Linear Regression

Simple linear regression (SLR) is a __________ type of statistical analysis.

• Univariate

• Bivariate

• Multivariate

The following types of data can be used in MLR (choose all that apply)

• Interval or ratio dependent variable (DV)

• Interval or ratio independent variables (IVs)

• Dichotomous IVs

A linear regression (LR) analysis produces the equation Y = 3 + 0.4X. This indicates that:

• When Y = 0.4, X = 3

• When Y = 0, X = 3

• When X = 3, Y = 0.4

• When X = 0, Y = 3

Linear regression analysis produces an equation of Y = 7 - 3.2X. This indicates that:

• An X value of 0 would would increase Y by 7.

• A 1 unit decrease in X results in a 3.2 unit decrease in Y.

• A 1 unit increase in X results in a 3.2 unit increase in Y.

• A 1 unit increase in X results in a 3.2 unit decrease in Y.

The main purpose(s) of (LR) is/are (choose all that apply):

• Exploring the relationship between one variable and another

• Describing the relationship between one variable and another

• Predicting one variable on the basis of another

• Explaining one variable in terms of another

When writing regression formulae, which of the following refers to the predicted value on the dependent variable (DV)?

• Y

• Y (hat)

• X

• X (hat)

• a

The major conceptual limitation of all regression techniques is that one can only ascertain prediction, but never be sure about underlying causal mechanism.

• True

• False

In MLR, the square of the multiple correlation coefficient or R² is called the __________.

• Variance

• Covariance

• Coefficient of determination

• Big R

In linear regression, the residual refers to the difference between the predicted Y and actual Y values.

• True

• False

A regression model in which more than one independent variable is used to predict the dependent variable is called as _________.

• a simple linear regression model

• a multiple regression model

• an independent model