Correlation Notes - Analyzing Results of Data If descriptive research(nominal data compare group percentages If experimental or quasi-experimental and

# Correlation Notes - Analyzing Results of Data If...

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Analyzing Results of Data If descriptive research (nominal data) compare group percentages If experimental or quasi-experimental and have interval or ratio data (DVs) com - pare groups means via inferential statistics If continuous predictor variables (non-experiemental) correlation Descriptive Stats Central tendency What is the whole sample like Mean (m), median, mode (e.g., if nominal scale used) Variability What does the distribution look like Range: highest to lowest Variance (s2): measure of dispersion (spread) Standard deviation (SD): average distance from the mean (square root of variance) Goals of Research Description, Prediction , Causation, Explanation, Application Relationship Between Variables For example: Height and winners of presidential elections Hurricane exposure and rate of PTSD Are two variables related AKA, do they vary together? Correlation Change in one indicates change in the other Simple Correlation Degree of relationship based on scores of individuals E.g., SAT scores and college grades Just need a score on the 2 variables for each participant in the sample Correlation coefficient Statistic used to indicate the degree to which 2 variables are related to one another in a linear fashion Pearson's r Sign refers to direction (+ or -) Magnitude refers to strengths (-1.00 to +1.00) Positive correlation As you increase one variable the other variables increases as well The variables go up and down together Ex., time exercising and calories burned Negative correlation Inverse relationship As you increase one, you decrease the other Move in the opposite direction Ex., number of kids and hours of sleep Significance and Strength Statistical significance
Related to the strength of a relationship Significant correlation Sample of 100 participants with a Pierson's r of .4, but does it relate to the population Unlikely that in the parent population that the relationship is zero r is significant when there is a low probability of the relationship being zero in the parent population Bigger r, larger sample, less variance Strength (effect size) < .20 are weak

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• Spring '12
• CarrieWyland
• Correlation, Experimental Psychology, Correlation and dependence, Pearson product-moment correlation coefficient, Covariance and correlation, Spearman's rank correlation coefficient