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Pearson R Critical Value:
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The Pearson R critical value is the minimum correlation coefficient value needed to reject the null hypothesis in a correlation test. It depends on the sample size and significance level, and is used to determine if a correlation is statistically significant.
The calculator determines the critical value using statistical tables:
Where:
Explanation: The critical value is looked up in Pearson correlation coefficient tables based on degrees of freedom and chosen significance level.
Details: Calculating the critical r value is essential for hypothesis testing in correlation analysis. It helps determine whether an observed correlation is statistically significant or could have occurred by chance.
Tips: Enter the sample size (must be ≥3) and select the desired significance level (α). The calculator will provide the critical r value from statistical tables.
Q1: What does the critical r value represent?
A: It represents the minimum correlation coefficient value needed to reject the null hypothesis that there is no correlation between variables.
Q2: How does sample size affect the critical value?
A: Larger sample sizes generally result in smaller critical values, making it easier to detect significant correlations.
Q3: What are common significance levels used?
A: The most common significance levels are 0.01, 0.05, and 0.10, representing 1%, 5%, and 10% probability of Type I error respectively.
Q4: When should I use a one-tailed vs two-tailed test?
A: Use one-tailed when you have a specific direction hypothesis, two-tailed when testing for any correlation regardless of direction. Critical values differ between them.
Q5: Can I use this for non-parametric correlations?
A: No, this calculator is specifically for Pearson's correlation coefficient. Spearman's or Kendall's correlations have different critical values.