Reference no: EM131811043
Question: Perform a multiple regression analysis using business data of your choice from the Internet, the library, or your company and write up the results as a report to upper-level management, either as a background summary report or as a proposal for action. You should have a significant F test and at least one significant t-test (so that you will be able to make some strong conclusions in your project). Your report should include five to seven pages plus an appendix and should be based on the following format:
a. Introduction: Describe the background and questions of interest and the data set clearly as if to an intelligent person who knows nothing about the details of the situation.
b. Analysis and Methods: Analyze the data, presenting displays and results, explaining as you go along. Consider including some of each of the following:
(1) Explore the data using histograms or box plots for each variable and using scatterplots for each pair of variables.
(2) Use a transformation (such as the logarithm) only if this would clearly help the analysis by dealing with a big problem in the diagnostic plot.
(3) Compute the correlation of each pair of variables and interpret these values.
(4) Report the multiple linear regressions to predict one variable (chosen appropriately) from the others by explaining the regression equation and interpreting each regression coefficient. Comment on the quality of the regression analysis in terms of both prediction accuracy (standard error of estimate) and how well the relationship is explained (coefficient of determination). Report statistical significance using p-values both overall (F test) and for each regression coefficient (t-tests). In particular, are your results reasonable?
c. Conclusion and summary: What has this analysis told you about the situation? How have your questions been answered? What have you learned?
d. Appendix: List the data, with their source indicated. (This does not count toward the page limit.)
Analyzing the situation on a seasonally adjusted basis
: At a meeting, everyone seems to be pleased by the fact that sales increased from $21,791,000 to $22,675,000 from the third to the fourth quarter.
|
Explain the time-series method of analysis
: Which time-series method of analysis would be most appropriate to a situation in which prices are lower at harvest time in the fall but are typically higher.
|
What important information is missing in given references
: What important information is missing from each of the following references? Personal communication, 2016.
|
Summarizing the relationship between gender and salary
: Write a three- to five-page report summarizing the relationship between gender and salary for these employees. Be sure to discuss the results of the following.
|
Compute the correlation of each pair of variables
: Perform a multiple regression analysis using business data of your choice from the Internet, the library, or your company and write up the results.
|
What are the forecast limits
: What role does a mathematical model play in forecasting? Why does not trend-seasonal analysis produce forecast limits?
|
What are the values of the regression coefficients
: A coworker of yours is very pleased, having just found an R2 value of 100%, indicating that the regression equation has explained all of the variability.
|
Find predicted sales for a store that is in a shopping mall
: Consider Table, showing the partial results from a multiple regression analysis (with significant F test) that explains the annual sales of 25 grocery stores.
|
Find the regression equation of the form predicted profit
: Setting prices is rarely an easy task. A low price usually results in higher sales, but there will be less profit per sale.
|