# WEEK 4

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1. Index indicating the proportion of the variance in the dependent variable that can be explained by the independent variables.
Coefficient of determination
2. Technique used to analyze relationships between variables and make predictions about the value of variables.
Linear regression
3. Equation for the best-fitting straight line to characterize the relationship between independent and dependent variables.
Regression equation
4. Point at which the line passes through the Y axis and the value of X is zero.
Intercept constant
5. Rate at which a line rises across a horizontal distance; the steepness of a regression line.
Slope
6. Error term or unexplained variance.
Residuals
7. Method of estimating parameters in a model such that the squared error term is minimized.
Least squares
8. Standard deviation of the errors from the regression line; used to indicate the accuracy of the predictions.
Standard error of the estimates
9. Procedure for understanding the effects of two or more independent variables on dependent variable using least squares estimation.
Multiple regression
10. Index that summarizes the magnitude of the relationship between two or more independent variables and a dependent variable.
Multiple correlation coefficient
11. Squared multiple correlation coefficient adjusted for sample size and number of predictors to give a more accurate estimate of the relationships in the population.
12. Multiple regression analysis in which all predictor variables are entered into the equation simultaneously.
Simultaneous regression model
13. Multiple regression analysis in which the predictor variables are entered into the model in steps prespecified by the analyst.
Hierarchical regression model
14. Multiple regression analysis in which predictor variables are entered into the model in steps, in the order in which the increment to R is greatest.
Step-wise regression model
15. A method of coding categorical variables into dichotomous variables using codes such as 1 and 0 to represent the presence and absence of an attribute (e.g., 1=male, 0=female).
Dummy coding
16. A way of coding categorical variables in multiple variate analysis that uses 1, 0, and -1 to designate categories.
Effect coding
17. A method of coding categorical variables in a regression analysis to make specific planned comparisons.
Orthogonal coding
18. When two or more independent variables in a matrix are highly correlated with each other.
Multicollinearity
19. A statistical method of used to test mean group differences on a dependent variable, while controlling for one or more extraneous variables (covariates).
Analysis of covariance (ANCOVA)
20. A variable that is statistically controlled (held constant) in ANCOVA; typically an extraneous, confounding influence.
Covariate
21. Statistical procedure used to test the significance of differences between the means of two or more groups on two or more dependent variables, after controlling for one or more covariates.
Multivariate ANCOVA (MANCOVA)
22. Multivariate statistical procedure for examining the relationship between two or more independent variables and two or more dependent variables.
Canonical analysis
 Author: FlawlessEra ID: 24403 Card Set: WEEK 4 Updated: 2010-06-21 18:08:04 Tags: Week vocabulary Folders: Description: Week 4 Vocabulary Show Answers: