Researchers Alfred P. Rovai and Marcus D. Childress asked the following question: "How can resistance to reduction of computer anxiety among teacher education students be explained and predicted?" (Journal of Research on Technology in Education, 35(2)). To answer this research question, they identified 86 undergraduate teacher education students enrolled in a computer literacy course and administered a series of questionnaires that quantified various predictors of the response variable, computer anxiety, y. For example, computer anxiety was measured by administering each student the Computer Anxiety Scale. This score ranges from 20 to 100, with higher scores indicating higher levels of computer anxiety. The explanatory variables were:

x1: Computer confidence on a scale from 10 to 40, with higher scores indicating higher confidence

x2: Computer knowledge on a scale from 0 to 33, with 0 indicating no computer knowledge and 33 indicating superior computer knowledge

x3: Computer liking on a scale from 10 to 40, with higher scores indicating a greater like of computers

x4: Trait anxiety on a scale from 20 to 80, with higher scores indicating a higher level of overall anxiety

The multiple regression model was

Y̅ = 84.04 - 0.87x1 - 0.51x2 - 0.45x3 + 0.33x4

(a) The reported P-value of the regression model was less than 0.0001. Would you reject the null hypothesis

H0: β1 = β2 = β3 = β4 = 0?

(b) Interpret the slope coefficients of the model in part (a). Are they all reasonable?

(c) Predict the computer anxiety score of an individual whose computer confidence score was 25, computer knowledge score was 19, computer liking score was 20, and trait anxiety score was 43.

(d) The coefficient of determination for this model is 0.69. Interpret this value.

(e) The article states that "regression assumptions were tested and found to be tenable." Explain what this means.