STAT 1100 Chapter Notes - Chapter 14: Test Statistic, Dependent And Independent Variables, Simple Linear Regression
Document Summary
Chapter 14 introduction to linear regression and correlation. The test of significance of the correlation coefficient. The correlation coefficient is a measure of association that allows studying the intensity of the link existing between two variables. The correlation coefficient is given by the following formula: The correlation coefficient varies between -1 and 1. A correlation coefficient closer to 1 or -1 means that the two variables are highly linked. f r is closer to 0, there is a low correlation between the two variables. When r is positive, it means that the two variables vary in the same sense. If r is negative, it means that they vary in the inverse sense. The significance test of the correlation coefficient aims to check whether the correlation in the sample also exists in the population. More the absolute value of t is greater more it"s believed that the two variables are associated (positively or negatively) in the population.
