1. Data Measurement. Descriptive Statistics, Tabular and Graphical Approaches.
2. Principle of Inference. Sampling and Sampling Distributions.
3. Estimation. Properties of Point Estimators. Interval Estimation.
4. Confidence Interval for the Mean. Confidence Interval for a Proportion. Confidence Interval and Sample Size.
5. Hypothesis Testing: Inference on a Single Population, Parametric and Nonparametric Methods.
6. Hypothesis Testing: Inference for Two Populations Using Independent Samples, Parametric and Nonparametric Methods.
7. Hypothesis Testing: Inference for Two Paired Samples, Parametric and Nonparametric Methods.
8. Analysis of Variance. Multiple Comparison Procedures. The Kruskal-Wallis Test, the Friedman Test.
9. Regression and Correlation Methods. Fitting Regression Lines – the Method of Least Squares. Inference About Parameters from Regression Lines.
10. Residual Analysis. The Correlation Coefficient. Statistical Inference for Correlation Coefficients.
11. Multiple Regression. The Multiple Regression Model and Its Assumptions.
12. Analysis of Categorial Data. The Goodness-of-Fit Test. Contingency Tables. Fisher’s Exact Test.
2. Principle of Inference. Sampling and Sampling Distributions.
3. Estimation. Properties of Point Estimators. Interval Estimation.
4. Confidence Interval for the Mean. Confidence Interval for a Proportion. Confidence Interval and Sample Size.
5. Hypothesis Testing: Inference on a Single Population, Parametric and Nonparametric Methods.
6. Hypothesis Testing: Inference for Two Populations Using Independent Samples, Parametric and Nonparametric Methods.
7. Hypothesis Testing: Inference for Two Paired Samples, Parametric and Nonparametric Methods.
8. Analysis of Variance. Multiple Comparison Procedures. The Kruskal-Wallis Test, the Friedman Test.
9. Regression and Correlation Methods. Fitting Regression Lines – the Method of Least Squares. Inference About Parameters from Regression Lines.
10. Residual Analysis. The Correlation Coefficient. Statistical Inference for Correlation Coefficients.
11. Multiple Regression. The Multiple Regression Model and Its Assumptions.
12. Analysis of Categorial Data. The Goodness-of-Fit Test. Contingency Tables. Fisher’s Exact Test.