Try out our new practice tests completely free!

Statistics

Bookmark

## Quiz 14 : Building Multiple Regression Models

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

True

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

False

The regression model y = 0 + 1 x1 + 2 x2 + 3 x1x2 + is a first order model.
Free
True False

False

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2k different models.
True False
Recoding data cannot improve the fit of a regression model.
True False
If each pair of independent variables is weakly correlated, there is no problem of multicollinearity.
True False
If two or more independent variables are highly correlated, the regression analysis is unlikely to suffer from the problem of multicollinearity.
True False
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
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
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
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
A logarithmic transformation may be applied to both positive and negative numbers.
True False
If a qualitative variable has c categories, then only (c - 1)dummy variables must be included in the regression model.
True False
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
The regression model y = 0 + 1 x1 + 2 x21 + is called a quadratic model.
True False
Qualitative data can be incorporated into linear regression models using indicator variables.
True False