation was 10, what else could you derive from that information?
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