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## Statistics in HRM

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Applied Research in HRM

- Statistics are used to answer applied research questions in HRM, such as:
- Does this selection test have adverse impact?
- Is this selection test valid?
- Is this selection test reliable?
- What is the reliability of this selection test?
- How much should this job be paid?

Determining whether a selection test has adverse impact

- Civil Rights Act of 1964, SEC. 2000e-2. [Section 703
- It shall be an unlawful employment practice for an employer –
- to fail or refuse to hire or to discharge any individual, or otherwise to discriminate against any individual with respect to his compensation, terms, conditions, or privileges of employment, because of such individual's race, color, religion, sex, or national origin;

Determining whether a selection test has adverse impact

- The Uniform Guidelines on Employee Selection , Section 41CFR60-3.4(d), Adverse impact and the “four-fifths rule.''
- A selection rate for any race, sex, or ethnic group which is less than four-fifths (4/5) (or eighty percent) of the rate for the group with the highest rate will generally be regarded by the Federal enforcement agencies as evidence of adverse impact, while a greater than four-fifths rate will generally not be regarded by Federal enforcement agencies as evidence of adverse impact.

Determining whether a selection test has adverse impact

- Calculating Adverse Impact by the 4/5ths Rule
- Selection Ratio Minority = # minority hired / # minority applicants
- Selection Ratio Majority = # majority hired / # majority applicants
- Adverse Impact Ratio = SRminority / SRmajority

Determining whether a selection test has adverse impact

- The Chi Square is the appropriate statistical test, when the sample size is large enough:

Determining whether a selection test is valid

- Uniform Guidelines on Employee Selection Proceedures, Section 41CFR60-3.3(a), Discrimination defined: Relationship between use of selection procedures and discrimination
- Procedure having adverse impact constitutes discrimination unless justified. The use of any selection procedure which has an adverse impact on the hiring, promotion, or other employment or membership opportunities of members of any race, sex, or ethnic group will be considered to be discriminatory and inconsistent with these guidelines, unless the procedure has been validated in accordance with these guidelines, or the provisions of section 6 of this part are satisfied.

Determining whether a selection test is valid

- Must show a statistically significant correlation between test scores and job performance
- Pearson Correlation Coefficient:

Determining whether a selection test is valid

- Checking the correlation coefficient for statistical significance:
- df = (# pairs –2); Alpha = .05
- If the correlation is equal to or greater than the tabled value, the correlation is statistically significant

Determining whether a selection test is valid

- Calculate the multiple correlation between test scores and job performance:

Determining the reliability of a selection test

- Reliability is the upper limit of validity
- For a test to be valid, it must be reliable
- To measure the reliability of a test over time (stability), calculate Test-Retest Reliability Coefficient
- Correlate a set of test scores at Time1 and Time2

Determining the reliability of a selection test

- To measure the reliability of a test with only one test administration, calculate the Internal Consistency using the Spearman-Brown prophecy formula:

Determining the reliability of a selection test

- Step1: Divide whatever test into two halves and score them separately (usually the odd numbered items are scored separately from the even-numbered items)
- Step2: Calculate a Pearson correlation coefficient between the scores on the even-numbered items and the scores on the odd-numbered items.
- Step3: Apply the Spearman-Brown prophecy formula to adjust the half-test reliability to full-test reliability. A longer test will generally be more reliable than a shorter test. The Spearman-Brown prophecy formula was developed to estimate the change in reliability for different numbers of items.

Determining the reliability of a selection test

- To determine the reliability of a panel of interviewers, use the Intraclass Correlation Coefficient

Determining the reliability of a selection test

- Agreement between each pair of interviewers an be calculated, and the ICC gives the level of agreement among all the interviewers

Determining how much a job should be paid

- People should be paid fairly based on two factors:
- The work that they do (difficulty, hazard, responsibility, education, etc.)
- Internal Equity
- What the market is paying
- External Competitiveness

Determining how much a job should be paid

- Job Evaluation
- Evaluate the job, how much of each of the compensable factors does the job require?
- Hazards: Occasional, intermittent or constant exposure to mechanical, electrical, chemical, biological, or physical factors which involve risks of accident, personal injury, health impairment or death
- 1. Safe/minimal: General office or equivalent conditions result in little or no exposure to injury or accident
- 2. Marginal/moderate: Occasional exposure to hazards or risk of injury which are generally protected against or predictable
- 3. Dangerous/considerable:Regular exposure to conditions which are unpredictable/uncertain and which result in risk of personal injury
- 4. Hazardous/Extreme:Continuous exposure to life threatening conditions or accidents which are difficult to identify or protect against

Determining how much a job should be paid

- Job Evaluation
- Collect salary survey data on benchmark jobs, how much do other organizations pay?

Determining how much a job should be paid

- Job Evaluation
- Do a regression analysis, to determine the midpoint salary for the benchmark jobs
- Interpolate/Extrapolate to determine the salary for non-benchmark jobs, using the equation: Salary = JETotal*Coeff+Intercept

Statistics Pretest

- What statistic do you use?
- To determine the validity of a selection test
- To determine the adverse impact of a selection test
- To determine whether women get significantly lower scores on a test than men
- To determine whether alternate (parallel) forms of a test are statistically equivalent
- To determine how well a panel of interviewers agrees with each other about candidates they’ve interviewed

Statistics Pretest

- Are the people who went through the training sessions (variable 1) more productive than the other employees?

Statistics Pretest

- Applicants completed a set of three selection tests…interpret the results:

Statistics Pretest

- Does this selection test have adverse impact?

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