- Create two columns, one called
**exam1**and one called**exam4**. - Enter the data into the two columns

- Choose Data / Descriptive Statistics
- Click Evaluate and copy down the relevant information for
**exam1** - Change the column to column 2
- Click Evaluate and copy down the relevant information for
**exam4**

Statdisk will make a scatterplot, but you can't copy and paste it into Word. Use Minitab instead.

- Choose Analysis / Correlation and Regression
- If you put
**exam1**in column 1 and**exam4**in column 2, then all you need to do is hit Evaluate. Otherwise, choose the proper columns and then hit evaluate.

If you said that you should use the equation given by the computer to make predictions, then use the regression equation given by Statdisk. Otherwise the regression equation is that the predicted exam4 value equals the mean of the exam4 variable.

When you write the regression equation, do not put Y = b0 + b1x. You need to replace the b0 and b1 by the values of the constants given below that. You should also replace the y with exam4 and the x with exam1.

Start a new worksheet for this problem.

- Label columns as
**year**,**seatbelt**, and**fatality** - Gather the information for 1985 through 2004 from Figure 1 of the June 2005 Safety Belt Usage in Illinois available from the Illinois Department of Transportation. The data is in a chart, so you'll have to read the percents from the top of the bars. Data is available as late as 2005, but we're only able to get information through 2004 for the next part, so we'll stop in 2004.
- The National Highway Traffic Safety Administration used to have a wonderful little page with this information available, but they have removed it. From other sources, I have obtained the table below. Use the appropriate years (matched up with the information from step 2) for the fatality rate per 100 million vehicle miles travelled in Illinois.

Year | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 |
---|---|---|---|---|---|---|---|---|---|---|---|---|

Rate | 2.51 | 2.27 | 2.21 | 2.17 | 2.15 | 2.18 | 2.34 | 2.15 | 1.91 | 1.69 | 1.58 | 1.55 |

Year | 94 | 95 | 96 | 97 | 98 | 99 | 00 | 01 | 02 | 03 | 04 | 05 |
---|---|---|---|---|---|---|---|---|---|---|---|---|

Rate | 1.68 | 1.68 | 1.53 | 1.41 | 1.38 | 1.42 | 1.38 | 1.37 | 1.35 | 1.36 | 1.24 | N/A |

Statdisk will make the graph, but you can't copy and paste it into Word. Use Minitab for this part.

- Choose Analysis / Correlation and Regression
- If you put the
**seatbelt**usage in column 1 and the**fatality**rate in column 2, then all you need to do is click Evaluate, otherwise adjust the columns first.

If you determined that there was significant linear correlation (positive or negative) by rejecting the null hypothesis of no significant linear correlation, then you should use the regression equation given by the computer. Do not write "Y = b0 + b1x" but replace the b0 and b1 by their values. Also replace the Y and x by the names of the variables. Your equation should look something like "fatality = 3.03814 - 0.0230872 seatbelt" (probably not that exactly).

If, however, you decided that there was no signficant linear correlation because you retained the null hypothesis of the correlation test, then you should use the mean of y (y-bar) for the estimated equation. Your equation should be something like "fatality = ####" where #### is the numerical value of the mean of the fatality variable. You'll have to do descriptive statistics to find out what that is.