1) In regression analysis, the model in the form y = 0 + 1x + is called the

a) regression model. b) correlation model.c) regression equation. d) estimated regression equation.

2)Regression analysis is a statistical procedure for developing a mathematical equation that describes how

a) one dependent and one or more independent variables are related.one dependent,

b) one independent, and several error variables are related.

c) one independent and one or more dependent variables are related.

d) several independent and several dependent variables are related.

3)In regression analysis, the variable that is being predicted is the

a) intercept variable. b) error variable.c) dependent variable. d) independent variable.

10 Which of the following is true of the fundamentals of regression analysis? Multiple Choice The regression coefficient is calculated by squaring errors of each dependent variable. O A fundamental basis of regression analysis is the assumption of a circular relationship between the independent and dependent variables. O Regression uses an estimation procedure called ordinary least squares that guarantees the line it estimates will be the best fitting line. O Any point that falls on the line of a regression analysis is the result of unexplained variance. O The differences between actual and predicted values of the dependent variable are known as regression coefficients and are represented by b.9 Which of the following statements is true of model F statistics? Multiple Choice Skipped O Analysis of linear relationships between a dependent variable and multiple independent variables requires that F statistics be smaller than beta coefficients. O An F statistic shows the change in the dependent variable for each unit change in the independent variable. O A larger F statistic indicates that the regression model has more explained variance than error variance. O Standardization using beta coefficient augments the effects of using different scales of measurement. O Bivariate regression becomes multiple regression analysis when F statistics are used.2 0 A fundamental basis of regression analysis is the assumption of: Multiple Choice Skipped O the existence of two independent variables for every dependent variable. the lack of a relationship between independent variables. a straight line relation ship between the in dependent and dependent variables. a uniform normal distribution between dependent variables. a curvilinear relationship between two weakly associated dependent variables. OOOO