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The course has been about statistics in psychology

For this extra credit, you need to write a 300–500-word short essay that discusses what you think is the most important thing you’ve learned from this class this semester. Define and describe what you think is the most important topic and then explain why you think it is the most important topic.

400 words

syllabus and course text attached

1. Distinguish among, interpret, and calculate the mean, median, and mode
2. Define, explain, interpret and calculate variance and standard deviation
3. Apply an understanding of central tendency and variability to interpreting and conducting statistical analysis
4. Define, interpret and calculate a z-score
5. Apply an understanding of mean and standard deviation to z-scores
6. Describe the nature and characteristics of normal distributions of data
7. Combine an understanding of normal curves and z-scores
8. Interpret and apply probability rules
9. Distinguish between the properties of samples and populations
10. Apply an understanding of z-scores, samples, probability, normal and curves to interpreting and conducting statistical analysis
11. Explain the core logic of hypothesis testing
12. Discuss the logic of null and research hypotheses
13. Distinguish between one-tailed and two-tailed hypothesis tests
14. Demonstrate an understating of and ability to interpret hypothesis tests in research articles
15. Apply an understanding of z-scores, samples, probability, normal and curves to interpreting and conducting statistical analysis
16. Describe the distribution of means
17. Distinguish among the three kinds of distributions
18. Explain and conduct the Z-test
19. Estimate the population mean when it is not known
20. Demonstrate an understanding of confidence intervals and standard error
21. Demonstrate an understating of and ability to interpret hypothesis tests and confidence intervals in research articles
22. Apply an understanding of hypothesis testing and confidence intervals to interpreting and conducting statistical analysis
23. Distinguish and explain Type I and Type II errors
24. Define and calculate effect size
25. Explain statistical power and what impacts it
26. Apply statistical power in the context of planning a study
27. Demonstrate an understating of and ability to interpret statistical significance, effect size, and statistical power in research articles
28. Apply an understanding of statistical significance, effect size, and statistical power to interpreting and conducting statistical analysis
29. Define degrees of freedom
30. Explain, conduct, and interpret a t-test for single samples
31. Explain, conduct and interpret a t-test for dependent samples
32. Demonstrate an understating of and ability to interpret t-tests in research articles
33. Apply an understanding of t-tests to interpreting and conducting statistical analysis
34. Describe the distribution of differences between means
35. Explain, conduct, and interpret a t-test for independent means
36. Apply statistical power and effect size to two-sample t-tests
37. Demonstrate an understating of and ability to interpret two sample t-tests in research articles
38. Apply an understanding of two sample t-tests to interpreting and conducting statistical analysis
39. Explain the basic logic of an ANOVA
40. Define within- and between-group variance and the F ratio
41. Explain, conduct, and interpret an ANOVA
42. Explain, conduct, and interpret post-hoc comparisons
43. Demonstrate an understating of and ability to interpret ANOVA tests in research articles
44. Apply an understanding of ANOVAs to interpreting and conducting statistical analysis
45. Explain the basic logic of a factorial ANOVA
46. Define factorial research designs
47. Recognize and interpret interaction effects
48. Demonstrate an understating of and ability to interpret factorial ANOVA tests in research articles
49. Apply an understanding of factorial ANOVAs to interpreting and conducting statistical analysis
50. Interpret correlation graphs
51. Distinguish correlation and causality
52. Describe and discuss patterns of correlation
53. Explain, conduct, and interpret a correlation coefficient
54. Demonstrate an understating of and ability to interpret correlation tests in research articles
55. Apply an understanding of correlation to interpreting and conducting statistical analysis
56. Define and discuss predictor and criterion variables
57. Explain the linear prediction rule
58. Explain, compute, and interpret a regression line
59. Discuss the basic logic of multiple regression
60. Demonstrate an understating of and ability to interpret predictive tests in research articles
61. Apply an understanding of prediction to interpreting and conducting statistical analysis
62. Explain the basic logic of chi square tests for goodness of fit and for independence
63. Explain, compute, and interpret a chi square test for goodness of fite and a chi square test for independence
64. Demonstrate an understating of and ability to interpret chi square tests in research articles
65. Apply an understanding of chi square tests to interpreting and conducting statistical analysis
66. Distinguish between parametric and non-parametric tests
67. Explain, conduct, and interpret rank-order tests
68. Compare different non-parametric tests
69. Demonstrate an understating of and ability to interpret non-parametric tests in research articles
70. Explain the basic logic of data transformation
71. Apply an understanding of non-parametric tests to interpreting and conducting statistical analysis

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