Answer the following questions for each data set

Answer the following questions for each data set:

1) Are the variables cross section or time series data?

2) How do you imagine that the data were collected?

3) Is the sample size sufficient to yield a good estimate? How do you know?

4) State you hypothesis about the sign of the slope.

5) Make a scatter plot of Y against X.  Discuss what this tells you.

6) Add a Trendline to your scatter plot.  Is a linear model credible?

7) Interpret the slope coefficient.  Does the intercept have meaning given the range of the data?

8) Use Megastat to fit the regression model, including residuals and standardized residuals

9) Interpret the P-value for the slope coefficient

10) Interpret the R^2 value

11) Study the table of residuals.  Identify outliers, and unusual observations (standardized obs. that exceed 3, and 2 std. deviations respectively). 

12) Output a normal probability plot. Do you see evidence that your regression violates the assumption of normality?

13)  Inspect the residual plot to check for heteroscedasticity.  Report your conclusions.

14) Identify any observations with high leverage.