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Industrial Psych Notes 1/25-1/29

by: Courtney Luber

Industrial Psych Notes 1/25-1/29 Psyc 3640

Marketplace > Clemson University > Psychlogy > Psyc 3640 > Industrial Psych Notes 1 25 1 29
Courtney Luber

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About this Document

These notes cover the material learned in class from 1/25-1/29
Industrial Psychology
Eric S McKibben
Class Notes
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This 6 page Class Notes was uploaded by Courtney Luber on Friday January 29, 2016. The Class Notes belongs to Psyc 3640 at Clemson University taught by Eric S McKibben in Fall 2016. Since its upload, it has received 15 views. For similar materials see Industrial Psychology in Psychlogy at Clemson University.


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Date Created: 01/29/16
1/25/2016 Methods and Statistics in I-O Psychology  Science—approach that involves the understanding, prediction, and control as some phenomenon of interest o Systematic process to help us achieve goals o Common scientific methods  Begins with observation, generate theory, generate specific questions you can test, create a hypothesis, create an experiment (collect additional data) o Logical approach to investigation  Based on a theory, hypothesis, or basic interest  Theory—educated explanation based on observations o Science depends on data  Gathered in a laboratory or the field o Research must be communicable, open, & public  Research published in journals, reports, or books  Methods of data collection described  Data reported  Analyses displayed for examination  Conclusions presented o Scientists set out to disprove theories or hypotheses (not prove!)  Goal is to eliminate all plausible explanations except one o Scientists are objective  Expectation that researchers will be objective & not influenced by biases or prejudices  Why do I-O psychologists engage in research? o Better equip HR professionals in making decisions in organizations o Provide an aspect of predictability to HR decisions o Helps to explain why people do what they do  Common Research Designs o Experimental  Random assignment of participants to conditions  Allows you to say that all groups are essentially equal  Correlation does equal causation in this case  Advantage—Can outline a true causal relationship  Independent variable causes dependent variable  Disadvantage—takes a lot of time, resources, and energy  Conducted in a laboratory or the workplace  Involves alteration/manipulation o Non-experimental  Does not include manipulation or assignment to different conditions  Disadvantage—correlation does not equal causation  Advantages—huge sample set very quickly and cheaply  2 common designs:  Observational design—observes and records behavior  Survey/questionnaire—most common o Quasi-experimental  Non-random assignment of participants to conditions  Quantitative methods—rely on tests, rating scales, questionnaires,& physiological measures o Yield results in terms of numbers  Qualitative methods—include procedures like observation, interview, case, study, & analysis of written documents o Generally produce flow diagrams & narrative descriptions of events/processes  Quantitative vs Qualitative o One is not better than the other; not mutually exclusive o Triangulation—examining converging info from different sources (qual & quan research)  Generalizability—application of results from one study or sample to other participants or situations (a broader population) o The more areas a study includes, the greater the generalizability o Every time a compromise is made, the generalizability of results is reduced  Sampling o Participantsjob titlestimeorganizations o Students in this particular psych classstudents in other psych classescertain point in timeClemson University  Experimental control—eliminates influences that could make results less reliable or harder to interpret  Statistical control—statistical techniques used to control for the influence of certain variables o Always factors you cannot think of o Does not allow you to say there is a casual relationship 1/27/2016 Histogram—has observed values on x axis and frequency on the y axis Ethical Behavior of I-O Psychology  Ethical standards of the APA  SIOP book of 61 cases (Lowman, 1998) o Cases illustrate ethical issues that are likely to arise in I-O psychology  Joel Lefkowitz (2003) published a recent book on values and ethics in I- O psychology  Descriptive statistics o Summarize, organize, describe sample of data  Frequency Distribution: o Horizontal axis = Scores running low to high o Vertical axis = Indicates frequency of occurrence  Measures of central tendency o Mean—add up all values and divide by number of observations o Mode—which value occurs the most frequently o Median— middle number  Variability o Standard deviation  How much change there is between the numbers and the average of change there is between a number and the mean o Or you could look at the range  Lopsidedness or skew o Mean is affected by high or low scores, median is not o Mean pulls in direction of skew  Inferential Statistics o Aid in testing hypotheses & making inferences from sample data to a larger sample/population o Include t-test, F-test, chi-square test  Statistical Significance o Defined in terms of a probability statement o Threshold for significance is often set at .05 or lower o Significance refers only to confidence that result is NOT due to chance, not strength of an association or importance of results.  Statistical Power o Likelihood of finding statistically significant difference when true difference exists o The smaller the sample size, the lower the power to detect a true or real difference  Concept of Correlation o Scatterplot  Displays correlational relationship between 2 variables o Regression  Straight line that best “fits” the scatterplot and describes the relationship between the variables in the graph  Correlation Coefficient o Slope of z scores o Statistic or measure of association o Reflects magnitude (numerical value) & direction (+ or –) of relationship between 2 variables o Ranges from -1.00 to 1.00 o 1.00 = perfect positive relationship; same z score; perfect diagonal line (45 degrees) o 0.00 = scattered dots; horizontal line o Positive correlation → As one variable increases, other variable also increases & vice versa o Negative correlation → As one variable increases, other variable decreases & vice versa o Strong positive correlation DOES NOT mean causation!  Curvilinear Relationship o If correlation coefficient is .00, one cannot conclude that there is no association between variables o A curvilinear relationship might better describe the association o Ex. stimulation (stress levels) vs performance  Multiple Correlation o Multiple correlation coefficient  Overall linear association between several variables & a single outcome variable  Meta-Analysis o Statistical method for combining results from many studies to draw a general conclusion o Statistical artifacts  Characteristics of a particular study that distort the results  Sample size is typically the most influential statistical artifact  Interpretation o Reliability  Consistency or stability of a measure  Test-retest reliability  Calculated by correlating measurements taken at Time 1 with measurements taken at Time 2  Memory vs extroversion  Memory—if you take a test once and then 24 hours after  Extroversion—if you take a test once and then a month later o Equivalent forms reliability  Calculated by correlating measurements from a sample of individuals who complete 2 different forms of same test  Problem: boredom sets in when the second test comes around; as we become fatigued, our ability to answer the questions appropriately wane o Internal consistency  Assesses how consistently items of a test measure a single construct  Calculates all of the possible correlations of items to come up with a value (alpha)  We want the value to be close to 1  Bare minimum is >0.7 o Inter-rater reliability  Can calculate various statistical indices to show level of agreement among raters  Values in the range of .70 to .80 represent reasonable reliability o Generalizability theory  Simultaneously considers all types of error in reliability estimates  Validity o Whether measurements taken accurately & completely represent what is to be measured o Measurement of how accurate the test is o Predictor  Test chosen or developed to assess identified abilities or other characteristics (KSAOs) o Criterion  Outcome variable describing important performance domain  Criterion-Related Validity o Correlate a test score (predictor) with a performance measure; resulting correlation often called a validity coefficient o Predicts outcome o Predictive validity design  Time lag between collection of test data & criterion data  Test often administered to job applicants  Predicts performance o Concurrent validity design  No time lag between collection of test data & criterion data  Test administered to current employees, performance measures collected at same time  Disadvantage: No data about those not employed by the organization  Use current data from current employees & then give intelligence test  Content-Related Validity o Demonstrates that content of selection procedure represents adequate sample of important work behaviors & activities or worker KSAOs defined by job analysis o I-O Psychologists can use incumbents/SMEs to gather content validity evidence o One question about this!!  Construct-Related Validity o Investigators gather evidence to support decisions or inferences about psychological constructs o Construct - concept or characteristic that a predictor is intended to measure; examples include intelligence, extraversion, and integrity o One question about this!!


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