Final answer:
To estimate the relationship between productivity and commitment in job survey data, use the Pearson correlation coefficient and conduct a hypothesis test and a significance test to evaluate the strength and significance of the relationship.
Step-by-step explanation:
To estimate the strength of the relationship between productivity (prody) and commitment (commit) in job survey data, a statistician would likely recommend using the Pearson correlation coefficient. This coefficient measures the linear correlation between two variables, giving a value between -1 and 1. A value close to 1 indicates a strong positive relationship, a value close to -1 indicates a strong negative relationship, and a value around 0 indicates no linear relationship.
To assess the significance of the Pearson correlation coefficient, a hypothesis test is often performed. If you want to be 95 percent confident in estimating the population correlation coefficient based on sample data, you could use a confidence interval around the sample correlation. Finally, to determine whether a linear relationship exists at all, you would conduct a significance test, such as the t-test for correlation, at a significance level of 0.05 as described in the provided information.