JNTUH CSE-AIML MA313BS: MATHEMATICAL AND STATISTICAL FOUNDATIONS SYLLABUS

Prerequisites: Mathematics courses of first year of study.
Course Objectives:
 The Number Theory basic concepts useful for cryptography etc
 The theory of Probability, and probability distributions of single and multiple random variables
 The sampling theory and testing of hypothesis and making inferences
 Stochastic process and Markov chains.
Course Outcomes: After learning the contents of this course, the student must be able to
 Apply the number theory concepts to cryptography domain
 Apply the concepts of probability and distributions to some case studies
 Correlate the material of one unit to the material in other units
 Resolve the potential misconceptions and hazards in each topic of study.
UNIT – I
Greatest Common Divisors and Prime Factorization: Greatest common divisors, The Euclidean algorithm, The fundamental theorem of arithmetic, Factorization of integers and the Fermat numbers Congruences: Introduction to congruences, Linear congruences, The Chinese remainder theorem, Systems of linear congruences
UNIT – II
Simple Linear Regression and Correlation: Introduction to Linear Regression, The Simple Linear Regression Model, Least Squares and the Fitted Model, Properties of the Least Squares Estimators,Inferences Concerning the Regression Coefficients, Prediction, Simple Linear Regression Case Study Random Variables and Probability Distributions: Concept of a Random Variable, Discrete Probability Distributions, Continuous Probability Distributions, Statistical Independence.Discrete Probability Distributions: Binomial Distribution, Poisson distribution.
UNIT – III
Continuous Probability Distributions: Normal Distribution, Areas under the Normal Curve,Applications of the Normal Distribution, Normal Approximation to the Binomial Fundamental Sampling Distributions: Random Sampling, Sampling Distributions, Sampling Distribution of Means and the Central Limit Theorem, Sampling Distribution of S2, t–Distribution, FDistribution.
UNIT – IV
Estimation & Tests of Hypotheses: Introduction, Statistical Inference, Classical Methods of Estimation. Estimating the Mean, Standard Error of a Point Estimate, Prediction Intervals, Tolerance Limits, Estimating the Variance, Estimating a Proportion for single mean , Difference between Two Means, between Two Proportions for Two Samples and Maximum Likelihood Estimation.
UNIT – V
Stochastic Processes and Markov Chains: Introduction to Stochastic processes- Markov process.Transition Probability, Transition Probability Matrix, First order and Higher order Markov process,nstep transition probabilities, Markov chain, Steady state condition, Markov analysis

TEXT BOOKS:

1. Kenneth H. Rosen, Elementary number theory & its applications, sixth edition, Addison Wesley, ISBN 978 0-321-50031-1
2. Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Probability & Statistics for Engineers & Scientists, 9th Ed. Pearson Publishers.
3. S. D. Sharma, Operations Research, Kedarnath and Ramnath Publishers, Meerut, Delhi
REFERENCE BOOK:
1. S C Gupta and V K Kapoor, Fundamentals of Mathematical statistics, Khanna publications
2. T.T. Soong, Fundamentals of Probability And Statistics For Engineers, John Wiley & Sons Ltd, 2004.
3. Sheldon M Ross, Probability and statistics for Engineers and scientists, Academic Press.

CSE-AIML