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M3 notes Mathematics 2022 scheme                            VTU University                            3rd SEM                            Computer science and Engineerings notes,2022 scheme Notes, study
                            materials, question
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M3 notes Mathematics 2022 scheme VTU University 3rd SEM Computer science and Engineerings|BCS301 notes

BCS301-M3 notes Mathematics 2022 scheme VTU University notes on 3rd SEM Computer science and Engineerings notes 2022 scheme notes 2024 VTU University BCS301 notes, study materials notes, and previous year question paper on easenotes 2024

M3 notes Mathematics 2022 scheme VTU University 3rd SEM Computer science and Engineerings notes, We are offering the best quality online 3rd SEM Computer science and Engineerings VTU University notes to help you learn, and have a better knowledge and also we are offering 2022 scheme Notes, study materials, question paper

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Scheme & Syllabus Copy of M3 notes Mathematics 2022 scheme VTU University 3rd SEM Computer science and Engineerings

Chapters of M3 VTU notes 2022 scheme

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

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.

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

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.

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.