CHAPTER 5 Flashcards
What are the 2 categories of non- experimental research method?
Correlational Designs
Quasi- Experimental Designs
What is Correlation Design?
It shows relationships between sets of antecedent condition and behavioural effects .
Antecedents are preexisting (manipulated or controlled by the researcher)
What is Quasi-Experimental Design?
Real Experiments
To compare behavioural differences associated with different types of subjects.
Lack of manipulation of antecedents
Quasi comes from the latin word_____
Seeming like
Designed to determine the correlation
Correlational Study
Positive Correlation or ______
Negative Correlation or _____
Direct
Inverse
_____ is the most commonly used procedure for calculating simple correlation.
The Pearson Product Moment Correlation Coefficient
Pearson r is used when the data collected is _____ or ____
Ratio or interval scale
This is the visual presentation of scores belonging to each subject in the study
Scatterplots
The lines drawn on the scatterplots are called____
Regression lines or Lines of Best Fit
When the r is near zero there is_____
No relationship between 2 variables
Assumes the direction of the X and Y is the same
General Linear Model
Assumes the relationship changes directions
Curvilinear
It affects the correlation coefficients.An artificial restriction of the ranges values of X or Y
Range Truncation
The behaviours could affect each other
Bidirectional Causation
The cause and effect
Causal Direction
There is a third variable
Third variable problem
It estimates the amount of variability in scores on one variable that can be explained by the other variable
Coefficient of determination
Formula for the coefficient of determination
r²
Used to estimate predict the score on one of the measured behaviours from the score on the other
Linear Regression Analysis
Used to test the relationship of several variable predictor variables with a criterion variable
Multiple Correlation
One variable to be held constant and computing the relationship between the two
Partial Correlation
Prediction and measures 2 or more Independent Variable to predict the Dependent Variable
Multiple Regression Analysis
What are the tools for causal modeling
Path analysis
Cross-lagged design