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1. 9 - Hypothesis Test for the Population Correlation Coefficient As always, we want to draw conclusions about populations, not just samples To do so, we either have to conduct a hypothesis test or calculate a confidence interval In this section, we learn how to conduct a hypothesis test for the population correlation coefficient ρ (the greek letter "rho")
Testing the Statistical Significance of Pearsons Correlation . . . Significance testing of Pearson’s r is done through a hypothesis test The goal is to determine whether the correlation coefficient in your sample is significantly different from zero (no correlation) in the population
T Test Overview: How to Use Examples - Statistics by Jim Use a paired t-test when you measure each subject twice, such as before and after test scores This procedure determines if the mean difference between paired scores differs from zero, where zero represents no effect
Pearson Correlation Coefficient (r) | Guide Examples - Scribbr The Pearson correlation coefficient (r) is the most common way of measuring a linear correlation It is a number between –1 and 1 that measures the strength and direction of the relationship between two variables
Testing the Significance of the Correlation Coefficient We perform a hypothesis test of the “ significance of the correlation coefficient ” to decide whether the linear relationship in the sample data is strong enough to use to model the relationship in the population
11. 2: Correlation Hypothesis Test - Statistics LibreTexts We perform a hypothesis test of the "significance of the correlation coefficient" to decide whether the linear relationship in the sample data is strong enough to use to model the relationship in the population