Ch 6 Vocab

Magnitude variables

an indication of the strength of the relationship between two

scatterplot variables

A figure that graphically represents the relationship between two

Causality The false assumption that a correlation indicates a causal relationship between the two variables. Directionality The mistaken inference made with respect to the direction of a causal relationship between two variables third variable problem the problem of a correlation between two variables being dependent on another (third) variable partial correlation A correlational technique that involves measuring three variables and then statistically removing the effect of the third variable from the correlation of the remaining two variables restrictive range

A variable that is truncated and has limited variability

person-who argument Arguing that a well-established statistical tren is invalid because we know "a person who" went against the trend Pearson product-moment correlation coefficient (Pearson's r) The most commonly used correlation coefficient when both variables are measured on an interval or ratio scale. As a general rule of thumb when calculating a correlation coefficient, we should have at least 10 particicpants per variable. Forumula: r = (Σ Zx*Zy) ÷ N Coefficient of Determination (r2) A measure of the proportion of the variance in one variale that is accounted by another variable; calculated by squaring the correlation coefficient. Spearman's Rank-order correlation coefficient The correlation coefficient used when one (or more) of the variables is measured on an ordinal (ranking) scale Point-biserial correlation coefficient The correlation coefficent used when on of the variables is measured on a dischotomous nominal scale, and hte other is measured on an interval or ratio scale. Phi coefficient The correlation coefficient used when both measured variables are dichotomous and nominal.

Regression analysis A procedure that allows us to predict an individual's score on one variable based on knowing one or more other varaibles. Regression line The best-fitting straight line drawn through the center of a scatterplot that indicates the relationship between varaibles. Formule = Y' = bX + a where Y' = predicted value on the y variable, b = slope of the line, X = individual score on x variable, a = y intercept. To get b; b = r * (σy ÷ σx) where σ is standard deviation. To get a; a = Avg of Y - b *(avg of x) multiple regression analysis Multiple regression anaysis involves combining several predictor variables in a single regression analysis. Helps to assess the effects of multiple predictor varaibles on the dependent measure.