Question

Assume a researcher found that the correlation between a test he or she developed and job performance was 0.55 in a study of 28 employees. If correlations under .35 are considered unacceptable, would you have any reservations about using this test to screen job applicants?

Short answer

No reservations; the correlation is acceptable at 0.55 (>0.35).

Step-by-step solution

Understanding Correlation

Correlation is a statistic that measures the degree to which two variables move in relation to each other. The correlation coefficient ranges from -1 to 1. A positive correlation means that as one variable increases, the other also increases. A correlation of 0 means there is no linear relationship between the variables.

Identifying Acceptable Correlation

In this exercise, correlations under 0.35 are deemed unacceptable. Therefore, any correlation equal to or above 0.35 is considered acceptable for the purpose of predicting job performance based on the test.

Analyzing the Given Correlation

The given correlation between the test and job performance is 0.55. Since 0.55 is greater than 0.35, the correlation is considered acceptable based on the criteria set out in the exercise.

Conclusion on Using the Test

Since the correlation of 0.55 is above the threshold of 0.35, there should be no reservations about using this test to screen job applicants. This indicates a moderately strong positive relationship, suggesting the test is a reliable predictor for job performance.

Key concepts

Correlation Coefficient

The correlation coefficient is a numerical measure that describes the strength and direction of a relationship between two variables. It ranges from -1 to 1. A value closer to 1 indicates a strong positive relationship, meaning that as one variable increases, so does the other. Conversely, a value closer to -1 indicates a strong negative relationship, where one variable increases as the other decreases. If the coefficient is 0, it signifies no linear relationship.
In our context of job performance and testing, a correlation of 0.55 suggests a moderate positive relationship. This implies that the test scores moderately relate to how employees perform in their jobs. This statistical measure provides an insight into whether the test can be considered a reliable predictive tool.

• Values close to 1: strong positive relationship.
• Values close to -1: strong negative relationship.
• Value of 0: no relationship.

This numerical representation helps to decide the suitability of the test in screening applicants.

Predictive Validity

Predictive validity refers to the extent to which a score on a test forecasts or predicts outcomes in a particular setting. In employment settings, predictive validity is crucial to determine how well a test can foresee job performance.
When assessing a test's predictive validity, researchers aim to establish if high scores correlate with successful job performance. Generally, a higher correlation coefficient increases the test's predictive validity, suggesting that the tool is effective in identifying potential high performers.
In this exercise, the test's predictive validity is depicted through the correlation coefficient of 0.55. Since this exceeds the unacceptable threshold of 0.35, it indicates that the test is a reasonably good predictor of job performance, hence it can be considered for candidate selection.

• Predictive Validity is measured through correlation.
• Higher correlation enhances the test's predictive strength.
• Utilizes statistical analysis to guide decision-making in hiring.

Statistical Thresholds

Statistical thresholds are pre-determined criteria used to evaluate the significance and acceptability of statistical results. Setting these thresholds helps to determine what is considered acceptable while interpreting correlations or other statistical measures.
In our scenario, a correlation value below 0.35 is deemed unacceptable to judge the effectiveness of the test in predicting job performance. The threshold acts as a benchmark to ensure that the predictive tool possesses a minimum level of reliability.

• Thresholds simplify decision-making by setting clear criteria.
• They ensure consistency in assessing test effectiveness.
• Provide a standard to measure against and help confirm reliability.

Since the test's correlation of 0.55 comfortably surpasses this threshold, it indicates the usefulness of the test in practical applications such as screening job candidates.