Shown in the SPSS output for creating a regression equation to predict students' attitudes toward statistics from their attitudes toward Ariana grande and beer. Model                        Unstandardized Coefficients              Standardized Coefficients            t            Sig.                                           B                                     Std. Error                  Beta                       1 (Constant)                   4.974                                    0.590                                                8.432         0.000 AttAriana                        0.264                                    0.155                     0.256                  1.701         0.097 Attbeer                         - 0.309                                    0.122                   - 0.381                - 2.536         0.015 Coefficients a a Dependent Variable: Attstatistics Which of these represents the correct regression equation for this information? a. Y = 0.59 + 0.155 (X1) + 0.122 (X2) b. Y = 4.974 + 0.256 (X1) - 0.381 (X2) c. Y = 4.974 + 0.264 (X1) - 0.309 (X2) d. Y = 8.432 + 1.701 (X1) - 2.536 (X2)

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?

Noise and Intelligibility Audiologists study the intelligibility of spoken sentences under different noise levels. Intelligibility, the MRT score, is measured as the percent of a spoken sentence that the listener can decipher at a cesl4ain noise level in decibels (dB). The table shows the results of one such test. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Find the correlation coefficient. Is a linear model appropriate? (d) Use the linear model in put (b) to estimate the intelligibility of a sentence at a 94-dB noise level.