A concept used when interpreting partial correlation coefficients to indicate that a control variable appears to explain the relationship between two other variables completely      A concept used in multiple regression and partial correlation to indicate that the effect of one independent variable on the dependent variable is different depending on the value of another independent variable      A value that is computed for each independent variable in a multiple regression equation and is used in the equation as a multiplier to the value of the corresponding independent variable      A statistical method that uses the least-squares method to produce an equation to predict the Z score of one variable using the Z scores of two or more other variables      A value that describes the percentage of variability in the dependent variable that is explained by two or more independent variables      A measure of the relationship between two variables without consideration of any other variables      A statistical method that measures the relationship between two variables while controlling for a third      A variable whose value is held constant so that the researcher can explore the relationship between two other variables      A concept used when interpreting partial correlation coefficients to indicate that a control variable does not appear to affect the relationship between two other variables      A statistical method that uses the least-squares method to produce an equation to predict the value of one variable using the values of two or more other variables      The Y variable in a multiple regression whose value is being predicted by two or more independent X variables      One of the X variables in a multiple regression equation used to predict the dependent Y variable      Partial slopes computed in a standardized multiple regression; these slopes can be compared to make statements about which dependent variables are more influential on the independent variable      A value that describes the correlation between the dependent variable and two or more independent variables

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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A concept used when interpreting partial correlation coefficients to indicate that a control variable appears to explain the relationship between two other variables completely     
A concept used in multiple regression and partial correlation to indicate that the effect of one independent variable on the dependent variable is different depending on the value of another independent variable     
A value that is computed for each independent variable in a multiple regression equation and is used in the equation as a multiplier to the value of the corresponding independent variable     
A statistical method that uses the least-squares method to produce an equation to predict the Z score of one variable using the Z scores of two or more other variables     
A value that describes the percentage of variability in the dependent variable that is explained by two or more independent variables     
A measure of the relationship between two variables without consideration of any other variables     
A statistical method that measures the relationship between two variables while controlling for a third     
A variable whose value is held constant so that the researcher can explore the relationship between two other variables     
A concept used when interpreting partial correlation coefficients to indicate that a control variable does not appear to affect the relationship between two other variables     
A statistical method that uses the least-squares method to produce an equation to predict the value of one variable using the values of two or more other variables     
The Y variable in a multiple regression whose value is being predicted by two or more independent X variables     
One of the X variables in a multiple regression equation used to predict the dependent Y variable     
Partial slopes computed in a standardized multiple regression; these slopes can be compared to make statements about which dependent variables are more influential on the independent variable     
A value that describes the correlation between the dependent variable and two or more independent variables     
 
 
 
Answer key:
 
Beta-weights
Coefficient of multiple determination
Control variable
Dependent variable
Direct relationship
Independent variable
Interaction
Multiple correlation coefficient
Multiple regression
Partial correlation
Partial slope
Spurious or intervening relationship
Standardized multiple regression
Zero-order correlation
Transcribed Image Text:Beta-weights Coefficient of multiple determination Control variable Dependent variable Direct relationship Independent variable Interaction Multiple correlation coefficient Multiple regression Partial correlation Partial slope Spurious or intervening relationship Standardized multiple regression Zero-order correlation
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