Question

PLEASE ANSWER ALL QUESTIONS! AND EXPLANATIONS IF POSSIBLE. THANK YOU

True/False: Q. # 56 - 59

56. The proportion of the Y score variance explained by X score variance equals R squared. 57. With a multiple regression formula of

Ỳ (College GPA) = (.71) * (High School GPA) – (2.08) * (Number of Days Missed in High School) + .91

one would interpret the formula as showing a positive relationship between College GPA and Number of Days Missed in High School.

58. In Multiple regression, beta scores are used to compare relative influence of independent variables on predicting dependent variable.

59. In Multiple Regression, Standard Error of Estimate gets be larger when r (Pearson Product Moment Correlation Coefficient) is smaller.

Note: Open-ended

60. Using #57 Question, write down Null Hypothesis:

Answer 1

56. False

This is because the coefficient of Number of Days Missed in High School is -2.08. This means that there is a negative relationship between College GPA and Number of Days Missed in High School.

58. True

This is because we test the coefficient of the independent variables to check the significance of the model.

59. True

The standard Error of Estimate and r have an inverse relationship. So, when Standard Error of Estimate gets to be larger, r will be smaller.

60. The hypothesis being tested is:

H0: β1 = 0 (Null hypothesis)

H1: β1 ≠ 0