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Lecture 4

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Carleton University
PSYC 2600
Chris Motz

Lecture 4 Thursday, January 13, 2011 - O-Data o Naturalistic- realistic context. Participants quickly ignore observer, natural behaviour starts to emerge. But there’s lack of control  Can see without interrupting or biasing what they’re doing, though  Difficult to control ambient noise level, what server does, etc. o Artificial- control conditions, variables. Sacrifice realism o Professional observers- can have professionals (trained, standardized) but lack in-depth knowledge/deeper understanding of individual  Could have people who know the participant (teachers, friends, family)  But they might want to present person in positive light  We can select observers from variety of social situations (work, school, etc.) to get whole picture of the personality o Benefits  Access to information not attainable through other sources  Can use multiple observers o Limitations  Poorly trained maybe- especially with family/friends/coworkers  Speculation about motives, feelings, etc. Even people who know the individual • Ex. Observing hostile behaviour in children, see kid move arm- was he intending to hit or was he off-balance? - T-Data o Different from self-report (questionnaire, ask directly about personality) o Here, use standardized form of testing  MRI, EEG, pedometer (activity level), Rorshach ink blot o Rorshach still considered test data because we have standardized set of rules for themes that person is talking about (even though it’s projective technique) o Limitations  Person may try to guess what’s going on  May just want to be helpful (self-esteem/stress related to activity level—given pedometer—tries to alter behaviour, increase activity level)  Or may want to undermine the research  Hard to know if participant and experimenter define the situation the same way  Researcher may have unintended influence- experimenter bias - L-Data o Data from that person’s life o Report cards, medical records, criminal records, history of employment (job records), history of residence (apartment/house), etc. o Can be used to help understand life outcomes related to aspects of personality o But incredibly tough to gather, reconstruct, to get complete picture of personality - Triangulation: use multiple types of data to get picture of personality (based way to overcome limitations) o More well-rounded, complete portrait of personality- will see this later - In personality psychology, we use questionnaires o Variety of ways to construct them o Self-esteem questionnaire- point out issues in designing it o Self-esteem: the way we feel about ourselves, positive and negative evaluation of self o 10 questions, Likert-type response (0-10) o For each question, can respond on that scale o 0- strongly disagree, 10- strongly agree o Do you want to have a mid-point? Option to say neither agree nor disagree? There will be some participant who always stays on the fence.  You may want to force them to recognize their have a leaning on one direction. o Reverse-score questions as a control—if person just wants to circle 10 on everything, it forces him/her to read all the questions—otherwise, can tell quickly whether the person has read the questions o Good question gives participants the opportunity to go on either side of the midpoint  In reality, there is an average to which we all cluster. Same for any personality characteristic—for the most part, we cluster around the middle.  There are some of us who have freakishly high self-esteem, some are at the other end.  Good question gives a chance for the people in the middle to be on the center, the people at each extreme to say they’re at the end. Reveals the differences in the population.  **Bad question: I always feel as though I’m the best person in the world. • Majority would strongly disagree • Only a few at the agree end • Skewed distribution • Nothing meaningful- we don’t see the variation in the group  **Bad question: At least occasionally, I don’t feel that I’m a terrible person. • Big cluster of people will strongly agree • Very few at the strongly disagree end • Skewed distribution • Nothing meaningful about group  We want naturally existing bell curve (normal distribution)  **Good question: I feel that I have a number of good qualities • High self esteem would agree, low self esteem would disagree, majority would be in the middle  **Good question: I’m able to do things as well as most people.  **Good question: I feel that I’m a person of worth at least on an equal basis as others. o Frequency distribution shows us the spread of scores on any one variable —the height of the curve represents the frequency  Spread of scores shows spread of data points in sample  If we do this enough, get a big enough sample of participants  Because we’ve designed a good enough questionnaire, get a natural bell curve o Reliability and validity- we’ll discuss them as they apply to questionnaire. But we can also talk about how they apply to study.  Reliability- consistent, accurate results • Standardized procedures • Standardized script, ordering of materials, manipulations in study • Eliminate error that might come from inconsistency in application of materials/instructions to participants • We want the test to be reliable too  Validity- all the variables have to be clearly defined, tests have to measure what they claim to measure • Lack of validity- wrong operational definition of validity (smiling shows happiness- could have nervous smile) - Correlational study- just studying things as they ex
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