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Exam 15: Multiple Regression and Model Building

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Question 41

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Below is a partial multiple regression computer output.

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Question 42

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When independent variables in a regression model are related to,or dependent on,each other,then there exists _____________ among the independent variables.

A) Multicollinearity
B) Autocorrelation
C) Independence
D) Probability

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Question 43

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A partial F test is used to assess when at least one variable in a subset of squared and interaction variables in the multiple regression model is significant.

Below is a partial multiple regression ANOVA table.

The assumption of independent error terms in regression analysis is often violated when using time-series data.

The manufacturer of a light fixture believes that the dollars spent on advertising,the price of the fixture and the number of retail stores selling the fixture in a particular month influence the light fixture sales.The manufacturer randomly selects 10 months and collects the following data:

Which one of the following tools is not used to check the normality of residuals assumption for a multiple regression model?

Consider the following partial computer output for a multiple regression model.

Consider the following partial computer output for a multiple regression model.

A very insignificant independent variable (an independent variable that has a very weak relationship with the dependent variable) is added to a multiple regression equation.As a result of this change,the value of the explained variation (SSR) will _________,the value of the multiple coefficient of determination (R²) will _________,and the calculated value of the F statistic will most likely _________.

Below is a partial multiple regression ANOVA table.

An acceptable residual plot exhibits:

The management of a professional baseball team is in the process of determining the budget for next year.A major component of future revenue is attendance at the home games.In order to predict attendance at home games,the team statistician has used a multiple regression model with dummy variables.The model is of the form y = β₀ + β₁x₁ + β₂x₂ + β₃x₃ + ε,where: y = attendance at a home game. x₁ = current power rating of the team on a scale from 0 to 100 before the game. x₂ and x₃ are dummy variables,and they are defined below. x₂ = 1,if weekend, x₂ = 0,otherwise. x₃ = 1,if weather is favorable, x₃ = 0,otherwise. After collecting the data,based on 30 games from last year,and implementing the above stated multiple regression model,the team statistician obtained the following least squares multiple regression equation:

Consider the following partial computer output for a multiple regression model.

In multiple regression analysis,if the simple correlation coefficient between the dependent variable and one of the independent variables is .95,then this indicates that the problem of multicollinearity exists.

The manufacturer of a light fixture believes that the dollars spent on advertising,the price of the fixture,and the number of retail stores selling the fixture in a particular month influence the light fixture sales.The manufacturer randomly selects 10 months and collects the following data:

In a multiple regression model we can conclude that multicollinearity exists if the average variance inflation factor $( \overline { V I F } )$ Is substantially greater than _____.

The ____________ term describes the effects on y of all factors other than the independent variables in a multiple regression model.

If a multiple regression model has a(n) ____________ statistic substantially greater than k + 1,then it can be shown that this model has substantial bias and is undesirable.

In the quadratic regression model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 1 } ^ { 2 } + \varepsilon$ The ?₂ term represents the: