1.A math placement test is given to all entering freshmen at a small college. A student who receives a grade below 35 is denied admission to the regular math course and placed in a remedial class. The placement test scores and the final grades or 20 students who took the regular course were recorded as follows: ) Compute the relationship using pearsons correlation and interpret the result. Test the hypothesis of the result using 5% level. Show the linear regression equation. ) If the minimum passing grade of the course is 60, what is placement test score should students in the future be denied admission to this course?

Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?