Tribhuvan University | Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Statistics I
Course Contents (Theory)
Unit 1. Introduction
4 Hrs
Basic concept of statistics; Application of Statistics in the field of Computer Science & Information technology; Scales of measurement; Variables; Types of Data; Notion of a statistical population.
Unit 2. Descriptive Statistics
6 Hrs
Measures of central tendency; Measures of dispersion; Measures of skewness; Measures of kurtosis; Moments; Steam and leaf display; five number summary; box plot. Problems and illustrative examples related to computer Science and IT.
Unit 3. Introduction to Probability
8 Hrs
Concepts of probability; Definitions of probability; Laws of probability; Bayes theorem; prior and posterior probabilities. Problems and illustrative examples related to computer Science and IT.
Unit 4. Sampling
3 Hrs
Definitions of population; sample survey vs. census survey; sampling error and non sampling error; Types of sampling.
Unit 5. Random Variables and Mathematical Expectation
5 Hrs
Concept of a random variable; Types of random variables; Probability distribution of a random variable; Mathematical expectation of a random variable; Addition and multiplicative theorems of expectation.
Unit 6. Probability Distributions
12 Hrs
Probability distribution function, Joint probability distribution of two random variables; Discrete distributions: Bernoulli trial, Binomial and Poisson distributions; Continuous distribution: Normal distributions; Standardization of normal distribution; Normal distribution as an approximation of Binomial and Poisson distribution; Exponential, Gamma distribution.
Unit 7. Correlation and Linear Regression
7 Hrs
Bivariate data; Bivariate frequency distribution; Correlation between two variables; Karl Pearson's coefficient of correlation(r); Spearman's rank correlation; Regression Analysis: Fitting of lines of regression by the least squares method; coefficient of determination.
Laboratory Works
Practical Overview
Lab Work
The laboratory work includes using any statistical software such as Microsoft Excel, SPSS, STATA etc. Practical problems cover:
- Computation of measures of central tendency and dispersion.
- Measures of skewness and kurtosis using method of moments and Box plots.
- Fitting of lines of regression and computation of correlation coefficients.
- Conditional probability and Bayes theorem.
- Fitting probability distributions (Binomial, Poisson, and Normal) to real data.
Text Books
- Michael Baron: "Probability and Statistics for Computer Scientists", 2nd Ed., CRC Press.
- Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, & Keying Ye: "Probability & Statistics for Engineers & Scientists", 9th Ed., Printice Hall.
Reference Books
- Douglas C. Montgomery & George C. Ranger: "Applied Statistics and Probability for Engineers", 3rd Ed., John Willey and Sons, Inc.
- Richard A. Johnson: "Probability and Statistics for Engineers", 6th Ed., Pearson Education, India.
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