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BUS 520 TUI Organic Food Simple Linear Regression Discussion Analysis & Sheet
MODULE 3 CASESIMPLE LINEAR REGRESSIONAssignment OverviewYou are a consultant who works for the Diligent Consulting Group. ...
BUS 520 TUI Organic Food Simple Linear Regression Discussion Analysis & Sheet
MODULE 3 CASESIMPLE LINEAR REGRESSIONAssignment OverviewYou are a consultant who works for the Diligent Consulting Group. In this Case, you are engaged on a consulting basis by Loving Organic Foods. In order to get a better idea of what might have motivated customers’ buying habits you are asked to analyze the factors that impact organic food expenditures. You opt to do this using linear regression analysis.Case AssignmentUsing Excel, generate regression estimates for the following model:Annual Amount Spent on Organic Food = α + bAgeAfter you have reviewed the results from the estimation, write a report to your boss that interprets the results that you obtained. Please include the following in your report:The regression output you generated in Excel.Your interpretation of the coefficient of determination (r-squared).Your interpretation of the coefficient estimate for the Age variable.Your interpretation of the statistical significance of the coefficient estimate for the Age variable.The regression equation with estimates substituted into the equation. (Note: Once the estimates are substituted into the regression equation, it should take a form similar to this: y = 10 +2x)A discussion of how this equation in item 5 above can be used to estimate annual expenditures on organic food.An estimate of “Annual Amount Spent on Organic Food” for the average consumer. (Note: You will need to substitute the average age into the regression equation for x, the intercept for α, and solve for y.)Data: Download the Excel-based data file: BUS520 Module 3 Case.Assignment ExpectationsWritten ReportLength requirements: 3–4 pages minimum (not including Cover and Reference pages). NOTE: You must submit 3–4 pages of written discussion and analysis.Provide a brief introduction to/background of the problem, similar to the introduction/background you provided in Module 1 and 2 Case submissions.Provide a brief discussion of linear regression analysis, including the value of using this estimation technique.Provide a written analysis that addresses each of requirements listed under the “Case Assignment” section.Write clearly, simply, and logically. Use double-spaced, black Verdana or Times Roman font in 12 pt. type size.Please use keywords as headings to organize the report.Avoid redundancy and general statements such as "All organizations exist to make a profit." Make every sentence count.Paraphrase the facts using your own words and ideas, employing quotes sparingly. Quotes, if absolutely necessary, should rarely exceed five words.Upload both your written report and Excel file to the Case 3 Dropbox.Module 3 - BackgroundSIMPLE LINEAR REGRESSIONRequired ReadingThe primary resource for this module is Introductory Business Statistics by Alexander, Illowsky, and Dean.Alexander, H., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. Openstax. Retrieved from https://openstax.org/details/books/introductory-business-statisticsFor Module 3, you should read through the following material in this textbook.Chapter 13: Linear Regression and CorrelationSections 13.1, 13.2, 13.3 and 13.7 onlyThis chapter introduces correlation coefficients and linear regression analysis. Section 13.7 explains how to create regression estimates in Excel. There is also tutorial link below that explains how to use that tool. We will cover the remaining sections in Module 4.You are now familiar with several tools in the Analysis Toolpak. Regression analysis is just another one of those tools. Please review the following tutorial for help in generating regression estimates in Excel:https://www.excel-easy.com/examples/regression.html
6 pages
Elm538 R1 Wk3 Formative Summative Math Assessments.edited
Choose one formative and one summative assessment, developed by you or obtained from another source, that are intended to ...
Elm538 R1 Wk3 Formative Summative Math Assessments.edited
Choose one formative and one summative assessment, developed by you or obtained from another source, that are intended to assess the same mathematics ...
SNHU Regional Average Market Price of Places of Residence Statistics Report
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address ...
SNHU Regional Average Market Price of Places of Residence Statistics Report
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address research problems
Perform hypothesis testing to address an authentic problem
Overview
In this project, you will apply inference methods for means to test your hypotheses about the housing sales market for a region of the United States. You will use appropriate sampling and statistical methods.
Scenario
You have been hired by your regional real estate company to determine if your region’s housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report:
Are housing prices in your regional market higher than the national market average?
Is the square footage for homes in your region different than the average square footage for homes in the national market?
For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market?
You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, complete the statistical analyses, and provide a report to the regional sales director. You will do so by completing the Project Two Template located in the What to Submit area below.
Directions
Introduction
Purpose: What was the purpose of your analysis, and what is your approach?
Define a random sample and two hypotheses (means) to analyze.
Sample: Define your sample. Take a random sample of 100 observations for your region.
Describe what is included in your sample (i.e., states, region, years or months).
Questions and type of test: For your selected sample, define two hypothesis questions and the appropriate type of test hypothesis for each. Address the following for each hypothesis:
Describe the population parameter for the variable you are analyzing.
Describe your hypothesis in your own words.
Describe the inference test you will use.
Identify the test statistic.
Level of confidence: Discuss how you will use estimation and conference intervals to help you solve the problem.
1-Tail Test
Hypothesis: Define your hypothesis.
Define the population parameter.
Write null (Ho) and alternative (Ha) hypotheses.
Specify your significance level.
Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test.
Summarize your sample data using appropriate graphical displays and summary statistics.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation.
Summarize your sample data, describing the center, spread, and shape in comparison to the national information.
Check the conditions.
Determine if the normal condition has been met.
Determine if there are any other conditions that you should check and whether they have been met.
Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t).
Calculate the probability (p value).
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
2-Tail Test
Hypotheses: Define your hypothesis.
Define the population parameter.
Write null and alternative hypotheses.
State your significance level.
Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test.
Summarize your sample data using appropriate graphical displays and summary statistics.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation.
Summarize your sample data, describing the center, spread, and shape in comparison to the national information.
Check the assumptions.
Determine if the normal condition has been met.
Determine if there are any other conditions that should be checked on and whether they have been met.
Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t).
Determine the probability (p value).
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
Comparison of the test results: See Question 3 from the Scenario section.
Calculate a 95% confidence interval. Show or describe your method of calculation.
Interpret a 95% confidence interval.
Final Conclusions
Summarize your findings: Refer back to the Introduction section above and summarize your findings of the sample you selected.
Discuss: Discuss whether you were surprised by the findings. Why or why not?
What to Submit
To complete this project, you must submit the following:
Project Two Template: Use this template to structure your report, and submit the finished version as a Word document.
Supporting Materials
The following resources may help support your work on the project:
Data Set: House Listing Price by Region
Use this data for input in your project report.
Document: National Statistics and Graphs
Use this data for input in your project report.
Use these tutorials for support with the Excel functions you will use in the project:
Tutorial: Random Sampling in Excel
Tutorial: Scatterplots in Excel
Tutorial: Descriptive Statistics in Excel
Tutorial: Creating Histograms in Excel
Big Data Architecture on the Cloud Platform
You are working as an analytics developer for a government firm such as CDC. You have collected close to 200 TB of medical ...
Big Data Architecture on the Cloud Platform
You are working as an analytics developer for a government firm such as CDC. You have collected close to 200 TB of medical health records. CDC needs to convert all the existing data to another format such as parquet within three weeks. It takes three days to convert one terabyte of existing data to the parquet format. So it is impossible to use the traditional approach to convert 200 TB of data from one format to the other within three weeks.
You are required to use Big Data architecture on the cloud platform. You need to design the system architecture and write one page summary about how your job is complete.
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Most Popular Content
BUS 520 TUI Organic Food Simple Linear Regression Discussion Analysis & Sheet
MODULE 3 CASESIMPLE LINEAR REGRESSIONAssignment OverviewYou are a consultant who works for the Diligent Consulting Group. ...
BUS 520 TUI Organic Food Simple Linear Regression Discussion Analysis & Sheet
MODULE 3 CASESIMPLE LINEAR REGRESSIONAssignment OverviewYou are a consultant who works for the Diligent Consulting Group. In this Case, you are engaged on a consulting basis by Loving Organic Foods. In order to get a better idea of what might have motivated customers’ buying habits you are asked to analyze the factors that impact organic food expenditures. You opt to do this using linear regression analysis.Case AssignmentUsing Excel, generate regression estimates for the following model:Annual Amount Spent on Organic Food = α + bAgeAfter you have reviewed the results from the estimation, write a report to your boss that interprets the results that you obtained. Please include the following in your report:The regression output you generated in Excel.Your interpretation of the coefficient of determination (r-squared).Your interpretation of the coefficient estimate for the Age variable.Your interpretation of the statistical significance of the coefficient estimate for the Age variable.The regression equation with estimates substituted into the equation. (Note: Once the estimates are substituted into the regression equation, it should take a form similar to this: y = 10 +2x)A discussion of how this equation in item 5 above can be used to estimate annual expenditures on organic food.An estimate of “Annual Amount Spent on Organic Food” for the average consumer. (Note: You will need to substitute the average age into the regression equation for x, the intercept for α, and solve for y.)Data: Download the Excel-based data file: BUS520 Module 3 Case.Assignment ExpectationsWritten ReportLength requirements: 3–4 pages minimum (not including Cover and Reference pages). NOTE: You must submit 3–4 pages of written discussion and analysis.Provide a brief introduction to/background of the problem, similar to the introduction/background you provided in Module 1 and 2 Case submissions.Provide a brief discussion of linear regression analysis, including the value of using this estimation technique.Provide a written analysis that addresses each of requirements listed under the “Case Assignment” section.Write clearly, simply, and logically. Use double-spaced, black Verdana or Times Roman font in 12 pt. type size.Please use keywords as headings to organize the report.Avoid redundancy and general statements such as "All organizations exist to make a profit." Make every sentence count.Paraphrase the facts using your own words and ideas, employing quotes sparingly. Quotes, if absolutely necessary, should rarely exceed five words.Upload both your written report and Excel file to the Case 3 Dropbox.Module 3 - BackgroundSIMPLE LINEAR REGRESSIONRequired ReadingThe primary resource for this module is Introductory Business Statistics by Alexander, Illowsky, and Dean.Alexander, H., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. Openstax. Retrieved from https://openstax.org/details/books/introductory-business-statisticsFor Module 3, you should read through the following material in this textbook.Chapter 13: Linear Regression and CorrelationSections 13.1, 13.2, 13.3 and 13.7 onlyThis chapter introduces correlation coefficients and linear regression analysis. Section 13.7 explains how to create regression estimates in Excel. There is also tutorial link below that explains how to use that tool. We will cover the remaining sections in Module 4.You are now familiar with several tools in the Analysis Toolpak. Regression analysis is just another one of those tools. Please review the following tutorial for help in generating regression estimates in Excel:https://www.excel-easy.com/examples/regression.html
6 pages
Elm538 R1 Wk3 Formative Summative Math Assessments.edited
Choose one formative and one summative assessment, developed by you or obtained from another source, that are intended to ...
Elm538 R1 Wk3 Formative Summative Math Assessments.edited
Choose one formative and one summative assessment, developed by you or obtained from another source, that are intended to assess the same mathematics ...
SNHU Regional Average Market Price of Places of Residence Statistics Report
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address ...
SNHU Regional Average Market Price of Places of Residence Statistics Report
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address research problems
Perform hypothesis testing to address an authentic problem
Overview
In this project, you will apply inference methods for means to test your hypotheses about the housing sales market for a region of the United States. You will use appropriate sampling and statistical methods.
Scenario
You have been hired by your regional real estate company to determine if your region’s housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report:
Are housing prices in your regional market higher than the national market average?
Is the square footage for homes in your region different than the average square footage for homes in the national market?
For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market?
You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, complete the statistical analyses, and provide a report to the regional sales director. You will do so by completing the Project Two Template located in the What to Submit area below.
Directions
Introduction
Purpose: What was the purpose of your analysis, and what is your approach?
Define a random sample and two hypotheses (means) to analyze.
Sample: Define your sample. Take a random sample of 100 observations for your region.
Describe what is included in your sample (i.e., states, region, years or months).
Questions and type of test: For your selected sample, define two hypothesis questions and the appropriate type of test hypothesis for each. Address the following for each hypothesis:
Describe the population parameter for the variable you are analyzing.
Describe your hypothesis in your own words.
Describe the inference test you will use.
Identify the test statistic.
Level of confidence: Discuss how you will use estimation and conference intervals to help you solve the problem.
1-Tail Test
Hypothesis: Define your hypothesis.
Define the population parameter.
Write null (Ho) and alternative (Ha) hypotheses.
Specify your significance level.
Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test.
Summarize your sample data using appropriate graphical displays and summary statistics.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation.
Summarize your sample data, describing the center, spread, and shape in comparison to the national information.
Check the conditions.
Determine if the normal condition has been met.
Determine if there are any other conditions that you should check and whether they have been met.
Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t).
Calculate the probability (p value).
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
2-Tail Test
Hypotheses: Define your hypothesis.
Define the population parameter.
Write null and alternative hypotheses.
State your significance level.
Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test.
Summarize your sample data using appropriate graphical displays and summary statistics.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation.
Summarize your sample data, describing the center, spread, and shape in comparison to the national information.
Check the assumptions.
Determine if the normal condition has been met.
Determine if there are any other conditions that should be checked on and whether they have been met.
Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t).
Determine the probability (p value).
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
Comparison of the test results: See Question 3 from the Scenario section.
Calculate a 95% confidence interval. Show or describe your method of calculation.
Interpret a 95% confidence interval.
Final Conclusions
Summarize your findings: Refer back to the Introduction section above and summarize your findings of the sample you selected.
Discuss: Discuss whether you were surprised by the findings. Why or why not?
What to Submit
To complete this project, you must submit the following:
Project Two Template: Use this template to structure your report, and submit the finished version as a Word document.
Supporting Materials
The following resources may help support your work on the project:
Data Set: House Listing Price by Region
Use this data for input in your project report.
Document: National Statistics and Graphs
Use this data for input in your project report.
Use these tutorials for support with the Excel functions you will use in the project:
Tutorial: Random Sampling in Excel
Tutorial: Scatterplots in Excel
Tutorial: Descriptive Statistics in Excel
Tutorial: Creating Histograms in Excel
Big Data Architecture on the Cloud Platform
You are working as an analytics developer for a government firm such as CDC. You have collected close to 200 TB of medical ...
Big Data Architecture on the Cloud Platform
You are working as an analytics developer for a government firm such as CDC. You have collected close to 200 TB of medical health records. CDC needs to convert all the existing data to another format such as parquet within three weeks. It takes three days to convert one terabyte of existing data to the parquet format. So it is impossible to use the traditional approach to convert 200 TB of data from one format to the other within three weeks.
You are required to use Big Data architecture on the cloud platform. You need to design the system architecture and write one page summary about how your job is complete.
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