# Study

**Chapter Summary**

When you are looking at the relationship between two interval-level variables, you can use regression to find the line that best describes that relationship. The intercept is interpreted as the value of the dependent variable that you would expect to see if the independent variable has a value of zero. The slope tells you how much the dependent variable changes, on average, for every unit increase in the independent variable. If the slope is positive, there is a positive relationship between the two variables; if it is negative, there is a negative relationship. The slope will have a significance value connected to it that is the statistical significance of the relationship. It will tell you whether or not you can reject the null hypothesis. Finally, regression tells you the R2 for the relationship. This is a PRE measure of the proportion of variance in the dependent variable that is explained by the independent variable. To calculate these statistics, you will complete two work tables.

**Learning Objectives**

After reading this chapter, you should:

- Know how to calculate a bivariate regression
- Understand the connection between regression statistics and the equation of a line
- Be able to interpret the constant and the slope
- Be able to complete a three step analysis of a bivariate regression
- Be able to interpret R2 as a PRE measure
- Be able to use regression to conduct a time series analysis
- Be able to interpret the slope of a dummy variable
- Know how to run a regression in SPSS
- Be able to save the predicted value from a regression in SPSS
- Be able to compute a new variable in SPSS
- Know how to create a professional looking regression table in Word