Model Summary |
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
1 | .521a | .271 | .268 | 3.218 |
a. Predictors: (Constant), Mother's height in inches, Father's height in inches |
The model summary table indicates that R value is 0.521 which is a moderate correlation. The R square value 27% (R2) of the variation in son’s height is explained by the variation in the two independent variables “Father’s height in inches” and “Mother’s height in inches”. The adjusted R square value can be generalize to the population and indicates that 26.8% of the variation in son’s height is explained by the variation in father’s height and mother’s height which ...view middle of the document...
507. For one unit increase in Mother’s height, the son’s height decreased by 0.089. However, the standardized score is 0.547 which means for every one standard deviation increase in father’s height, the son’s height increases by 0.547 of a standard deviation. The t- value= 11.701 and is statistically significant (p<0.001). Although, b= 0.507, in the general population we would expect, with a 95% likelihood, that a true value of b would fall somewhere between 0.422 and 0.592. The strongest predictor based on the standardized beta value is the father’s height (0.547).
The mother’s height itself is not statistically significant (p= 0.103) and does not predict the son’s height.
Son’s height (y) = a + b1x1 + b2x2
Son’s height (y) = 40.163 + 0.507x1 - 0.089x
A. By looking at the table, it is clear that the p-value for both the systolic and diastolic blood pressure is the same that is (p= 0.001), which means that according to the p-value, both of them are statistically significant. However, the chi-square value for systolic blood pressure (χ² = 141.4) is greater than the chi-square value for diastolic blood pressure (χ²= 80.2), which shows that the systolic blood pressure contributes more to the hypertension than the diastolic blood pressure. As far as comparison is concerned, since there are no standardized...