Mathematics for Computer Science
Course Code BCS301
CIE Marks 50
Teaching Hours/Week (L: T:P: S) 3:2:0:0
SEE Marks 50
Total Hours of Pedagogy 40 hours Theory + 20 Hours
Tutorial Total Marks 100
Credits 04
Exam Hours 3
Examination type (SEE)
Module-1:
Probability Distributions Probability Distributions: Review of basic probability theory. Random variables (discrete and continuous), probability mass and density functions. Mathematical expectation, mean and variance. Binomial, Poisson and normal distributions- problems (derivations for mean and standard deviation for Binomial and Poisson distributions only)-Illustrative examples. Exponential distribution. (12 Hours) (RBT Levels: L1, L2 and L3) Pedagogy Chalk and Board, Problem-based learning
Click here to download module-1
Module-2:
Joint probability distribution & Markov Chain 15.09.2023 14.09.2023 Annexure-II 2 2 Joint probability distribution: Joint Probability distribution for two discrete random variables, expectation, covariance and correlation. Markov Chain: Introduction to Stochastic Process, Probability Vectors, Stochastic matrices, Regular stochastic matrices, Markov chains, Higher transition probabilities, Stationary distribution of Regular Markov chains and absorbing states. (12 Hours) (RBT Levels: L1, L2 and L3) Pedagogy Chalk and Board, Problem-based learning
Click here to download module-2
Module-3:
Statistical Inference 1 Introduction, sampling distribution, standard error, testing of hypothesis, levels of significance, test of significances, confidence limits, simple sampling of attributes, test of significance for large samples, comparison of large samples. (12 Hours) (RBT Levels: L1, L2 and L3) Pedagogy Chalk and Board, Problem-based learning
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Module-4:
Statistical Inference 2 Sampling variables, central limit theorem and confidences limit for unknown mean. Test of Significance for means of two small samples, students ‘t’ distribution, Chi-square distribution as a test of goodness of fit. F-Distribution. (12 Hours) (RBT Levels: L1, L2 and L3) Pedagogy Chalk and Board, Problem-based learning
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Module-5:
Design of Experiments & ANOVA Principles of experimentation in design, Analysis of completely randomized design, randomized block design. The ANOVA Technique, Basic Principle of ANOVA, One-way ANOVA, Two-way ANOVA, Latin-square Design, and Analysis of Co-Variance. (12 Hours) (RBT Levels: L1, L2 and L3)
Click here to download module-5
Important Links:
1. Click here to download Model Question Paper-1
2. Click here to download Model Question Paper-2
3. Click here to download Model Question Paper with Solutions
Suggested Learning Resources: Textbooks:
1. Ronald E. Walpole, Raymond H Myers, Sharon L Myers & Keying Ye “Probability & Statistics for Engineers & Scientists”, Pearson Education, 9 th edition, 2017.
2. Peter Bruce, Andrew Bruce & Peter Gedeck “Practical Statistics for Data Scientists” O’Reilly Media, Inc., 2nd edition 2020.
Reference Books:
1. Erwin Kreyszig, “Advanced Engineering Mathematics”, John Wiley & Sons, 9 th Edition, 2006.
2. B. S. Grewal “Higher Engineering Mathematics”, Khanna publishers, 44 th Ed., 2021.
3. G Haribaskaran “Probability, Queuing Theory & Reliability Engineering”, Laxmi Publication, Latest Edition, 2006
4. Irwin Miller & Marylees Miller, John E. Freund’s “Mathematical Statistics with Applications” Pearson. Dorling Kindersley Pvt. Ltd. India, 8 th edition, 2014.
5. S C Gupta and V K Kapoor, “Fundamentals of Mathematical Statistics”, S Chand and Company, Latest edition.
6. Robert V. Hogg, Joseph W. McKean & Allen T. Craig. “Introduction to Mathematical Statistics”, Pearson Education 7 th edition, 2013.
7. Jim Pitman. Probability, Springer-Verlag, 1993.
8. Sheldon M. Ross, “Introduction to Probability Models” 11 th edition. Elsevier, 2014.
9. A. M. Yaglom and I. M. Yaglom, “Probability and Information”. D. Reidel Publishing Company. Distributed by Hindustan Publishing Corporation (India) Delhi, 1983.
10. P. G. Hoel, S. C. Port and C. J. Stone, “Introduction to Probability Theory”, Universal Book Stall, (Reprint), 2003.
11. S. Ross, “A First Course in Probability”, Pearson Education India, 6 th Ed., 2002.
12. W. Feller, “An Introduction to Probability Theory and its Applications”, Vol. 1, Wiley, 3rd 15.09.2023 14.09.2023 Annexure-II 4 4 Ed., 1968.
13. N.P. Bali and Manish Goyal, A Textbook of Engineering Mathematics, Laxmi Publications, Reprint, 2010. 14. Veerarajan T, Engineering Mathematics (for semester III), Tata McGraw-Hill, New Delhi, 2010
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