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Stepwise regression is one of the ways to prevent the problem of multicollinearity.

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True False

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Answer:

True

A linear regression model cannot be used to explore the possibility that a quadratic relationship may exist between two variables.

Free

True False

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False

The regression model y = _{0} + _{1} x_{1} + _{2} x_{2} + _{3} x_{1}x_{2} + is a first order model.

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True False

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False

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2^{k} different models.

True False

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If each pair of independent variables is weakly correlated, there is no problem of multicollinearity.

True False

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If two or more independent variables are highly correlated, the regression analysis is unlikely to suffer from the problem of multicollinearity.

True False

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Regression models in which the highest power of any predictor variable is 1 and in which there are no cross product terms are referred to as first-order models.

True False

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If the effect of an independent variable (e.g., square footage)on a dependent variable (e.g., price)is affected by different ranges of values for a second independent variable (e.g., age ), the two independent variables are said to interact.

True False

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A linear regression model can be used to explore the possibility that a quadratic relationship may exist between two variables by suitably transforming the independent variable.

True False

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A qualitative variable which represents categories such as geographical territories or job classifications may be included in a regression model by using indicator or dummy variables.

True False

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A logarithmic transformation may be applied to both positive and negative numbers.

True False

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If a qualitative variable has c categories, then only (c - 1)dummy variables must be included in the regression model.

True False

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If a square-transformation is applied to a series of positive numbers, all greater than 1, the numerical values of the numbers in the transformed series will be smaller than the corresponding numbers in the original series.

True False

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The regression model y = _{0} + _{1} x_{1} + _{2} x^{2}_{1} + is called a quadratic model.

True False

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Qualitative data can be incorporated into linear regression models using indicator variables.

True False

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If a data set contains k independent variables, the "all possible regression" search procedure will determine 2^{k} - 1 different models.

True False

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If a qualitative variable has c categories, then c dummy variables must be included in the regression model, one for each category.

True False

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The interaction between two independent variables can be examined by including a new variable, which is the sum of the two independent variables, in the regression model.

True False

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The regression model y = _{0} + _{1} x_{1} + _{2} x_{2} + _{3} x_{3} + is a third order model.

True False

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