For a set of data, the following summaries were calculated: I = 12.6 y = 34.2 ST = 3.1 Sy = 4.4 r = 0.55 What is the slope of the regression line for predicting y from x? O 0.55 O 0.78 O 1.49 O 0.385\fA regression model is calculated to predict an individual's weight {in pounds} based on their height {in inches}. The slope of the regression line is estimated to be 3.6. Whlcl'l of the following interpretations. of the slope is correct? 0 Individuals whose heights differ bv one inch tend to have a difference in weight of about 3.6 pounds. (:3 No answer text provided. 0 Individuals whose weights differ bv one pound tend to have a difference in height of about 8.6 inches. O Growing one inch taller will tvpicallv cause someone to gain ab out 3.6 pounds in weight. The least-squares regression line is of the form ii = o. | hm. Suppose that for a data set, we have the following numerical summaries: The sample mean for x is: E: = 4 The sample standard deviation form: is : a: = 2 The sample mean for y is: if = Q The sample standard deviation for}; is : 31,. = 5 The correlation coefcient is: 1' = 0.5 What is the resulting form of the regression line? O=3+L5c O=3+1.5:.: O n_25 1 y 3 +63 \fSuppose we have a data set that is described by a Normal distribution with mean 20 and standard deviation 3. Approximately 95% of the data set will lie in which of the following intervals? C] [14, 26] E] [11 231 C1 [11, 291 C] [15534.5]