| 13 | Use the following data to answer the questions below | |||
| SAT | Income | GPA | ||
| 1651 | 47000 | 2.79 | ||
| 1581 | 34000 | 2.97 | ||
| 1790 | 90000 | 3.48 | ||
| 1626 | 60000 | 2.5 | ||
| 1754 | 113000 | 2.92 | ||
| 1754 | 71000 | 3.76 | ||
| 1706 | 105000 | 2.8 | ||
| 1765 | 59000 | 3.26 | ||
| 1786 | 50000 | 3.89 | ||
| 1686 | 27000 | 3.67 | ||
| 1790 | 107000 | 3.31 | ||
| 1707 | 109000 | 3.16 | ||
| 1804 | 81000 | 3.73 | ||
| 1712 | 62000 | 3.21 | ||
| 1607 | 72000 | 2.8 | ||
| 1738 | 63000 | 3.7 | ||
| 1790 | 55000 | 3.86 | ||
| 1796 | 64000 | 3.91 | ||
| 1547 | 47000 | 2.63 | ||
| 1692 | 89000 | 2.98 | ||
| 1711 | 42000 | 3.45 | ||
| 1689 | 70000 | 3.06 | ||
| 1740 | 118000 | 2.88 | ||
| 1940 | 113000 | 3.96 | ||
| i | What predicts SAT scores better - GPA or Income? | |||
| j | Why? | |||

SAT
score predict better by Income
1) Because R square blue for that is greater than other i.e. 0.2211 which means that 22.11% of Variability is explained by model where as 14.10% Variability is explained by other model ( GPA) .
2) Also by model significance - SAT & Income model is significant as p value < 0.05 where as SAT & GPA model has insignificant as p value > 0.05 PL??
13 Use the following data to answer the questions below SAT Income GPA 1651 47000 2.79...