What is adjusted R-square? a conservative version of R-square that is always less than regular R-square What is control by adjustment? a form of statistical control in which a mathematical adjustment is made to assess the impact of a third variable What is control by grouping? a form of statistical control in which observations identical or similar to the control variable are grouped together What is correlation analysis? produces a measure of association, known as Pearson's correlation coefficient or Pearson's , that measures the direction and magnitude of a relationship between two INTERVAL-LEVEL variables

 What is a dummy variable? a hypothetical index that has just two values: 0 for the presence (or absence) of a factor and 1 for its absence (or presence) What is an efficient estimator? An estimator having standard error smaller than those of other estimators is said to be efficient. An efficient estimator falls closer, on average, than other estimators to the parameter. What is the error sum of squares? the prediction error, the part of the total sum of squares that is not accounted for by the regression equation What is an estimator? the particular type of statistic for estimating a parameter

 What is experimental control? manipulation of the exposure of experimental groups to experimental stimuli to assess the impact of a third variable What is explication? the specification of the conditions under which X and Y are and are not related What is an interaction effect? An interaction effect occurs when the effect of an independent variable cannot be fairly summarized by a single partial effect. Instead, the effect varies, depending on the value of another independent variable in the model. What is an interaction variable? The multiplicative product of two (or more) independent variables.

 What is an interval estimate? An interval of numbers around a point estimate, within which the parameter is believed to fall What is a linear probability model? regression model in which a dichotomous variable is treated as the dependent variable What is multicollinearity? Multicollinearity occurs when the independent variables are related to each other so strongly that it becomes difficult to estimate the partial effect of each independent variable on the dependent variable. What is a multiple correlation coefficient? a statistic varying between 0 and 1 that indicates the proportion of the total variation in Y, a dependent variable, that is statistically explained by the independent variables

 What is multiple regression? In multiple regression, we are able to isolate the effect of one independent variable on the dependent variable, while controlling for the effects of the other independent variable(s). What is multiple regression analysis? a technique for measuring the mathematical relationships between more than one independent variable and a dependent variable while controlling for all other independent variables in the equation What is a multiple regression coefficient? a number that tells how much Y will change for a one-unit change in a particular independent variable, if all the other variables in the model have been held constant What is multivariate analysis? data analysis techniques designed to test hypotheses involving more than two variables

 What is multivariate cross-tabulation? a procedure by which cross-tabulation is used to control for a third variable What is a partial regression coefficient? a number that indicates how much a dependent variable would change if an independent variable changed one unit and all other variables in the equation or model were held constant What is a partly spurious relationship? a relationship between two variables caused partially by a third What is Pearson's correlation coefficient? a measure of association which always has a value between -1 and 1; -1 showing perfectly negative association between variables and 1 showing perfectly positive association between variables

 What is a point estimate? A single number that is the best guess for a parameter What is prediction error? The difference between the value of the dependent variable estimated from a regression equation and its actual value. What is regression analysis? a technique for measuring the relationship between two interval- or ratio-level variables What is a regression coefficient? a statistic that indicates the strength and direction of the relationship between two quantitative variables

 What is a regression constant? value of the dependent variable when all the values of the independent variables in the equation equal zero What is a regression line? An algebra-type equation that specifies the relationship among variables on interest. What is the regression sum of squares? the component of the total sum of squares that we pick up by knowing the independent variable What is R-square? a statistic, sometimes called the coefficient of determination, defined as the explained sum of squares divided by the total sum of squares. It purportedly measures the strength of the relationship between a dependent variable and one or more independent variables

 What is a scatterplot? a plot of Y-X values on a graph consisting of an x-axis drawn perpendicular to a y-axis. The axes represent the values of the variables. Usually the x-axis represents the independent variable if there is one and is drawn horizontally; the y-axis is vertical. Observed pairs of Y-X values are plotted on this coordinate system What is a specified relationship? a relationship between two variables that varies with the values of a third What is statistical control? assessing the impact of a third variable by comparing observations across the values of a control variable What is the total sum of squares? an overall summary of the variation in the dependent variable

 What is an unbiased estimator? An estimator is unbiased if its sampling distribution centers around the parameter; the parameter is the mean of the sampling distribution. By contrast, a biased estimator tends to underestimate or overestimate the parameter. What are the assumptions about residuals? Assumptions about “random noise” in regression analysis, qualities that “random noise” must have in order to truly be noise. What is listwise deletion? In multiple regression analysis, if an observation is missing values on any variable, that observation is omitted and the regression only proceeds with complete observations. What is ordinary least squares? The criteria used to estimate regression coefficients; regression coefficients are found to minimize the sum of the squared differences between the observed values of y and estimated values of y.

 Define parsimony. Concept that should guide the inclusion of more independent variables in multiple regression analysis – one should consider being stingy with including more variables.