The worksheet will be provided to you by the instructor. That is so that you won't know whose blood pressure and pulse rate is whose. Although gender and age may be related to blood pressure and pulse rate, we're not collecting that information for this project. If this were a more clinical study, we would collect and analyze that data and more.

The variables recorded are called **systolic**,
**diastolic**, and **pulse**.

- Choose File / Open Worksheet (make sure it's open worksheet and and not open project)
- Move through the file system to
**P:\james\math113** - Open the worksheet called
**blood.mtw**. - Choose File / Save Project As
- Type a name that is unique to your group
- Click OK

From now on, when you need to work with the project, open the one for your group.

The following examples use the response variable y = diastolic and the predictor variable x = systolic. Be sure to use your variables when you actually generate the results.

Should you wish to duplicate the results in the example, the data is from the Spring 2005 semester of Math 113.

This question wants you to generate a scatterplot and try to determine the value of the correlation coefficient based on the scatterplot alone.

- Choose Graph / Scatterplot
- Choose With Regression
- For the Y variable, double click on your response variable (mine is
**disastolic**) - For the X variable, double click on your predictor variable (mine is
**systolic**) - (Optional) Add a title by clicking Labels
- Click OK

Now make a guess as to what you think the correlation coefficient would be. For my data, there appears to be a very slight positive correlation, but it's not very good at all. I would guess about r = 0.1 (later we'll find out I'm not very close, but this is just a guess).

I'm going to describe my predictor variable of **systolic**
and my response variable of **diastolic**. Be sure you use your
variables instead of mine.

- Choose Stat / Basic Statistics / Display Descriptive Statistics
- Double click on your two variables (mine are
**systolic**and**diastolic**) - (Optional) click on Statistics and select just the statistics you need.
- Click OK

You should get some output that looks like this.

Variable N Mean StDev Variance

systolic 37 118.08 12.72 161.69

diastolic 37 69.43 7.14 51.03

Copy the sample size, mean, standard deviation, and variance onto your activity sheet.

I'm going to find the correlation between my variables of
**systolic** and **diastolic**. Be sure you use
your variables instead of mine.

- Choose Stat / Basic Statistics / Correlation
- Double click on the predictor variable (
**systolic**) and then double click on the response variable (**diastolic**). - Click OK

You will get something that looks like this. The first number is the correlation coefficient. The second number is the p-value.

Pearson correlation of systolic and diastolic = 0.400

P-Value = 0.014

Now, repeat these steps, but put the response variable first and the predictor variable second.

I'm going to describe my predictor variable of **systolic**
and my response variable of **diastolic**. Be sure you use your
variables instead of mine

- Choose Stat / Regression / Regression
- Use your response variable for the response variable
(
**diastolic**) - Use your predictor variable for the predictor variables
(
**systolic**). Even though there is room for more than one predictor variable, we're not going to have more than one until the end of the book when we talk about multiple regression. - Click OK

You will get a lot of information and you will probably need to scroll up to find what we need for question 10. The very top of the regression output should contain the regression equation.

The regression equation is

diastolic = 42.9 + 0.224 systolic

There will be an "Analysis of Variance" table that is generated as part of the regression output from question 10. It looks something like this.

Analysis of VarianceSource DF SS MS F P

Regression 1 293.34 293.34 6.65 0.014

Residual Error 35 1543.74 44.11

Total 36 1837.08

Copy down the numbers onto your activity sheet. Notice that the order of the columns is switched around on the activity sheet. There is a reason for this that will become evident when we talk more about the ANOVA table. Note that on the activity sheet, the "residual error" is abbreviated as "residual".

The one number that is missing from Minitab is the total MS value. It's not technically part of the ANOVA table, but it does serve a useful purpose.

Use the explanation on your activity sheet about the ANOVA table to answer questions 14-16.