1. Introductory Statistics
Course Summation
Introductory Statistics

2. Introduction to Statistics
Graphical Descriptions of Data
Numerical Descriptions of Data
Discrete Probability Distributions
Continuous Probability Distributions
The Central Limit Theorem …

3. …
Confidence Intervals
Confidence Intervals for Two Samples
Hypothesis Testing
Hypothesis Testing for Two+ Populations
Regression, Inference, Model Building

4. Introduction to Statistics

5. Introduction to Statistics
Definition of Statistic and Statistics
Population
Variable
Data
Census
Parameter
Sample

6. Data Classification Qualitative (Categorical) Quantitative (Numeric)
Nominal
Ordinal
Quantitative (Numeric)
Interval
Ratio
Continuous
Discrete

7. Sampling Methods Random Sampling Stratified Sampling Cluster Sampling
Systematic Sampling
Convenience Sampling
Stopping Rules
Replacement
Representative

8. Graphical Descriptions

9. Graphical Displays Pie Charts Bar Charts Side-by-Side Bar Charts
Stacked Bar Charts
Histogram
Box-and-Whiskers Plot
Stem-and-Leaf Plots

10. Numerical Descriptions

11. Measures of Center
Mode
Mean
Median
Outlier

12. Measures of Dispersion (Spread)
Range
Variance
Standard Deviation
Interquartile Range
Coefficient of Variation
Empirical Rule

13. Other Measures Percentile (Quantile) Quartile Five-Number Summary
Standard Score (z-score)

14. Discrete Distributions

15. Discrete Random Variables
Properties of a Discrete RV
Sample Space
Probability
Expected Value
Variance, Standard Deviation

16. Binomial Random Variables
Five Requirements
Sample Space
Probability mass function
Parameters
Expected value
Variance

17. Poisson Random Variables
Requirements
Sample Space
Probability mass function
Parameters
Expected value
Variance

18. Hypergeometric Random Variable
Requirements
Properties

19. Continuous Distributions

20. Uniform Distribution Parameters Sample Space Expected Value Variance
Shape
Probabilities (CDF)
Quantiles

21. Exponential Distribution
Parameter
Sample Space
Expected Value
Variance
Shape
Probabilities (CDF)
Quantiles

22. Normal Distribution Parameters Sample Space Expected Value Variance
Shape
Probabilities (CDF)
Quantiles

23. Central Limit Theorem

24. The Central Limit Theorem
Statements
Effects
Uses

25. Confidence Intervals, I

26. Estimating Population Mean ( unknown)
Meaning of Confidence Interval
Calculation of CI
Margin of Error, E
Effects of population variance on E
Effects of sample size on E
Effects of  on E

27. Estimating Population Proportion
Meaning of Confidence Interval
Calculation of CI
Margin of Error, E
Effects of population variance on E
Effects of sample size on E
Effects of  on E

28. Estimating Population Variance
Meaning of Confidence Interval
Calculation of CI
Margin of Error, E
Effects of population variance on E
Effects of sample size on E
Effects of  on E

29. Confidence Intervals, II

30. Estimating Difference of Population Means
Meaning of Confidence Interval
Calculation of CI
Margin of Error, E
Effects of population variance on E
Effects of sample size on E
Effects of  on E

31. Estimating Difference of Population Proportions
Meaning of Confidence Interval
Calculation of CI
Margin of Error, E
Effects of population variance on E
Effects of sample size on E
Effects of  on E

32. Estimating Ratio of Population Variances
Meaning of Confidence Interval
Calculation of CI
Margin of Error, E
Effects of population variance on E
Effects of sample size on E
Effects of  on E

33. Hypothesis Testing, I

34. Fundamentals of Hypothesis Testing
Research hypothesis, HR
Null hypothesis, H0
Alternative hypothesis, HA
Test statistic
Statistically significant
Practically significant
Level of significance, 
p-value

35. Hypothesis Testing for One 
Test statistic
Rejection region
p-value
Assumptions of t-test
Checking assumptions
Wilcoxon test
Assumption of Wilcoxon test
Non-parametric Bootstrap

36. Hypothesis Testing for One p
Test statistic
Rejection region
p-value
Assumptions of z-test for proportions
Assumptions of Binomial test

37. Hypothesis Testing for One 2
Test statistic
Rejection region
p-value
Assumptions of Chi-square test

38. Hypothesis Testing, II

39. Hypothesis Testing for Difference in 
Test statistic
Rejection region
p-value
Assumptions of two-sample t-test
Checking assumptions
Mann-Whitney test

40. Hypothesis Testing for Difference in p
Test statistic
Rejection region
p-value
Assumption of proportions test

41. Hypothesis Testing for Ratio of Two 2
Test statistic
Rejection region
p-value
Assumptions of F test for variances

42. Hypothesis Testing, III

43. Hypothesis Testing for Multiple Means (11.6)
Analysis of Variance (ANOVA)
Interpreting p-value
Assumptions of ANOVA
Testing assumptions of ANOVA
Alternative to ANOVA if assumptions not met

44. Hypothesis Testing for Goodness-of-Fit (10.6)
Test statistic
Rejection region
p-value
Assumptions of Chi-square GoF test

45. Hypothesis Testing for Independence (10.7)
Test statistic
Rejection region
p-value
Assumptions of Chi-square test of Independence

46. Hypothesis Testing for Independence (12)
Correlation Test
Regression Test
Regression Line
Slope and Intercept
Interpreting p-value
Interpreting confidence interval for slope
Interpreting prediction interval for next observation