BSc CSIT · Semester III
Statistics II syllabus
Official TU syllabus for Statistics II (STA215): 6 units, 52 topics, 3 credit hours. Every unit links to its notes and solved questions.
1
Sampling Distribution and Estimation
6h · 12 Q- Sampling distribution
- sampling distribution of mean and proportion
- Central Limit Theorem
- Concept of inferential Statistics
- Estimation
- Methods of estimation
- Properties of good estimator
- Determination of sample size
- Relationship of sample size with desired level of error
- Problems and illustrative examples related to computer Science and IT
2
Testing of hypothesis
8h · 12 Q- Types of statistical hypotheses
- Power of the test, concept of p-value and use of p-value in decision making
- steps used in testing of hypothesis
- one sample tests for mean of normal population (for known and unknown variance)
- test for single proportion
- test for difference between two means and two proportions
- paired sample t-test
- Linkage between confidence interval and testing of hypothesis
- Problems and illustrative examples related to computer Science and IT
3
Non parametric test
8h · 15 Q- Parametric vs. non-parametric test
- Needs of applying non-parametric tests
- One-sample test: Run test, Binomial test, Kolmogorov–Smirnov test
- Two independent sample test: Median test, Kolmogorov-Smirnov test, Wilcoxon Mann Whitney test, Chi-square test
- Paired-sample test: Wilcoxon signed rank test
- Cochran's Q test
- Friedman two way analysis of variance test
- Kruskal Wallis test
- Problems and illustrative examples related to computer Science and IT
4
Multiple correlation and regression
6h · 13 Q- Multiple and partial correlation
- Introduction of multiple linear regression
- Hypothesis testing of multiple regression
- Test of significance of regression
- Test of individual regression coefficient
- Model adequacy tests
- Problems and illustrative examples related to computer Science and IT
5
Design of experiment
10h · 10 Q- Experimental design
- Basic principles of experimental designs
- Completely Randomized Design (CRD)
- Randomized Block Design (RBD)
- ANOVA table
- Efficiency of RBD relative to CRD
- Estimations of missing value (one observation only)
- Advantages and disadvantages
- Latin Square Design (LSD): Statistical analysis of m × m LSD for one observation per experimental unit, ANOVA table, Estimation of missing value in LSD (one observation only), Efficiency of LSD relative to RBD, Advantage and disadvantages
- Problems and illustrative examples related to computer Science and IT
6
Stochastic Process
7h · 9 Q- Definition and classification
- Markov Process: Markov chain, Matrix approach, Steady-State distribution
- Counting process: Binomial process, Poisson process
- Simulation of stochastic process
- Queuing system: Main component of queuing system, Little's law
- Bernoulli single server queuing process: system with limited capacity
- M/M/1 system: Evaluating the system performance
Textbooks and references
- Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, & Keying Ye(2012). Probability & Statistics for Engineers & Scientists. 9th Ed., Printice Hall
- Michael Baron (2013). Probability and Statistics for Computer Scientists. 2nd Ed., CRC Press, Taylor & Francis Group, A Chapman & Hall Book
- Douglas C. Montgomery & George C. Runger (2003). Applied Statistics and Probability for Engineers. 3rd Ed., John Willey and Sons, Inc.
- Sidney Siegel, & N. John Castellan, Jr. Nonparametric Statistics for the Behavioral Sciences, 2nd Ed., McGraw Hill International Editions.
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