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AP Psychology

AP Psychology. Inferential Statistics Sampling and Selection. Essential Question. 1-5 How do psychologists draw appropriate conclusions about behavior from research?. Inferential Statistics. You are trying to reach conclusions that extend beyond the immediate data alone.

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AP Psychology

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  1. AP Psychology Inferential StatisticsSampling and Selection

  2. Essential Question • 1-5 How do psychologists draw appropriate conclusions about behavior from research?

  3. Inferential Statistics • You are trying to reach conclusions that extend beyond the immediate data alone. • Used to test hypothesis about samples.

  4. Testing for Differences • If we have results from two samples we can ask the question: • Is there a difference between • the means of the two the samples?

  5. Testing for Differences • Using the assumption of a normal distribution, we can also ask the question: • How confident are we that the mean difference is genuinely represented in the population rather than just due to random variation? • Using inferential statistics, we can ask this question using a t-test when comparing two groups.

  6. P values and statistical significance • Generally, the t test gives a P value that allows us a measure of confidence in the observed difference. • It allows us to say that the difference is real and not just by chance. • The smaller the p value the least chance of making a false positive (Type I error). • A p value of less than 0.05 is a common criteria for significance. • We call this statistically significant

  7. An Example Experiment • Does caffeine improve our reaction time? • We recruit 40 people and give • 20 a cup of coffee • 20 a cup of decaffeinated coffee • We give them a brief reaction time test and record the results.

  8. Inferential Statistics • Caffeine condition • Mean = 500.32ms • SD = 172.60ms • No Caffeine condition • Mean = 608.64ms • SD = 146.93

  9. Effect of Caffeine on RT? Caffeine No Caffeine

  10. t-test results • Does caffeine improve our reaction time? • Caffeine condition has a lower mean RT. • We run a t-test on our samples and get: • p = 0.039 • Can we be confident that the difference in the data is not due to chance? (P Value video) • ANOVA An ANOVA (Analysis of Variance), sometimes called an F test, is closely related to the t test. The major difference is that, where the t test measures the difference between the means of two groups, an ANOVA tests the difference between the means of two or more groups.

  11. Video notes • 1) P value refers to the likelihood your research results were by chance. It usually has to be below .05 for the differences you found to have any real meaning. • 2) F critical is the value that must be "crossed" in order for p value to be significant. • 3) If F critical is passed, then the p value gets glory (so to speak) because it is now significant. • 4) Bonferroni is a conservative stats adjustment used when making many comparisons between effects. it makes it more likely that p will be non-significant and that F critical will not "have her threshold" crossed.

  12. Condition 2: Sleep Deprived Condition 1: Slept Well Time Test memory Test memory again Within / Between Group Comparison • Two ways of comparing people: • Within groups (everybody does all conditions) • e.g. ‘before and after’ study

  13. Group 2: Females Group 1: Males Test visual abilities Test visual abilities Within / Between Group Comparison • Between groups (different people do each condition) • e.g. ‘males vs females’ study

  14. Summary • Descriptive statistics give a summary of the data. • Statistical dispersion describes the spread of the data. • Many attributes are normally distributed. • Inferential statistics allow us to test hypotheses using this assumption. • Studies need to be carefully designed to make this meaningful.

  15. Essential Question • 1-5 How do psychologists draw appropriate conclusions about behavior from research?

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