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This 3 page Class Notes was uploaded by Takyra Thompson on Friday September 18, 2015. The Class Notes belongs to Psyc 318 at Old Dominion University taught by Barbara Winstead in Summer 2015. Since its upload, it has received 43 views. For similar materials see Research Methods in Psychlogy at Old Dominion University.
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Date Created: 09/18/15
Chapter 4 Defining and Measuring Variables I What is a Variable 0 Two or more values that contribute to any factor or attribute 0 Variables Qualitative vs Quantitative O Qualitative I Variable levels are categorized values of different kindtype I Measuring the quality of a value 0 For example sex religion color 0 Quantitative I Variable levels exist on a continuum from the low to high values re ected in amount I Number of sibling quiz score 0 Variables Discrete vs Continuous 0 Discrete I Intermediate values are impossible 0 Example number of cars number of Oscars won 0 Continuous I Intermediate values are possible precision limited only by our measurement tools 0 Height in inches personality scale score 0 In practice ultimately converted into discrete values 0 Independent and Dependent Variables 0 Independent variables factors the researcher manipulates or systematically varies the casual factor in a causeeffect relationship 0 Dependent variable behavior or that the researcher measure s to determine whether the IV has produced an effect the effect in the cause effect relationship 0 Predictor and Outcome Variables O In NONEXPERIMENTAL research we also have variables where we expect that one variable is related to or predict the other I Predictor variable measured or observed variablenot manipulated that we expect to be related to the outcome variable I Outcome variable a measured or observed variable that we expect to be related to the predictor variable I Situational or Subject Variables O Situational variables character the re ects differences in the environment stimuli or situations 0 Subject variable person characteristic that differs among individuals 0 Building Theories 0 At the simplest level I IV gtDV or Predictor gt Outcome 0 Mediator Variables O Mediators explain a casual relationship shedding light on the process by which the IVPredictor variable in uences the DVOutcome variable 0 Moderator Variables 0 Moderator Variables in uences the direction strength of the relationship between two variables I Constructs O Psychological scientists have their work cut out for them as they tend to be interested in phenomena that are not directly observable 0 Construct must be translated into something measurable 0 The process occurs via operationalization O generate on operational definition for aggression I Scales of Measurement 0 Measurement assignment of numbers to aspects of objects or events according to rules 0 Scale of measurement impacts how you analyze data I Scales of Measurement 0 Nominal least precise O Ratiomost precise 0 Nominal group objects into categories I Variable levels differ kind not in degree I Example gender political party affiliation O Ordinal I Values re ect rank ordering 0 Example 1st place 2rld place 3rd place 0 Interval I Numbers re ect actual amounts I Equal distance between intervals I 0 point is arbitrary I Likert scale 0 Ratio I Interval scales but zero point re ects true absence of property I Scores can be compared as ratios or percent I For example speed or dollars 0 Are our Measures any Good Accuracy Reliability and Validity 0 Accuracy re ects the degree to which measures align with known standard 0 Reliability refers to the consistency of measurement I Assumes a true score I Random measurement errorrandom uctuations from the true score I Several forms of reliability 0 Testrest consistency of scores over time 0 Internal consistency consistency of a measure within itself 0 Assumes multiple items 0 Interrater reliabilityindependent raters agree on score Validity addresses the alignment between our construct and the measurement tool we employed to gain insight into the construct I Like reliability validity can be addressed several ways 0 Free validitymeasure appears appropriate to participants 0 Example job applicants perceived that an interviewer asked jobrelevant questions 0 Content validity measure adequately covers the domain of inters 0 Example a course exam samples from all of the content students were exposed to in and out of class 0 Criterion validitymeasure predicts an outcome 0 Example conscientiousness in a positive predictor of job performance 39 Construct validity measure authentically represents the construct of interest 0 Demonstrated in part via convergent and discriminant validity O Convergent example scores on new creativity test correlate with scores on established creativity measures 0 Discriminant example scores on new creativity test are not correlated with scores on an assertiveness measure
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