Consider a study investigating the correlation between people's calorie estimates and their weight. Since there is no expectation about the direction of the relationship, a two-tailed test is conducted. For a sample of $22$ students, Pearson's $r$ is computed to be $-.21$. Using statistical software, the $p$-value is found to be $.348$. Because the $p$-value is greater than $.05$, the null hypothesis is retained, concluding that there is no statistically significant relationship between the variables. Alternatively, computing the test by hand involves finding the critical value. For $22 - 2 = 20$ degrees of freedom, the critical value is $.444$. Since the absolute value of the sample correlation coefficient ($.21$) is less extreme than the critical value ($.444$), this confirms that the $p$-value is greater than $.05$, leading to the same conclusion to retain the null hypothesis.