1. Using the SAS data set Heart in the SASHELP library (scroll down in the menu following the image above to Heart), use a one-way t test to determine if the mean weight of the population from which the sample was drawn is equal to 150 pounds. Include a test of normality and generate a histogram and box plot. Should you be concerned that the tests of normality reject the null hypothesis at the .05 level?

2. Using the data set Fish in the SASHELP library, test if the mean weight of Smelt (use a filter: Species = 'Smelt')) is equal to 10. Be sure to run both a parametric and nonparametric test for this analysis. How do the parametric and nonparametric tests compare? Would you reach the same conclusion using these tests?

3. Using the SAS data set Air in the SASHELP library, do the following:

1. List the first 10 observations from this data set.

2. Run summary statistics on the variable Air (number of flights per day in thousands). Include a histogram and box plot.

3. Run a parametric and nonparametric one-way t test to determine if the mean number of flights per day (in thousands) is significantly different from 285.

4. Run the short program below and then run a one-way t test to determine if the difference scores (Diff) come from a population whose mean is zero. In this program, the RAND function is generating uniform random numbers (numbers between 0 and 1 (all with equal likelihood)). The DO loop generates 20 of these random numbers and outputs them to the Difference data set. (If you don't like to type, this program and all the other programs associated with the exercises are included in the program Create_Datasets.sas.)