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The Logic of Statistical Analysis Lesson 2 Population APopulation B Sample 1Sample 2 OR.

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Presentation on theme: "The Logic of Statistical Analysis Lesson 2 Population APopulation B Sample 1Sample 2 OR."— Presentation transcript:

1 The Logic of Statistical Analysis Lesson 2 Population APopulation B Sample 1Sample 2 OR

2 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 ~

3 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 ~

4 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 ~

5 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? ~

6 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 ~

7 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 =  ~

8 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 ~

9 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 ~

10 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 ~

11 Population APopulation B Sample 1Sample 2 OR This or That?

12 Hypothesis Test: General Form

13 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) ~

14 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 ~

15 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 ~

16 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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