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The significance of a correlation coefficient is tested to determine whether the observed relationship between two variables is statistically significant or whether it could have occurred merely by chance. In Data Analysis, this test is commonly performed by converting the correlation coefficient into a t-statistic and comparing the calculated value with the critical value obtained from the t-distribution table. The null hypothesis and alternative hypothesis are formulated as follows: H₀: ρ = 0 There is no significant correlation between the two variables in the population. H₁: ρ ≠ 0 There is a significant correlation between the two variables in the population. Here, ρ represents the population correlation coefficient. Since the significance level is given as α = 0.05 and the test is two-tailed, the critical values are ±2.776. The appropriate test statistic for testing the significance of Pearson's correlation coefficient _____ __________ _______ __________ ________ ____.
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