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The Logic of Statistical Analysis Lesson 2 Population APopulation B Sample 1Sample 2 OR
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Mysteries of Life n We have questions l Why do people behave that way? l Is global warming occurring? l Will my cancer come back? n To get answers, we need… l Information Data l Explanation analysis & interpretation ~
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Theories & Statistical Models n Theories l Describe, explain, & predict real- world events/objects n Models l Replicas of real-world events/objects l Can test predictions ~
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Models & Fit n Model not exact replica l Smaller, simulated n Sample l Model of population l Introduces error n Fit l How well does model represent population? l Amount of error in model l Good fit more useful ~
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Models in Psychology n My research model l Domestic chicks l Effects of pre-/postnatal drug use l Addiction & its consequences n Who/What do most psychologists study? l Rats, pigeons, intro. psych. students n External validity l Good fit with real-world populations? ~
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The General Linear Model n Relationship b/n predictor & outcome variables form straight line l Correlation, regression, analysis of variance l Other more complex models ~
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Populations & Samples n Population l The whole group of interest l parameter population mean = n Samples l A portion of population l statistic sample mean = ~
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Populations & Samples n Research goals l Learn about population l Characteristics that widely apply l Impossible/impractical to directly study n Research methods l Study representative sample l Introduce sampling error l ~
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Analyzing Data n Descriptive Statistics l Quantitative descriptions of characteristics l Mean & standard error n Inferential Statistics l Statistical tests l Use sample descriptive statistics l Draw conclusions about population parameters ~
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Hypothesis Testing n Hypotheses l testable assumptions l About groups n Same l From same populations l Null hypothesis n Different l From different populations l Alternative hypothesis ~
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Population APopulation B Sample 1Sample 2 OR This or That?
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Hypothesis Test: General Form
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Logic of the Hypothesis Test n Difference between groups l Caused by independent variable n Difference between individuals l Due to individual differences l Average difference between individuals chosen randomly l Chance/error (or natural variability) ~
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Variability & Variance n Characteristics are variable l People are different n Variance l Numerical measure of variability l Expected differences between individuals n Statistics l Help sift through natural variability l Help determine if same or different ~
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Logic of the Hypothesis Test n Groups the same u Or too similar l Difference between groups = difference between individuals l Test statistic ≤ 1 n Groups different l Difference between groups bigger than difference between individuals l Test statistic >> 1 ~
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Rosenthal & Jacobsen (1968) n Inferential statistics l Hypothesis testing n Reporting results l Descriptive statistics for each group l Summary of results of statistical test n Bloomers (M=16.5, SD=19.4) had a statistically significant greater increase in IQ scores than Non-bloomers (M=7.0, SD=10.1), t(57)=2.36, p=.022.
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