The course is intended to give basic knowledge of the theory and methods of statistical inference, i.e., how to use observed data to draw conclusions about phenomena influenced by random factors. By the end of the course, the student should be able to: use a probability model to describe and analyses observed data and draw conclusions concerning interesting parameters; understand the principles of statistical inference; explore the relationships between two or several variables and use suitable software (R) for certain types of statistical analyses.
IS -132 CRs
Michael J. Crawley, Statistics: An Introduction using R, Wiley
| content serial | Description |
|---|
| 1 | Sampling and probability (Random sampling- Probability calculations and combinatory) |
| 2 | Distributions (Discrete- Continuous) |
| 3 | Introduction to R |
| 4 | Statistics and graphical display for single data (Histograms- Q-Q plots- Boxplots) |
| 5 | Statistics and graphical display for grouped data (Histograms- boxplots- Stripcharts) |
| 6 | Generating tables and Marginal tables and relative frequency |
| 7 | Correlation |
| 8 | Correlation (Pearson -Spearman) and Simple linear regression |
| 9 | Prediction and confidence bands |
| 10 | One-sample T- test |
| 11 | Two-sample T-test |
| 12 | The paired T-test |
| 13 | The paired T-test |
| 14 | Wilcoxon signed-rank test |
| 15 | Chi-square test - Goodness of fit |
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