The document provides an overview of quantitative data analysis and various statistical concepts including the normal distribution, z-tests, confidence intervals, and t-tests. It discusses how the normal distribution was developed by de Moivre and Gauss. It then explains the key properties of the normal distribution and how it can be used to describe many natural phenomena. Examples are provided to illustrate how to calculate and interpret confidence intervals and choose the appropriate statistical test.

1. Quantitative Data Analysis: Statistics – Part 2

3. The Normal Distribution

9. The Normal Distribution

11. The Normal Distribution

12. The Normal Distribution

14. Density Curves: Properties

17. Same Mean, Different Standard Deviation 10 1

18. Different Mean, Different Standard Deviation 10 1

19. Different Mean, Same Standard Deviation 10 1

30. The Normal Distribution

34. So what? Before = 6.4 After = 9.2 0 10

35. So what? Is this a significant difference? Before = 6.4 After = 9.2 10 0

36. So what? or is it more likely a sampling variation? Before = 6.4 After = 9.2 10 0

37. So what? Before = 6.4 After = 9.2 10 0

38. So what? Before = 6.4 After = 9.2 10 0

39. So what? Before = 6.4 After = 9.2 How many standard devaitions from the mean is this? 10 0

40. So what? Before = 6.4 After = 9.2 How many standard devaitions from the mean is this? 10 0 and is it statistically significant?

41. So what? Before = 6.4 After = 9.2 10 0 σ σ σ

47. Trends in Statistical Tests used in Research Papers Historically Currently Testing Estimation Hypothesis Tests Quoting P-Values Confidence Intervals Results in: Accept/Reject Results in: p-Value Results in: Approx. Mean

49. Confidence Intervals

56. Example 1

59. Example 2

64. T-Tests

76. Choosing the right test

77. Choosing a statistical test http://www.graphpad.com/www/Book/Choose.htm

78. Choosing a statistical test http://www.graphpad.com/www/Book/Choose.htm