For a sample of over 160 college students, the following variables were measured: Y = height X1 = mother’s height X2 = father’s height X3 = 1 if male, 0 if female The goal is to predict student’s height using the mother’s and father’s heights, and sex, where sex is categorized using the variable “male” = 1 if male, 0 if female. Question 1 The regression model is __________________________________________ Regress command results (remember that we now have n = 165 cases; we removed one outlier): Source | SS df MS Number of obs = 165 -------------+------------------------------ F( 3, 161) = 104.38 Model | 1679.17741 3 559.725803 Prob > F = 0.0000 Residual | 863.31653 161 5.36221447 R-squared = 0.6604 -------------+------------------------------ Adj R-squared = 0.6541 Total | 2542.49394 164 15.5030118 Root MSE = 2.3156 ------------------------------------------------------------------------------ height | Coef. Std. Err. t P>|t| [95% Conf. Interval] momheight | .2996154 .0687614 4.36 0.000 .1638247 .435406 dadheight | .412135 .0510733 8.07 0.000 .311275 .512995 male | 5.298218 .3637717 14.56 0.000 4.579839 6.016597 constant | 16.96746 4.658309 3.64 0.000 7.768196 26.16673 Question 2 3-a - Is the model useful and if so how did you determine it is useful? What measures did you use? 3-b - Which (if any) of the independent variables, at a confidence level of 95%, are useful in the model? 3-c – Would your answer to question 3-b change if you use a 90% confidence level. 3-d - Which factor (independent variable) is the best predictor? Question 3 The college has a policy that a student must be 5 ft 11 inches tall in order to try out for a particular sport. Given my mother’s height is 5 ft 4 inches tall and my father was 6 ft tall will I be allowed to try out for the team. You must show calculations.
For a sample of over 160 college students, the following variables were measured:
Y = height
X1 = mother’s height
X2 = father’s height
X3 = 1 if male, 0 if female
The goal is to predict student’s height using the mother’s and father’s heights, and sex, where sex is categorized using the variable “male” = 1 if male, 0 if female.
Question 1
The regression model is __________________________________________
Regress command results (remember that we now have n = 165 cases; we removed one outlier):
Source | SS df MS Number of obs = 165
-------------+------------------------------ F( 3, 161) = 104.38
Model | 1679.17741 3 559.725803 Prob > F = 0.0000
Residual | 863.31653 161 5.36221447 R-squared = 0.6604
-------------+------------------------------ Adj R-squared = 0.6541
Total | 2542.49394 164 15.5030118 Root MSE = 2.3156
------------------------------------------------------------------------------
height | Coef. Std. Err. t P>|t| [95% Conf. Interval]
momheight | .2996154 .0687614 4.36 0.000 .1638247 .435406
dadheight | .412135 .0510733 8.07 0.000 .311275 .512995
male | 5.298218 .3637717 14.56 0.000 4.579839 6.016597
constant | 16.96746 4.658309 3.64 0.000 7.768196 26.16673
Question 2
3-a - Is the model useful and if so how did you determine it is useful? What measures did you use?
3-b - Which (if any) of the independent variables, at a confidence level of 95%, are useful in the model?
3-c – Would your answer to question 3-b change if you use a 90% confidence level.
3-d - Which factor (independent variable) is the best predictor?
Question 3
The college has a policy that a student must be 5 ft 11 inches tall in order to try out for a particular sport. Given my mother’s height is 5 ft 4 inches tall and my father was 6 ft tall will I be allowed to try out for the team. You must show calculations.
Note:
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