Welcome Statistical Methods and Data analysis PSY-301.

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Welcome Statistical Methods and Data analysis PSY-301

Transcript of Welcome Statistical Methods and Data analysis PSY-301.

Page 1: Welcome Statistical Methods and Data analysis PSY-301.

Welcome Statistical Methods

and Data analysis

PSY-301

Page 2: Welcome Statistical Methods and Data analysis PSY-301.

Course Skills Objectives Computer Analysis of Data

Using SPSS (PASW) Statistical Package for the Social Sciences

Interpretation of Results What do results mean? What conclusions can be drawn?

Communication Written, oral, and graphical Effectively communicate results

and influence others ~

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Statistics are Tools

Tools that: are useful don’t tell truth or lies Are used by people

Statistics help us make decisions About variable & fluctuating

information Guided by human wisdom & values ~

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Application of Statistics Opinion/Political Polls

Influence public policy Benefits vs. safety risks new drugs / medical procedures Epidemiology (autism & vaccines)

Environmental issues Emissions control vs. economics

Courts Sentencing equity ~

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Statistics & Psychology

The Science of Statistics a set of methods & rules for

organizing, summarizing, and interpreting information

The Science of Psychology Behavior & cognitive processes describe, explain, predict & control Relationships between variables Similarities & Differences ~

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An observation on human behavior:

You see, really and truly, apart from the things anyone can pick up (the dressing and the proper way of speaking, and so on), the difference between a lady and a flower girl is not how she behaves, but how she’s treated. I shall always be a flower girl to Professor Higgins because he always treats me as a flower girl, and always will; but I know I can be a lady to you because you treat me like a lady, and always will.

Eliza Doolittle in George Bernard Shaw’s Pygmalion

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Testing the Pygmalion Effect

Can the expectations of others influence one’s behavior? Rosenthal & Jacobson (1968)

Predictor Variable Teacher’s expectation of student “bloomer” or “non-bloomer”

Outcome Variable Change in student IQ score ~

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Rosenthal & Jacobson (1968) “Oak School” 2d graders given new test

“Harvard Test of Inflected Acquisition”: HTIA

predicts learning spurts in top 20% Informed only teacher of scores

End of school year test again Test Of General Abilities: IQ test HTIA actually was TOGA

pretest - posttest

Operational definition Measure change in IQ scores ~

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Rosenthal & Jacobson (1968)

Conclusions not readily apparent “real” differences or normal variation Sampling error?

Descriptive Statistics: Average IQ change Bloomers: 16.5 Nonbloomers: 7.0

Inferential statistics Did bloomers improve significantly more

Experimenter Bias in research Importance of control ~

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Why Statistics?

Tools to critically evaluate information Help account for variations

differences & similarities Psychology goals

describe, explain, predict, control Statistics AID decision-making

Meaningful results from fluctuating data ~