1. THE ROLE OF STATISTICS IN RESEARCH

2. Reading APPENDIX A: Statistics pp. 673-677

3. Definition A field of mathematics dealing with the analysis, interpretation, and presentation of masses of numerical data (Merriam-Webster’s Collegiate Dictionary). There are three kind of lies: “Lies, damned lies, and statistics.”

4. Types of Statistics Descriptive Statistics - simple quantitative summaries of the data - describe the basic features of the data in a study Inferential Statistics - used for testing hypotheses. - complex calculations based on probabilities - help reach conclusions about the data. eg did these 2 samples come from the same population ?

5. We’ll focus on Descriptive Statistics

6. A summary of the frequency of individual scores on one variable i.e., How many people got each score Nominal (categories) vs. Score (ordered) variables Smooth curve vs. histogram Frequency Distributions

7. Histogram of of Psych 100 grades

8. 1.SHAPE: flat, normal, skewed etc 2.CENTRAL TENDENCY: where is the "center" of a distribution? -Mean, median, or mode 3.VARIABILITY: how different are the scores from each other? Three Aspects of Distributions

9. 1. Shapes of Distributions The normal distribution (bell-curve) Flat distribution

10. More Shapes Skewed distributions Leans to right Leans to left

11. 2. Measures of Central Tendency MEAN - average of the scores - (Sum of scores)/Number of people MEDIAN - the middle score when ordered MODE - most frequent score

12. Shape is important too Multi-modal distributions 0 2

13. They sometimes disagree Mo 50, 60, 60, 99, 100 (Mean = 74) Jo 50, 60, 70, 70, 90 (Mean = 68) Flo 50, 50, 75, 76, 77 (Mean = 66)

14. 2. Measures of Variability RANGE: - the highest value minus the lowest value STANDARD DEVIATION: - the average difference among the scores

15. e.g. of Variability Two normal distributions -same mean --differ in variability

16. Normal Curve 170 190 150 130 210 Mean 68% 3% 13%

17. Standard Normal Curve (in terms of standard deviations) 0 +1 - 1 - 2 +2 Mean 68%

18. Measuring associations between variables: The main goal of science

19. Plotting Associations

20. CORRELATION COEFFICIENT (r) -quantifies associations -plug your numbers into the correlation formula (see book) -yields a number between -1 and +1

21. Perfect positive correlation r = + 1.00

22. Perfect negative r = - 1.00

23. r = +.85

24. Zero correlation r = 0

25. SUMMARY One variable: Frequency distributions measures of central tendency measures of variability Two variables: correlations