Adverse Impact Ratio:
Note: Ratio < 0.8 indicates potential bias.
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Adverse Impact Analysis is a statistical method used in human resources to detect potential discrimination in employment practices. It compares selection rates between different demographic groups to identify significant disparities that may indicate bias.
The calculator uses the Four-Fifths Rule (80% Rule):
Where:
Interpretation: A ratio below 0.8 (80%) suggests potential adverse impact and may warrant further investigation into the selection process.
Details: Regular adverse impact analysis helps organizations ensure fair hiring practices, comply with equal employment opportunity laws, and promote diversity and inclusion in the workplace.
Tips: Enter selection rates as percentages (0-100%). The minority selection rate should be the rate for the protected group being analyzed. Both rates must be valid positive numbers.
Q1: What Is The Four-Fifths Rule?
A: The Four-Fifths Rule is a guideline established by the Equal Employment Opportunity Commission (EEOC) that identifies selection rates for any race, sex, or ethnic group that are less than 80% of the rate for the group with the highest rate as potential evidence of adverse impact.
Q2: Does A Ratio Below 0.8 Always Mean Discrimination?
A: No, a ratio below 0.8 indicates potential adverse impact that warrants further investigation. It does not automatically prove discrimination but serves as a statistical trigger for deeper analysis.
Q3: What Selection Processes Can Be Analyzed?
A: Adverse impact analysis can be applied to hiring, promotions, training opportunities, performance evaluations, and any other employment decisions where selection rates can be calculated.
Q4: What Should I Do If Adverse Impact Is Detected?
A: Conduct a thorough review of the selection process, examine job-relatedness of criteria, consider alternative selection methods, and document the business necessity of any practices causing the disparity.
Q5: Are There Statistical Tests Beyond The Four-Fifths Rule?
A: Yes, for more rigorous analysis, organizations may use statistical significance tests like chi-square tests or Fisher's exact test, especially when dealing with small sample sizes.