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Intro to Stats

Intro to Stats. Methods Overview. The goals of science. Description: What happens? Prediction: When does it happen? Explanation: Why does it happen? Theory Causal Inferences Intervention/Application: What could be done to help? These all build on each other. Self Report .

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Intro to Stats

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  1. Intro to Stats Methods Overview

  2. The goals of science • Description: What happens? • Prediction: When does it happen? • Explanation: Why does it happen? • Theory • Causal Inferences • Intervention/Application: What could be done to help? • These all build on each other

  3. Self Report • Self-report methods: ask participants to tell you • Interviews • Questionnaires • Daily diary methods Fixed response scale Open-ended question

  4. Observational Data • Observational Data • Observations in natural settings • Laboratory-based observation

  5. 1. Correlational Research • Assess the naturally occurring associations among two variables • Positive correlation • rewards are positively associated with satisfaction • Negative correlation • conflicts are negatively associated with satisfaction

  6. Correlation does not imply causation! • Three possible interpretations of any correlation • X may cause Y • Y may cause X • Both X and Y may be the result of some other cause

  7. A B 2. Experimental Research • Manipulate one variable to see if it causes changes in another variable. • Does arousal lead to greater liking?

  8. Testing the WHATs and WHYs • 1:1 correspondence • If you pour x into y, you know x caused the explosion • If you pour x and z into y, you don’t know what caused the explosion • Random Assignment • In large enough samples, characteristics will be equally distributed

  9. 4 scales of measurement • Scale determines what analyses you can run • Nominal • Categories (gender, race, experimental conditions) • Ordinal • Ranks (freshman, sophomore, junior, senior) • Interval • Ordered with equal intervals, no zero (survey item) • Ratio • Ordered, equal intervals, zero (time)

  10. Reflecting on Scales • Any outcome can be assigned as one type of scale • Nominal is least precise, ratio most precise • The more precise, the more informative your data will be • More precise scales include all qualities of the scales below them

  11. Continuous vs. Categorical • Categorical: scale is best conceptualized as a series of categories (nominal, ordinal) • Gender • Class rank • Continuous: scale is best conceptualized as points on a continuum where it makes sense for someone to be partway between 2 scale points (interval, ratio) • Age • Happiness on a 7-pt scale

  12. Preparing for next lab • You will be asked to develop a study with your group • Anything that’s interesting (and be SURE it’s interesting!!!) • Writing Assignments • Poster Presentation • Several variables needed • Pick 1 outcome and measure it 3 ways (continuous) • Pick predictors • 2-group category • 3+ group category • One continuous predictor that precedes outcome either empirically or theoretically • One continuous predictor that does not precede outcome

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