1. Using the data sashelp.class in SAS, run a single sample t-test to determine if the mean of the incoming class of 13-year-old students at a private school in GA is different from the national average of 105 pounds. Use an alpha of .05. However, first test to see if weight is normally distributed. Include your code and a screenshot of the results. Also, include a) the null and alternative hypotheses; b) the df; c) the t value and p value; d) the 95% confidence interval; e) brief explanation of overall findings. 2. Using the data sashelp.stocks in SAS, run a paired sample t-test to determine if there is a significant difference in the value of the stock from open to close (assume something major happened before the closing bell). Use an alpha of .05. However, first test to see if price at open and close is normally distributed. Include your code and a screenshot of the results. Also, include a) the null and alternative hypotheses; b) the df; c) the t value and p value; d) the 95% confidence interval; e) brief explanation of overall findings. 3 . Using the data sashelp.heart in SAS, run an independent sample t-test to determine if there is a significant difference between males and females in their diastolic blood pressure. Use an alpha of .05. However, first test to see if blood pressure is normally distributed. Evaluate if equal variances can be assumed. Include your code and a screenshot of the results. Also, include a) the null and alternative hypotheses; b) the df; c) the t value and p value; d) the 95% confidence interval; e) brief explanation of overall findings. 4. Do the same thing as #3 above, but now assess if males have a lower diastolic blood pressure than females. 5 . Using sashelp.heart, run a one way ANOVA to determine if there are significant differences in age by blood pressure status. Use an alpha of .05. However, first test to see if age is normally distributed. Include your code and a screenshot of the results. Also, include a) the null and alternative hypotheses; b) the df; c) the t value and p value; d) the 95% confidence interval; e) explanation of overall findings. 6. Using sashelp.heart, assess whether weight and height are correlated using a Pearson r. 7. Using sashelp.cars, run a multiple regression model where Weight of a car and Cylinders are used to predict MPG. Which of the two regressors are significant? 8. Run a chi square test using the SAS data sashelp.birthwet variables married and drinking. Is there a relationship between being married and drinking? Use the chi-square, p-value, and percentages to interpret the results. What is a possible explanation for the results? What is a third (or fourth) variable that could play a role in the results