Description
Regression Project
1. Find a set of data that includes two variables you think may be related. In your report (Word document or Google doc), explain which variable you think would be the independent variable and which one you think would be the dependent variable and why (You can find a list of data sources at the end of this document). (6pts)
For example, if you found a data set that had crime rate and average income for 100 cities, you might expect average income to predict crime rate. The more affluent the community, the less likely for crime to occur. So average income would be the independent variable and crime rate would be the dependent variable (crime rate “depends on” average income).
2. Find a quote, statistic, or sentence from an article that would support the relationship you have decided to test. (2pts)
For example, “On the enforcement side, expansion and modernization of the police force, improved apprehension system, stricter implementation of punishments, changes in legal and justice systems, and general advancements in education, values and societal norms and conducts account for the lesser crime rate.” (Source:
3. Using Megastat, run the scatterplot, correlation, and regression analyses. Using cut and paste, put the scatterplot within your document/report. Explain what kind of relationship is shown by the scatterplot (negative or positive? Strong or weak?) (4pts)
4. Using cut and paste or a screen shot, put the correlation and regression results in your document/report. (4pts) Then answer the following questions:
a. What is the correlation? Was it significant? (4pts)
b. What is the r-squared? How would you interpret it? (4pts)
c. What is the regression equation? (6pts)
d. How would you interpret the slope? (2pts)
e. Is the intercept meaningful? Explain. (2pts)
f. Is the model significant? Explain what that means. (4pts)
5. Conclude with a summary of findings and suggestions for future research (6pts)
Use Calibri 12-point font.