Employee Selection and Staffing

MGRS 467

Dr. Yvonne Stedham

Pre-requisites

MGRS 323 – Organizational Behavior

MGRS 467 – Human Resource Management

Course Materials available on

http://www.scsr.nevada.edu/~ystedham/

Employee SelectionOutline -- Session #1

Personal IntroductionCourse Introduction

Content OverviewFormat Overview (Syllabus)

External EnvironmentThe Labor Market (Demand and Supply)The Legal Environment

IntroductionsInstructorStudents – Table Tents

Name and MajorExpected graduation Work ExperienceInterest in HRAspirations

Relevance of this CourseWhat is HRM? HRM Functions?Why a course in Selection?What is the relationship between HR and organizational performance?

HR and Organizational Performance

What is an organization?What is organizational effectiveness?How does HR contribute?

HR and Org effectivenessIndividual effectiveness is the foundation for organizational effectiveness.Individual effectiveness depends on ….

HR and Org effectivenessIndividual effectiveness =

f(Ability,Motivation)

Performance = Ability * Motivation

HR and Org. EffectivenessMatch

Individuals (Knowledge, Skills, Abilities)

withJobs (Requirements and Rewards)

The HRM FrameworkThe External Environment

EconomySocial

EnvironmentLabor Market

LegalEnvironment

Match

Individual*KSA’s*Needs

HR Activities:Recruitment,Selection,Training,Compensation,Labor relations Job

*KSA Requirements*Rewards

HR Outcomes:Job SatisfactionOrg.commitmentAttractionRetentionAttendancePerformance

Session #2Handouts

Readings Sign-upReadings

WSJ and Fortune Sign-upReview

Introductions – Personal and CourseCourse Content

The HRM FrameworkThe External Environment

EconomySocial

EnvironmentLabor Market

LegalEnvironment

Match

Individual*KSA’s*Needs

HR Activities:Recruitment,Selection,Training,Compensation,Labor relations Job

*KSA Requirements*Rewards

HR Outcomes:Job SatisfactionOrg.commitmentAttractionRetentionAttendancePerformance

HR and Org effectivenessIndividual effectiveness =

f(Ability,Motivation)

Performance = Ability * Motivation

Course FormatSyllabus

Session #3Readings Sign-upExtra CreditToday – The HR Department and The External Environment (The LM)Review

The HRM Framework – Four ElementsCourse Format – SyllabusWhat do we know about HR?

What do you know about selection?

Answer the following questions!

Session #4Quiz – Reading #1: The Tie that BindsNNHRA SpeakerReadings Sign-upExtra CreditToday – The HR Department and The External Environment (The LM)Review

What do we know about HR?

Competing in the Third Wave

What is the third wave?Implications for HR?Implications for selection?

Session #5IGT Internship – Compensation – Megan LaKruse 448-0350MHRA – Next Meeting September 25 at 12:15 p.m. in AB 210/ SHRMCurrent Issue – HR represents the focus on equal and fair treatment .. Internationally

President Bush 5:30p.m.What do we know?Results and Impact?Cause .. Reason? Purpose?Reaction? … Purpose?

Session #6Reading #2 todayQuestions for Reading #4Quiz on Reading #3Today –External Environment

The Economic EnvironmentThe Labor Market The Legal Environment

The Staffing FunctionRecruitment and Selection

Recruitment: Generating a pool of qualified applicantsSelection: Assessing/Measuring Applicant KSA’s – Development of KSA Measures

SelectionThe most important HR function

Budget and time spent Definitions

StaffingMutual process by which the individual and the organization become matched to form the employment relationship. Mutual Process: Series of interrelated activities - R, S, DM, job offers, hiring.

SelectionDefinitions (continued)

Selection The process of obtaining and using information about job applicants to determine who should be hired.Focus here is on how to collect relevant info on applicants’ KSA’s.

HR Department and Its Influence

Department vs Functions/Activities (Japan, Europe)

Influence of organizational units on organizational decisions… two viewpoints:

Strategic contingenciesResource dependency

Role of HRThe Human Equation

Putting people firstStrategy implementation

External Environment for HR and Selection

Economic ConditionsFrom land based to capital based to knowledge basedFrom agriculture to factory to computerInformation Age: Implications for demand for labor - Types of jobs and KSA requirementsImplications for selection – KSA AssessmentManagement of Knowledge WorkersEconomic growth – New EconomyInternational competition

Economic ConditionsOld economy: Mass production – high volume and efficiencyNew economy – current … Info age trans

private sector: product - service and quality; variety and choice; customization; convenience; timeliness; public sector: taxpayer demand .. Education, healthcare, welfare, competition KSA requirements

External EnvironmentLabor Market

Demand – Derived Demand Job growth: quantity about 20%, service industryQuality - Types of jobs and KSA’s

Supply – Workforce number and composition

ASAP survey

External EnviroSupply- Workforce characteristics:

Values – Psychological Contract - ReadingGenerations at work

WWII Generation 60+Baby Boom 40-60Generation X 20-40Millennial Generation birth-20 (Gen Y)

GenerationsWWII

Outlook: practicalWork Ethic: dedicatedView of Authority: respectfulLeadership by: hierarchyRelationship: personal sacrificePerspective: Civic

GenerationsBaby Boom

Outlook: optimisticWork Ethic: drivenView of Authority: love/hateLeadership by: consensusRelationship: personal gratificationPerspective: team

GenerationsGeneration X

Outlook: skepticalWork Ethic: balancedView of Authority: unimpressedLeadership by: competenceRelationship: reluctant to commitPerspective: self

GenerationsMillennials

environmentally consciousconnectedmore tolerant of differencesgenerally optimisticachievement oriented team playerssociablewant to fit in not revolutionize

External Enviro – Summary

Economic ConditionsInformation AgeManagement of Knowledge WorkersJob growthThe New EconomyImplications for Selection

Review - External EnviroLabor Market

Demand - QUN and - QUL - Labor Shortage

Supply - QUN and - QUL - Composition and KSA type and level; and, needs and values of employees

ReviewHRM Framework HRM Framework is implemented through an HR departmentThe HR Department and Its Influence

Function/ActivitiesInfluence depends on what

ReviewLabor Market

Supply - WorkforceDiversity of valuesGenerational Differences

WWIIBaby BoomersGeneration XGeneration Y

ReviewPsychological Contract -- TodayLegal Conditions relevant to selection

Employment ContractEmployment-at-will

Assignment backCommon Law: refers to laws applied in the English-speaking world when there were few statutes. Courts wrote opinions explaining the bases for their decisions -- these opinions became precedents for later decisions in similar cases

Session #7Review – External Environment

The Economic EnvironmentThe Labor Market The Legal Environment

Hand back – Readings #1 and #2Quiz on Reading #3 Questions for Reading #4 next timeCase Review next timeToday: Legal Environment

ReviewLabor Market

Supply - WorkforceDiversity of valuesGenerational Differences

WWIIBaby BoomersGeneration XGeneration Y

Legal EnvironmentThe Employment RelationshipPsychological ContractEmployment Contract Formal agreement, voluntary: Defines

and governs the terms and conditions of the employment relationship; promises and expectations … change with time

Written or oral --- both are legally enforceable

Employment at WillReading #2Right of both parties to terminate the employment relationship If “set-term” contract …Termination for

Just cause Failure to perform

If “indeterminate-term” contract --- employment at will (common law); most are “at-will”.

Session #8Quick Decision ReadingHand in Case ReviewHand in Answers to Reading #4SH Exercise for next timeKristin - ArticleReview – External Environment

The Legal Environment

Today: Legal EnvironmentEEO LawsReadings #3 and #4BFOQ Exercise

Workplace TortsBreaches of legal duty by ER when

establishing or modifying the initial relationship (common law)

Tort: civil wrong = violation of a duty by the ER that leads to harm or damages suffered by others

Examples:1. Fraud or misrepresentation: lie/mislead applicant when communicating conditions and terms -> ER violates a duty to be truthful in the presentation of information2. Negligent hiring: ER violates duty to protect Ees and customers against unreasonable and foreseeable risk of harm

Need for Laws and Regulations

Balance of Power Laws limit discretion of ER in establishment of terms and conditionsProtection of EEs

Employment Standards: Minimum acceptable terms and conditions of employment … min. wage, overtime, safety and health (FLSA 1938, OSHA)

Need for lawsIndividual Rights: Labor Relations, Civil Rights Protection, Restrictions on employment-at-will … implied contract

Legal Environment Consistency of Treatment: Procedural

justice Standardized Systems

Protection of ERs Permissble and impermissible

practices: CRA specifies what is OK … e.g., to use ability testsAdministrative predictability and stability

Sources of Laws and Regulations

Common Law: England; Court-made Law; Case-by-case decisions Precedence (Germany and other country code-based law); States – develop and administer own common law.

Constitutional Law: Supersedes; Prohibits deprivation of employment right without due process.

Legal EnvironmentStatutory Law: Derived from written

statutes that are passed by legislative bodies (Federal – Congress; State – Legislature/Assemblies; Local – Municipal/Councils)

Agencies: Interpret, administer, enforce law. DOL (OFCCP); EEOC; FEP; publish rules and regulatory guidelines that are given “great deference” by courts. Federal Register; Code of Federal Regulations.

EEO Framework - Specific Laws

I. U.S. Constitution5th Amendment:

Due Process of law --- Prohibition upon federal government; no person shall be deprived of life, liberty, or property; does not speak directly to specific subjects such as employment Courts prefer to defer to existing statutory laws because it is more specific!!

14th Amendment:Prohibition for States to enacts any law that does not “guarantee” equal protection for all.

II.Statutory LawsCivil Rights Act 1866:

Right to make and enforce contracts for employment … for all citizens as enjoyed by white citizens.

Civil Rights Act of 1871:Right to sue if deprived of any rights or privileges guaranteed by the Constitution and laws for ALL citizens. Must show intention.

Equal Pay Act 1963:Equal pay for equal work regardless of SEX (female employees only); amendment to FLSA .

Session #9Quick Decision ReadingCase Review – Next Time and Statistics AssignmentsReading #3 today and #4 next timeArticles?Review – External Environment

The Legal Environment: Workplace Torts; FLSA, NLRA; Constitution – Amendments; Early Civil Rights Acts; EEO – Framework; EPA; CRA 1964 TVII

Today: Legal EnvironmentTitle VIIBFOQ Exercise; SH ExerciseSH Reading – Reading #4 (Cassandra and Sarah)ADEAADA – Reading #3

EPAEqual pay for equal work regardless of SEX (female employees only); amendment to FLSA .

“Equal” Work: Substantially similar – Requirements concerning skill, effort, responsibilities, working conditions.

Exceptions: Seniority; Merit; Quantity of production;

Note: If in violation of EPA, ER may not LOWER wages.

Consider --- Internal equity and job evaluation; Comparable worth.

Title VII of CRA 1964: Coverage: ERs with 15 or more

employees; Federal, State, Local governments; Educational Institutions; Employment Agencies; Labor Unions

Not covered: Until recently “Congress”; Private Clubs; Religious Organizations.

CRA 1964: Several Titles each focusing on discrimination in a different “sectors” of society (education, right to vote,… ) Title VII focuses on discrimination in employment.

Title VII Enforcement: EEOC Contents of TVII:

703 (a) Employer may not discriminate on the basis of race, color, national origin, sex, and religion in any employment decision.

Title VII Color: White, black, yellow, brown, red. Race: Local geographic or global human

population distinguished by genetically transmitted physical characteristics … Caucasian; Negro; Hispanic; Oriental; Indian.

National Origin: Citizenship; Heritage; Any country, nation.

Religion: All kinds; not associated with any of the other characteristics; Christian, Hindu, Muslim, Buddhist.

Title VII703 (b) …. Nondiscriminatory apprenticeship program704 (a) …. Unlawful to discriminate … if opposed unlawful employment practice … assisted in TVII investigation.704 (b) …. Prohibits ads concerning employment indicating preference for any of the prohibited factors.

1978 Amendment: Pregnancy Discrimination Act --- prohibits discrimination on the basis of pregnancy, childbirth, or related condition. Reinstatement right for similar position; no loss of seniority; coverage of disability insurance.

Title VIIExemptions: that are written into the lawDiscrimination on the basis of the “protected factors” is permissible when such qualification is a bona-fide occupationl qualification (BFOQ) = reasonably necessary to the operation of that particular business or enterprise; burden of proof is with ER; very narrowly interpreted --- preferences of ER, coworkers, clients are irrelevant.Seniority Systems: Bona fide seniority or merit systems are lawful if no intention to discriminate; job or departmental systems are not seen as “bona fide”, plant or company-wide systems are seen as “bona fide”.

Exemptions to TVII Testing: Employer may give and act

upon professionally developed ability tests if they are not used to discriminate on the basis of the protected factors.

Preferential Treatment: It is unlawful to interpret TVII as requiring preferential treatment of individuals of protected groups - reverse discrimination

National Security: Discrimination is permitted

Further TVII Issues:

Fetal Protection -- Johnson Controls 1991: An employer’s exclusion of fertile women, but not fertile men, could not be justified on grounds that the rule protected the woman’s reproductive capacity and the physical welfare of the fetus. The safety qualification is limited to those instances where sex or pregnancy presents danger to customers or third parties. A fetus is not a “third party” whose safety is essential to the operation of the employer’s business, and thus cannot be the basis of a BFOQ.

Sexual Harassment:

Unwelcome sexual advances in exchange for a favorable employment condition. Quid pro quo; hostile work environment sexual harassment. Employer is liable. Pattern of behavior. Policy and process. Onclae v. Sundowner --- same sex. Faragher v. Boca Raton --- ER liable even if the employer had no knowledge of the harassment. Burlington v. Ellerth allows employers to be sued for quid pro quo even if the employee suffered no tangible loss of job benefits for declining the supervisor’s sexual advances

Session #10

Executive Order 11246 Contractors doing business with

federal government ($ amount of contract specified). Same provisions as TVII AND requires contractors to develop affirmative action plans: Formal, specific personnel programs that are designed to increase the participation of protected groups.

1967 … sex-based discrimination added as prohibited

Age Discrimination in Employment Act 1967

Amended 1986. Protects EEs and applicants who are 40 years old and above (no upper limit). No mandatory retirement age (except law enforcement officers, firefighters, tenured professors, executive under certain conditions, top policy makers.);No reverse discrimination.

EEO Legislation - How effective?EEO Laws clearly address societal problems --- safeguarding fair treatment in employment of traditionally disadvantaged groups.

Hire the most qualified applicant -- the role and effect of stereotypes

ReviewStatutory Laws

Early Civil Rights ActsEqual Pay ActTitle VII of CRA 1964

CoverageWho is protected?How?Pregnancy Dicrimination Act 1978

ReviewExemptions: BFOQ, business necessity, seniority system, testingPreferential Treatment and Reverse DiscriminationFetal ProtectionSexual Harassment (Training Handout)

ReviewReadings

Employment at Will and recent Legal DevelopmentsSexual Harassment - Assignment back

Executive Order 11246 Contractors doing business with

federal government ($ amount of contract specified). Same provisions as TVII AND requires contractors to develop affirmative action plans: Formal, specific personnel programs that are designed to increase the participation of protected groups.

1967 … sex-based discrimination added as prohibited - Executive Order 11375

AAP and reverse discrimination

Age Discrimination in Employment Act 1967

Amended 1986. Protects EEs and applicants who are 40 years old and above(no upper limit). No mandatory retirement age (except law enforcement officers, firefighters, tenured professors, executive under certain conditions, top policy makers.); no reverse discrimination.

Age Discrimination in Employment Act 1967

Amended 1878, 1986. Protects EEs and applicants who are 40 years old and above (no upper limit). No mandatory retirement age (except law enforcement officers, firefighters, tenured professors, executives under certain conditions, top policy makers.)No reverse discrimination.

Americans with Disabilities Act 1990

Since 1994 covers Ers with 15 or more Ees.

43 mill. Disabled Americans.Protects:

Physical or mental impairment that substantially limits one or more life activities (walk, see, ..)Record of impairmentRegarded as having impairment

… about 1,000 disabilities (affective disorders, biochemically based disorders - AIDS, Cancer, Anxiety Disorders, Eating Disorders, Infertility, Epilepsy)Disability evaluated with adjustive equipment (glasses)

ADAHow it protects:

.Punitive damages

.Essential job functions

.Reasonable accommodations

.Restructuring of physical facilities

.Perceptual restructuring

… 1994 5,500 complaints (25% more than were expected)ADA Reading - Quiz Back

ADA… cultural change; education vs compliance… “Be reasonable, thoughtful, caring, and you can comply”

Janet Reno

Other LawsRehabilitation Act 1972Vietnam Era Readjustment Act 1974

Family and Medical Leave Act 1993

Employers with more than 50 employees have to provide 12 weeks of unpaid leave for family or medical emergencies.

Employer must guarantee the employee the same or a comparable job. The employer must also pay the health-care coverage for the EE --- which the EE has to be back if he/she fails to return to work. ERs are allowed to exempt “key” employees – defined as the highest paid 10% of their work force whose leave would cause substantial economic harm to the employer. Also exempt are EEs who have not worked at least 1,250 hours (25 hrs a week) in the previous 12 months.

Session #11Stuff backAdjustements to syllabus:

No SH VideoStat Assignment #1 due October 9th

Stat Assignment #2 due October 16th

Review:Statutory Laws – Who covered; Who protected, How protectedReadings – ADA; SHExercises – BFOQ; SH

CasesFinish Legal Enviro

Enforcement of Laws and Court Process

Filing a Discrimination ComplaintLocal EEO AgencyNERC (Nevada Civil Rights Commission)EEOCInvestigationRight to sue letter

Evidence of DiscriminationIntentional DiscriminationDisparate Treatment: different standards applied to various groupsAdverse Impact: same standards are applied but disproportionately less minority applicants are selected

Session #12MHRA Tuesday, October 9, 4:00pm AB 209

Speaker

October 18 – Midterm; October 9 – Study GuideGraduate Project Stat Assignment #1 due October 9th

Review:CasesFinish Legal Enviro

Federal Court ProcessPRESENTATION OF EVIDENCE IN

TITLE VII CASESBurden of Proof

Plaintiff Defendant Plaintiff

Prima Facie Evidence1. Disparate Treatment 1. Job-based/legitimate 1. Defendant explanationpretext; true McDonnell Rule: 4 conditionsreason was rejection for prejudice2. Adverse Impact 2. Business Necessity, 2. Other

method 80% or 4/5 Rule BFOQ, Validation

Disparate Treatment: 4 Conditions- McDonnel Rule

Plaintiff must showbelongs to protected classapplied and was qualified for the jobdespite the qualifications - was rejectedposition remained open and the employer continued to seek applications from persons with the complainant’s qualificationsApplied also for ADEA cases

Adverse Impact: 80% or 4/5 RuleSelection Ratios

Number of nonminority applicants selectedDIVIDED BY

Number of nonminority applicants appliedTHIS IS

Nonminority selection ratioNonminority selection ratioNumber of minority applicants selected

DIVIDED BY

Number of minority applicants appliedTHIS IS

Minority selection ratioMinority selection ratio

Adverse ImpactCompare the two selection ratiosIf the ratio for nonminorities is smaller there may be evidence of discriminationIf the ratio is less than 80% or 4/5 of the nonminority ratio, then there is evidence of adverse impact (because the difference in the ratios is statistically significant)

Adverse Impact - Example100 White applicants100 African American applicants20 of the White applicants are selected5 of the African Americans are selected

20:100 = .2 Nonminority Selection Ratio5:100 = .05 Minority Selection Ratio

.05 : .2 = .25 This does not meet the 80% rule!

Adverse Impact - Example100 White applicants100 African American applicants20 of the White applicants are selected16 of the African Americans are selected

20:100 = .216:100 = .16 AND .16 : .2 = .80 meets the 80% rule BUT 16 … 80%

General Statistical Evidence for Discrimination

Stock Statistics# of women managers in org.

DIVIDED BY

# of skilled women managers in the work forceTotal # of managers in the org.

DIVIDED BY

Total # of skilled managers in the work force

What is the relevant labor market? EEO 1 form

Flow Statistics# of nonminority applicants selected

DIVIDED BY# of nonminority applicants

# of minority applicants selectedDIVIDED BY

# of minority applicants

When is the difference between these two ratios significant?

.80% or 4/5 ruleStandard Deviation Rule

Standard Deviation RuleProvides a rule of thumb to judge whether or not the # of minorities selected is representative of their proportion in the applicant pool.S.D. = Square Root of Total # of minority applicants/Total applicants

MULTIPLIED BYTotal # of nonminority applicants /Total applicants

MULTIPLIED BYTotal # of persons selectedThe number of minorities selected should be in the following range:

- 2S.D. < Mean < + 2S.D.

Landmark Selection CasesPage 66Resulted in establishing burden of proof requirements

Session #13Graduate Project Review

Definition of DiscriminationStock Statistics and Flow StatisticsLandmark Selection Cases

Measurement in SelectionPrinciplesReliabilityValidity

Review - MeasurementWhy measurement in selection?How can we mess up?How to capture applicant KSA’s? Why is this difficult?We need criterion and predictor measures. Explain.What are measurement scales? What type of measurement scales are distinguished?What is a frequency distribution? Measures of central tendency and variation?Describe the characteristics of the Normal Distribution.What is the purpose of Hypothesis Testing?

Measurement in SelectionI Overview

Selection decisions are based on what information?

Purpose is to ……..

Measurement in SelectionI OverviewSelection decisions are based on what information?

Purpose is to match the ind and the jobNeed information about both:

JD -> KSA’s required for the job?? -> KSA’s of the individual

How can we mess up?Measure irrelevant KSA’sMeasure KSA’s inaccurately

How can we “accurately” capture applicants’ KSA’s?

Ask * Observe * Test

We must determine the type and level of KSA’s that applicants have. The assumption is that the higher the level of KSA’s the higher the level of predicted performance.Level? = Measurement = Quantification

Definition of Measurement

Application of rules for assigning numbers to objects to represent quantities of attributes.Differences between applicant scores are due to actual differences in KSA’s.Rules

Specified algorithms to assign numbers (She is a 10) – same results by different users;

Measurement Attributes of an object: Physical and

psychological – which is are intangible and must be inferred from indicants of these objects.

Criterion: measure or definition of what is meant by employee success on the job; it is the dependent variable to be predicted by KSA’s; e.g., employee behaviors, attitudes, supervisor ratings

Predictors:indicants of relevant attributes; predict criteria

Must be important to the job (job related) Must be measures of attributes that are identified

as critical to job success

II Measurement and Individual Differences

Scales of Measurement Measurement is prerequisite for any

statistical analysis; how precisely can we measure – can we detect small differences (classification of success as “yes” or “no” OR degree of success??)

Scale Means by which individuals can be

distinguished on a specific variable Nominal scale: Scale composed of mutually

exclusive categories (sex, race, job class); the numbers are “labels”; only frequencies.

Scales Ordinal scale: Ranks objects (hi, lo); differences

between numbers yield additional information but not on the magnitude of the differences among ranks; e.g., percentile (represents the proportion of persons taking a test who made below a given score – 70th percentile means that 70% scored lower and 30% scored higher; does not tell how much higher and lower)

Interval scale: Arbitrary – no absolute zero; interpretation of differences – 40 vs 80 points does not mean 2 times the level of skill; e.g., zero on a test for math skills does not mean that the individual has zero math skills

Ratio scale: physical measures (height) and counting; has absolute zero.

Standardization of Selection Measures

Definition: Systematic instrument, technique, or procedure for assigning scores to a characteristic or attribute of an individual

Detect a true difference Standardized if: Content – measures by same

information; Administration - information collected the same way; Scoring – rules for scoring are pre-specifiedIndividual Differences

Applying the scale, each applicant receives a score – how do we interpret the scores? What do they mean?

Interpreting Individual ScoresFrequency DistributionHow many time did we get each score? First understanding of what our sample (applicant pool looks like) – did applicants tend to score higher or lower or are scores evenly distributed?

Frequency distribution is a frame of reference to give meaning to scores.

Most characteristics are normally distributed – bell curve! That means that most applicants score around average (have an average level of the characteristic, a few have more and a few have less.

Distributions differ with respect to

Central tendency: Mean Mode – most often observed score

Median – 50% of the scores are above and 50% are below this score

Variation: Mean of squares of the deviation scores (variance) depends on the extent to which scores cluster together; the square root of the variance is the standard deviation – a large standard deviation means that the scores a widely spread around the mean, a small standard deviation means that the scores are clustered around the mean

Skewness and Kurtosis

Skweness:Scores are symmetrically or asymmetrically distributed around the mean; if the scores are symmetrically distributed then the mean = median; the distribution is positively skewed if the bulk of the scores is above the mean and the mean is larger than the median; negatively skewed if the bulk of the scores is below the mean and the mean is smaller than the median.

Kurtosis: Peaked or flat

Probability DistributionsIn order to draw conclusions about the scores that applicants receive we have to evaluate whether our results are statistically significant; we want to make inferences from our sample about the population – statistical significant results are not random but are truly describing the population.

Probability distribution or probability density function – the normal distribution is a theoretical density function

Decreasing probability values when the variable values grow extreme from the mode

It is symmetric if: mean=mode=median Entire area under the curve = 1.00

Session #14Important Dates:

October 16 – Statistics Assignment #2October 18 – Midterm Exam (Study Guide +)October 30 – Quiz on Reading #5: JA

Graduate Projects: Cassandra – Selection Methods for Executives in Japan, Australia, the UK, and the U.S.Mike - Interviewing and Organizational FitBen – “Suspect” Selection Methods

ReviewMeasurement in Selection:

Principles – Hypothesis TestingReliability

ReviewHow do we evaluate whether two variables are related to each other?Why and how do we determine whether our result is statistically significant?Why do we need to evaluate the quality of our measures?What does it mean when a measure is reliable?How do we assess whether a measure is reliable?What does a p-value of .02 imply?

Tests and Reference Sources

Buros’s Mental Measurement YearbooksThe Mental Measurement Yearbooks DatabaseJournals

Normal Distribution Standardized normal distribution

mean = 0 and SD = 1 68% of the scores are within + and – 1 SD

around the mean In selection we assume that most

characteristics that we measure are normally distributed in the population – that means if had an endless number of observations our frequency distribution would look like a normal curve

This is important because evaluating the statistical significance of what we are interested (hypotheses testing) is based on the assumption of a normal distribution.

Normal Distribution If we assume a normal curve we can

calculate z-scores – that means we can transform our raw scores (the score that the applicants received) into a score “on the normal curve” by deducting the mean from each raw score and dividing that number by the SD (this is called the Z score);

so for each raw score we get a z score; that is important because we can now more simply calculate other statistics such as correlations

Session #15Important Dates:

October 18 – Midterm ExamOctober 30 – Quiz on Reading #5: JA

Review and Assignment #1Measurement in Selection:

Principles – Hypothesis TestingReliability

Hypothesis TestingIn order to draw valid conclusions from our

sample we must show that our results are statistically significant (representative of the population) and not random.

We would like to reject the null hypothesis which says that our results are not truly reflecting the population

For example: We want to conclude that the correlation between test scores and performance that we got for our sample is “true” – Null Hypothesis: rxy = 0 which means that there is no relationship between x (test scores) and y (performance score).

Hypothesis TestingIf H0 is true and we reject it we make a Type I error which would be bad and we want to avoid it;Therefore, we allow only a minimum level of error in rejecting the H0 (traditionally .05 or .01 – this is your alpha level). Based on the observed correlation and the number of observations in our sample we calculate a t-statistic. We then find the corresponding values, based on the sample size and the alpha level in the table for the t-distribution. If our obtained t-value is larger than the value in the table then our result is significant and we can reject the notion that there is not really a relationship between the two variables.

p -ValueP value for a sample outcome is the probability that the sample outcome could have been more extreme than the observed one. Large p-values support H0 while small p-values support the alternative hypothesis. Compare the p-value to the specified alpha risk. If p < alpha then conclude Ha (significance)

Stat Assignment #1Descriptive StatisticsTwo employment tests with scores for 15 employeesWhich test should be used? Which applicant should be hired?Determine the correlation between test scores and performance. The magnitude and significance of the correlation are used to determine which test should be used.

Assignment #1Purpose: Review of Statistical Concepts and Overview of Measurement ConceptsTest A and Test B - measure the same KSAType of Data -- Interval, no absolute zeroDescriptive Statistics - Range A: 18-47 (29) and Range B: 10 - 27 (17) => SD for A > than for BInterval size for Test B: 4 or 3 points per group (17:5); Test A 6 points;Normally distributed test scores VS our test resultsNegatively skewed: mean (31.5) < median (32.5)Significance t-test and p-value

Quality of Measures: Reliability

How good a measure is my test? To what extent does the measure accurately capture the KSA we are interested?The scores obtained on a measure are

X obtained = X true + X errorIf there was no error in the measure, every time we apply the measure to the same person we should get the same score.A reliable measure is a consistent measure.The reliability of a measure reflects the measures consistency.

ReliabilityThree methods to evaluate the reliability of a measure Each method focuses on a different source of measurement error. Measurement error are those factors that impact the obtained score but are not at all related to the attribute that is being measured.The methods:

Test-Retest ReliabilityParallel or Equivalent Forms ReliabilityInternal Consistency Reliability

Split-Half and Odd-Even; Cronbach AlphaSpearman-Brown Adjustment

Spearman-Brown Formula to Correct a Split-Half Reliability

Coefficient

measureselection theof 2 and 1 Partsbetween n correlatio ther

lengthin increased test was the timesofnumber nmeasureselection totalfor thet coefficien yreliabilit half-split corrected ther

:

1)r-(n1

nrr

12

ttc

12

12ttc

Where

ReliabilityThe conclusion that a measure is reliable can only be drawn if, and only if, the reliability coefficient (a correlation coefficient) is statistically significant (as determined by a t-test.

Meaning of Reliability Coefficient

The extent (in percentage terms) to which individual differences in scores of a measure are due to “true” differences in the attribute measured and the extent to which they are due to chance error

ReliabilityInterpretation of the reliability coefficient

The reliability coefficient is equal to the correlation coefficient between the obtained and the true score squared page 141Acceptable magnitude of reliability The standard error of measurement - is the amount of error to be expected in an individual’s score. We calculate the standard error of measurement as the SD of the sample multiplied by the square root of 1 minus the reliability coefficient

Standard Error of Measurement

X measure ofy reliabilit ther

X measureon score obtained ofdeviation standard the

X measurefor t measuremen oferror standard the

:Where

xxxmeas

xx

x

meas

r-1

ReliabilityImportant

The difference in the score between two applicants is only significant if it is at least two times the standard

error of measurement.Example:The standard error of measurement for a test is 1.5. Candidate A scores 18, candidate B scores 24 - does candidate B really have more of the attribute that is being measured?

Assignment #2Reliability of written test:

Test - Re-testInternal Consitency - Split Half

Reliability of the final interview:InterraterScreening with supervisorScreening with technicianSEM - which candidate to choose

Quality of Measures:Validity

Validity in Selection concerns the following question: How appropriate is it to make inferences from the scores on a measure to performance?Is the score a good predictor of performance? Is the score actually related to future performance?Relationship between reliability and validity

Quantitative Relationship between Validity and Reliability

Ypredictor oft coefficieny reliabilitrXpredictor oft coefficieny reliabilitr

t)coefficien (validity Ycriterion and Xpredictor

between n correlatio possible maximum r:Where

rrr

yy

xx

xy

yyxx xy

ValidityThree methods to evaluate the validity of a measure.Criterion-Related (Empirical) Validity

Predictive ValidityConcurrent ValidityContent ValidityConstruct Validity

Major Steps in Conducting Concurrent Validation Studies

Conduct analyses of the jobDetermine relevant KSAs and other characteristics required to perform the job successfullyChoose or develop the experimental predictors of these KSAs.

Major Steps in Conducting Concurrent Validation Studies

Select criteria of job successAdminister predictors to current employees and collect criterion dataAnalyze predictor and criterion data

Major Steps in Conducting Predictive Validation StudiesConduct Analyses of the jobDetermine relevant KSAs and other characteristics required to perform the job successfullyChoose or develop the experimental predictors of these KSAs.

Major Steps in Conducting Predictive Validation StudiesSelect criteria of job successAdminister predictors to job applicants and file results After passage of a suitable period of time, collect criterion dataAnalyze predictor and criterion data

Requirements for a Criterion-Related Validation Study

The job should be reasonably stable and not in a period of change or transitionA relevant, reliable criterion that is free from contamination must be available or feasible to develop

Requirements for a Criterion-Related Validation Study

It must be possible to base the validation study on a sample of people and jobs that is representative of people and jobs to which the results will be generalizedA large enough sample of people on whom both predictor and criterion data have been collected must be available

Content versus Face Validity

Content Validity deals with the representative sampling of the content domain of a job by a selection measure

Face Validity concerns the appearance of whether a measure is measuring what is intended

Session #17Midterm Exam – Next WeekReview and Assignment #2

ReliabilityContent Validity

Assignment #2Reliability of written test:

Test - Re-testInternal Consitency - Split Half

Reliability of the final interview:InterraterScreening with supervisorScreening with technicianSEM - which candidate to choose

Session #18

Content ValidityUtility AnalysisRegressionSelection Methods - KSA Measures

Key Elements of Implementing a Content Validity Strategy

Conduct a comprehensive job analysisSelection of experts participating in a content validity study – SME’sSpecification of selection measure contentAssessment of selection measure and job content relevance

Major Steps for Implementing a Construct Validation Study

The construct must be carefully defined and hypotheses formed concerning the relationships between the constructs and other variablesA measure hypothesized to assess the construct is developed

Major Steps for Implementing a Construct Validation Study

Studies testing the hypothesized relationships between the construct measured and other, relevant variables are conducted.

Major Factors Affecting the Size of Validity Coefficients

Reliability of Criterion and PredictorRestriction of RangeCriterion Contamination

ValidityInterpretation of Validity Coefficients

Magnitude and SignificanceStandard error of estimate shows how much error there may be in the predicted score.It is determined as the SD in the performance scores times the square root of 1 minus the squared validity coefficientCross-validationCorrection for attenuationCorrection for Restriction of RangeCriterion Contamination

Utility AnalysisUsing dollar-and-cents terms as well as other measures

such as percentage increase in output,it shows the degree to which the use of a selection measure improves the quality of individuals selected

over what would have happened if the measure had not been used.

An Equation for Calculating the Utility of a Selection Program

Expected Dollar Gain from Selection=

NsrxySDyZx-NT(C)

Expected Dollar Gain from Selection=return in dollars to the organization for having a valid selection program

An Equation for Calculating the Utility of a Selection Program

Ns=number of job applicants selected

rxy=validity coefficient of the selection procedure

SDy=standard deviation of job performance in dollars

An Equation for Calculating the Utility of a Selection Program

Zx=average score on the selection procedure of those hired expressed in z or standardized score form as compared to the applicant pool

NT=number of applicants assessed with the selection procedure

C=cost of assessing each job applicant with the selection procedure

Strategies for Selection Decision-Making

How to transform DATA into relevant information

.Data Collection

.Data Combination

Judgmental and Mechanical MethodsSelection Decision-Making Strategies

.Multiple Regression - Compensatory Model.Multiple Hurdles.Combination.Profile Matching

Regression AnalysisY = f(X) - linear relationshipCollect data on X and YScatterplotEstimate the equation that describes the linear relationship between X and YEstimate in such a way so that the predictions that are made for based on X using the equation contain a minimal amount of errorLeast Squares Estimates - beta = regression coefficientThe equation for estimation is Y = beta0 +beta1X1

ExampleAssignment #3 - Multiple Regression

Empirical Weights for Selection DevicesX1 = Initial Screening Interview

X2 = Ability Test

X3 = Final Interview

Y = beta + beta1 X1 + beta2 X2+beta3 X3

The weights reflect the extent to which each selection device contributes to explaining performanceQuestion: Is a compensatory model what we want?

Session #19

Quiz on Job Analysis ReadingMeasurement QuizAssignment #3Discussion on JA ReadingSelection Methods - KSA Measures

Application Blanks

Midterm Exam back

Measurement Review QuizHandout

Stat Assignment #3Validity

Assignment #3Validation of several selection devices and interpretation and use of validity information

Initial interviewSupervisor interviewTechnician interviewMechanical ability test

Reliability: Best was mechanical ability test, then technician interview

Questions #1 and #2Steps in concurrent validation: page 164Weaknesses of concurrent validation: page 162Compare concurrent and predictive validation results in general: page 166

Validity QuestionsValidity of the initial interviewValidity of the supervisor interviewValidity of the technician interviewValidity of the mechanical ability test

Midterm ExamFrequencies95-90 289-85 184-80 779-75 474-70 169-65 264-60 3Mean: 76Letter grades90+ A, 88 A-, 85 B+, 80 B, 78 B-, 75 C+, 70 C

Session #20Syllabus – Update

November 8, 11, or 13 - Guestspeaker

November 6: Bio Item Reading – QuizSelection Project Instructions

November 13: Selecting Top Corporate Leaders - Questions

November 20: Interview: Quick Decision - Questions

November 27:Physical Attractiveness - Quiz

November 29:Intelligence and Conscientiousness - Questions

December 4:Criterion of Fit – Questions

Today ArticlesRe-do’sDesigning a Selection ProcedureSelection Methods

Application Blank

Session #21Update

November 15 - Guestspeaker

November 6: Bio Item Reading – QuizSelection Project Instructions

November 13: Selecting Top Corporate Leaders - Questions

November 20:Interview: Quick Decision November 27:Physical Attractiveness November 29:Intelligence and Conscientiousness December 4:Criterion of Fit

Today Re-do’s

Articles: Florence, Julie, KurtDesigning a Selection ProcedureSelection Methods

Application Blank

Designing a Selection Procedure -> 1 Job Analysis -> 2 Identification of relevant job performance dimensions -> 3 Identification of KSA’s necessary for the

job -> 4 Development of assessment devices to

measure KSA’s -> 5 Assessing the quality of the assessment

devices - reliability and validity-> 6 Use of assessment devices

JA ReadingWhat is JA? Define!

Developing a Selection Procedure: Selection Process for Logistics

Professor

JA => Tasks=> KSA RequirementsMeasures for KSA’sContent Validity??Selection Procedure

Selection Methods Introduction

For each methodTo measure which KSA’s/DesignAdverse ImpactValidity

Session #22November 27 – Interview ExerciseRe-dos, articles, quiz – next timeReligious, national origin harassmentArticles: Jon; Jessicah

Application Forms and ResumesIntroduction

Information about the applicant’s background and present status -- brief and general OR long and detailed??Based on .. Past behavior is a good predictor of future behaviorTo determine … minimum qualifications and general suitability for job; permanent record;Determine relative strengths and weaknessesIt is assumed that all data collected are used

Training and Experience RequirementsJob-related training - formal and informalType of training; length; quality

Application Form ….Careful with degree requirements

Why?

Certification requirementsExample

Application BlankSpecific job-related experience and accomplishments

Minimum qualifications p.429Maintained Filing System: YES NOUsed computer and Microsoft Word for Windows 2000 word processor to type letters and reportsUsed a Dictaphone to transcribe correspondence

TE Evaluation Form p.431Specific tasks are listed – indicate YES NOFor YES, describe experience

Application BlankMethods for collecting TE evaluation info

Holistic – general judgment about suitability p.433Point Method – A priori scale p.435Grouping – p.436Behavioral Consistency Method – Description of job behavior by ER and applicant p. 439Task based and KSA based methods p.439 -441

Application BlankLikely candidate for Adverse Impact -- Why?Current forms -- 100% had at least 1 inappropriate question; on average 7 inappropriate questions.Are these questions acceptable? What do you reaally want to know? P.416-410

What was your maiden name?What is your date of birth? What is your age?What is your height and weight?What language do you commonly use?What is your religious faith?List the number and ages of your children?Do you have any physical or mental disabilites?List your birthplace.Have you ever been arrested?Do you own your car/residence?

Application Forms ...Adverse Impact: HighValidity: On average .1 -- corrected for attenuation .13Select content

Job-related - Job-related languageUsefulnessFairness -- Face Validity

Validity of T&E Evaluation Methods (Schmidt and Hunter,

1998)Criteria

Predictor Measure Overall J obPerformance

Overall perf.in Trainingprograms

T&E MethodBehavioralconsistency methodPoint Method

.45

.11NANA

Related MeasuresY ears of experienceY ears of education

.18

.10.01.20

References and Recommendations

To verify informationIssuesAssess applicant’s job experienceAssess applicant’s effectiveness in those jobs -- what done and how well??Types of info received p.446

ReferencesNot appropriate to assess personality ..Sources of and methods to collect Reference Data

Methods: In-person; Mail p.448; Letter of R; PhoneSources: Former ER; Personal; Investigative agencies; Public record;

Usefulness of reference dataReliability: .4 or lessValidity: .16-.26Reference giver-better if immediate supervisorOld and new jobs are very similar?Adverse Impact ??

References ..Validity -- not much evidence -- favorable info -- job related

better if content of the new and old job are very similarlow validity because low reliability and restricted range

Recommendations Don’t use subjective infowritten consent by applicantask only specific job-related infoDevelopment of reference checking systemGuidelines for defensible references page 426 and 427

Session #23HR Games Team: SHRM MembershipTownhall Meeting – 11/27Workshop: Hire the best & avoid the rest – Bob BravettiArticles: Norma, Craig, Beth, JulieBehavioral Interviewing HandoutReading # 7 – Answers hand in at end of classReview

Application Form and ResumeReferences

Application, resume, references

Design – PurposeWhich KSA’s?Recommendations

Adverse Impact?Validity?

WABChoose criterionSample sizeAs many predictors of HR outcomes as possibleRegression => weights for itemsAI but can show validity

BIO DataQuestions about personal background and life experiences Why?

BIO DataPast behavior=> Future behaviorACTAutobiographical questions:

academic achievement, work attitudes, self-perception, feelings, values, educational experiences,hobbies, family relations, use of leisure time, early work experiences -- focus on motivation??

BIO DataEnhances info in ABTypes of BIO data items

Hard vs soft p.487Response type p.486

BIO Data

BIO data are good predictors of job success (validity) and have less adverse impact on minorities than do many traditional tests; Face validity??? –

BIO DataInclude as one of several predictorsCriteria: tenure; performance in training; performance ratings; productivity Mean validity coeff: .35; Engineering .41; clerical .52; management .38; sales .5Must be based on JA and must be empirically scored; reliable and accurate if verifiable

BIB Reading – Corporate Leaders

Ben and Gary

Developing BIO DataSTEPS IN CONSTRUCTION

Selecting a JobAnalyzing the Job and Defining the Criterion Life History DomainForming Hypotheses of Life History ExperiencesDeveloping a Pool of Biodata ItemsPrescreening and Pilot-Testing Biodata Items

Develop BIO Data for Professor in HR

Developing a Selection Procedure: Selection Process for Logistics

Professor

JA => Tasks=> KSA RequirementsMeasures for KSA’sContent Validity??Selection Procedure

Session #27HR Games Team – Six students in MGRS 490Reading #8 – Answers at end of classReading #9 - Quiz Reading #10 – Questions Nov. 29Reading #11 – Quiz on December 4Selection Project December 4 or 6??Interview Assignment – 11/29 and 12/4Final Exam – Project Presentation

December 18, 4:30 – 6:30p.m.Graduate Project – due December 17Reading #7 - BackLast Time – Recruitment; SATArticles: Kyle, Tabor, Mike

Employment InterviewKSA’s to be measuredValidityAdverse Impact

Employment InterviewSelection interview:

dialogue, gather information evaluate qualifications

Selection interview: varies in type content

Generally, the interviewlacks standardization in questions and evaluationis not focusedis worker rather than job-content orientedrequires the interviewer to fulfill multiple functions

Interviews involve cognitive and social processesInformation processing and decision-makingInterpersonal influences

Employment InterviewResearch

Interview does not add to selecting the most qualified candidate … because…..

InterviewSources of problems

impression formation human perception

InterviewInformation processing and decision-making

observe behaviorsattribute to traits impressions about applicant depend on interviewer’s knowledge structure, a priori beliefs, recall of informationE.g.: High GPA = Diligence, hard work; Competitive sport = Aggressiveness; PA = Social Skills

Employment InterviewModel: Interviewer’s Information Processing and Decision-MakingImportance of knowledge structures

Improve the Validity of the Interview

1. Decide on location and seating2. More than one interviewer – Panel3. KSA’s to be measured: Measure interpersonal, communication skills4. Job-related questions only - Multiple Questions (Behavioral)5. Limit pre-interview info6. Use a rating format7. Train the interviewer

Employment InterviewSee transparencies

Interview SimulationRelevant TasksRelevant KSA’s - combine into categories or dimensionsKSA’s to be measure in the interviewLinkage between Question and KSAQuality of QuestionsInterview Structure/ Process -

1. Measure interpersonal, communication skills2. Job-related questions only - Multiple Questions (Behavioral)3. Limit pre-interview info4. Use a panel5. Use a rating format6. Train the interviewer7. Semi-structure

Ability TestingTesting – DefinitionTypes of tests

Mental Ability Tests - Wonderlic pg. 527Mechanical Ability Tests - Bennett and McQuarrie 529Clerical Ability - Minnesota 532Physical AbilityIntegrity Tests

Job RelatednessAdverse ImpactValidity

Personality AssessmentMethods - DesignJob RelatednessAdverse ImpactValidity

Session #15“Stuff” and Articles backCurrent IssuesGraduate Presentations

Course SummaryProject BackProject Presentations

HR and Org effectivenessIndividual effectiveness =

f(Ability,Motivation)

Performance = Ability * Motivation

HR and Org. EffectivenessMatch

Individuals (Knowledge, Skills, Abilities)

withJobs (Requirements and Rewards)

The HRM FrameworkThe External Environment

EconomySocial

EnvironmentLabor Market

LegalEnvironment

Match

Individual*KSA’s*Needs

HR Activities:Recruitment,Selection,Training,Compensation,Labor relations Job

*KSA Requirements*Rewards

HR Outcomes:Job SatisfactionOrg.commitmentAttractionRetentionAttendancePerformance

SelectionDefinition - Selection: The process of obtaining and using information about job applicants to determine who should be hired. Focus here is on how to collect relevant info on applicants’ KSA’s. Final decision must be accurate and fair.

Course SummaryExternal Environment

The Labor Market - Demand/Supply (Workforce - Quality+Composition/Quantity)Legal Environment

Principles of Selection - MeasurementTypes of MeasuresValidity and Reliability

Selection Methods - Which KSA’s? Design? Adverse Impact? Validity

Application Blank/T&E/Bio Data/ReferencesEmployment InterviewTests

Eleven ReadingsTie that bonds - Psych Contract ChangesEmployment at WillADA - Unintended ConsequencesThree pronged approach to Sexual HJA in HRBio ItemCorporate Leaders - Bio DataInterview - Quick DecisionInterview - Physical AttractivenessConscientiousness - gNotion of Fit

Selection ProjectWhat is CONTENT VALIDITY??

Job AnalysisMatrices - LinkagesKSA Measures - Appropriateness, DesignReport - Completeness

Specific JobsStudent Name Job TitleCathie * Forensic Technician IIKatie* Hardware EngineerAnn Warehouse Lead PositionCrystal Case Manager – Employee BenefitsAmy Bank Teller – Wells FargoLacey* Scheduler/Sales AssistantBrian Health Service School NurseGlenn Public Administrator Estate InvestigatorAmanda Medical TechnologistAngela Pharmacy TechnicianMatt District Ski and Snowboard CoordinatorMitch Automotive RefinisherChad Operations Technician/Order PickerMichael Lomoljo* Certified Nurses AssistantMichelle Computer Lab AttendantLarry Department SupervisorLaura Schoolbus DriverNavneet Sales Person

Specific JobsStudent Name Job TitleVictoria Computer Systems TechnicianRachel Operations ManagerJennifer McD Restaurant Manager – OutbackMike Schilling Line CookHadi Office Manager/ Client LiaisonJennifer Fast Department AssistantBrenda Accounts Payable Clerk

* Presentation

Employee Selection

THE END