1. Recapitulation! Statistics 515

2. What Have We Covered? Elements Variables and Populations Parameters Samples Sample Statistics Population Distributions

3. Descriptive Statistics Tabular presentations Graphical Presentations Comparative Graphical Presentations Numerical Summary Measures Measures of Central Tendency Measures of Variation Measures of Relationships

4. Basic Probability Experiments Meaning of Probability Operations with Probabilities Conditional Probability Combining Probabilities Bayes Theorem

5. Random Variables and Distributions ProbabilityDistributions Binomial and Normal; Others Population Means,Variances, Std. Devs. Sampling and Sampling Distributions Basic Ideas Mean of a Statistic Standard Error of a Statistic Central Limit Theorem

6. Statistical Inference Confidence Intervals for Parameters Interpretations Interplay among sample size, accuracy and precision Sample Size Determination Testing Hypothesis of Parameters Type I and Type II Errors Mechanics of Testing

7. Specific CIs and Tests For Means and Proportions For Variances (Chi-Square Test) Z-Based and T-Based Procedures For One Population (Z- and T-Based) For Two-Populations (Z- and T-Based) For More Than Two Populations (F-Test; ANOVA) T-Distribution Chi-Square Distribution F-Distribution

8. Studying Relationships Simple Linear Regression Model and Assumptions Least-Squares Principle Best-Fitting Line Test for significance of predictor Predicting the Mean Response at a Given Value of Predictor Predicting the Value of Response at a Given Value of Predictor

9. A Final Note! The methods of statistics may only be the second best for determining the truth about population parameters, but then they are the only ones that are practically implementable when you factor in cost, time, and resource constraints!