This course will help students gain an understanding of elementary probability theory and how to apply it to analyze statistical problems. It also provides an undergraduate student who is preparing for gradu-ate study in statistical concepts to include measurements of location and dispersion, probability, proba-bility distributions, sampling, estimation, hypothesis testing, regression, and correlation analysis.
Bachelor of Computer Science - 144 CRs
Michael J. Crawley, Statistics: An Introduction using R, Wiley
content serial | Description |
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1 | Sampling and probability (Random sampling- Probability calculations and combinatory) Discrete event simulation |
2 | Distributions (Discrete- Continuous) |
3 | Statistics and graphical display for single data (Histograms- Q–Q plots- Boxplots) |
4 | Statistics and graphical display for grouped data (Histograms- boxplots- Strip charts) |
5 | Generating tables and Marginal tables and relative frequency |
6 | Graphical display for Tables (Bar plots- Dot charts- Pie charts) |
7 | 7th Week Exam + Correlation (Pearson –Spearman) |
8 | Simple linear regression |
9 | Residuals and fitted values |
10 | Prediction and confidence bands |
11 | Comparison of variances |
12 | 12th Week Exam + One-sample T- test |
13 | Two-sample T-test |
14 | Wilcoxon signed-rank test + Paired sample test (T-test, Wilcoxon test) |
15 | Revision |
16 | Final Exam |
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