Education: Published Examples of Correlation, Hypothesis Testing (t-test), Multinomial Experiments & Contingency Tables (Chi-square), and Variance (ANOVA)
Correlations determine the degree that two variables vary together, such as with the study of individual differences and job performance. The Pearson product-moment correlation coefficient or "r" is the most commonly used to measure the association of two quantitative variables characterized by a linear relationship (positive or negative). It determines how well bivariate data points stay within the assumed straight line of best fit. The correlation coefficient is a statistic or parameter which measures the strength and direction of a relationship between the two variables (Minium, King, & Bear, 1993).
Trost, Klieme, and Nauels (1998) used correlations to show the relationship between quantitative criteria for admission and performance on the First Medical Examination, thus showing the relationship between criteria for admission to medical school and student success. For their longitudinal study, data on the total population of several student cohorts admitted to medical schools (n = 28,000), was analyzed. The correlations utilized the First Medical Examination, which took place after 2-3 years of study. Criteria for admission included: 45% were admitted due to a score combining the average mark of the secondary school leaving certificate and results of a specific scholastic aptitude test (the Test for Medical Studies); 10% were admitted based on test results regardless of school marks; 20% were admitted based on length of time applicants had to wait for admission; 15% were admitted due to results of an interview conducted by members of the faculty; and 10% were admitted due to special circumstances such as foreigners or hardship cases.
Pearson coefficients for the correlation between the quantitative admission criteria and the total score on the First Medical Exami...