Ch12 Key Terms Flashcards
Beta coefficient
A regression coefficient that as been recalculated to have a mean of 0 and standard deviation of 1
Bivariate regression analysis
A stats technique that analyzes linear relationships between 2 or more variables by estimating coefficients for an equation for a straight line
Coefficient of determination
A numbering measuring the proportion of variation in 1 variable accounted for by another
Composite variable
Variable that’s measured with several separate questions
Confirmatory composite analysis (CAA)
Analysis that determines whether the variables are accurately measures
Covariation
The amount of change in 1 variable that is related to the change of another
Curvilinear relationship
Relationship between 2 variables where the strengths / direction of their relationship changes over the range of both
Homoskedasticity
The pattern of covariation is constant around the regression line whether values are small, medium or large
Heteroskedasticity
The pattern around regression line = not constant, values vary from small, medium and large
Inner model
The 5 structural relationships between the 6 constructs in the path model
Least square procedure
Regression approach that determines the best-fitting line by minimizing the vertical distance of all the points from the line
Linear relationship
An association between 2 variables where the strength remains the same over the range of both variables
Model F-statistic
Stats that compares the amount of variation in the dependent measure (explained) associated with the independent variable (unexplained)
Multicollinearity
A situation in which several indépendant variables are highly correlated with each other
Multiple regression analysis s
Stats technique that analyzes the linear relationship between a dependent variable and multiple independant ones
Normal curve
A curve that indicates the shape of the distribution of a variable is equal both above and below the mean
Ordinary least squares
Stats procedure that stigmates regression equation coefficients that product the lowest sum of squared differences between the actual and predicted values of the dependent variable
Outer model
Relationships between sic constructs and multiple variables
Partial least squares (PLS)
A method that is an extension of multiple regression and helps researchers determine whether there are meaningful relationships between the variables
Pearson correlation coefficient
A measure of strength of a linear relationship between 2 metric variables
Regression coefficient
An indicator of important of an independent variable in predicting a dependent variable
Scatter diagram
A graphic plot of the relative position of 2 variables using horizontal and vertical axis
Spearman rank order correlation coefficient
A measure of the linear association between 2 variables where both have been measured using ordinal scales (ranking)
Structural model
Visual representation of the relationships between the variables
Structural modeling (SM)
The process of identifying the relationships between variables
Unexplained variable
The amount of variation in the dependent variable that can’t e accounted by the combination of independent variables
