EXPE Chapter 5: Alternatives to Experimentation Correlational and Quasi-Experimental Designs Flashcards
“seeming like”
Quasi
superficially resemble experiments, but lack their required manipulation of antecedent conditions and/or random assignment to conditions.
Quasi-experiments
is used to calculate simple correlations (between two variables)
Pearson correlation coefficient
how the relationship between x and y can be plotted as a line (linear relationship) or a curve (curvilinear relationship).
Linearity
refers to whether the correlation coefficient is positive or negative.
Sign
the strength of the correlation coefficient, ranging from -1 to +1.
Magnitude
the likelihood of obtaining a correlation coefficient of this magnitude due to chance.
Probability
a graphic display of pairs of data points on the x and y axes
Scatterplots
an artificial restriction of the range of X and Y that can reduce the strength of a correlation coefficient.
Range truncation
are extreme scores. They usually affect correlations by disturbing the trends in the data.
Outliers
estimates the amount of variability that can be explained by a predictor variable.
coefficient of determination (r2)
when we want to hold one variable (age) constant to measure its influence on a correlation between two other variables (television watching and vocabulary).
partial correlation
when they want to know whether there is a relationship among three or more variables
multiple correlation (R)
predict behavior measured by one variable based on scores on two or more other variables.
multiple regression
the creation and testing of models that suggest cause-and-effect relationships between behaviors
Causal modeling
