MA41009: Probability And Statistics

MA41009
Course name	Probability and Statistics
Offered by	Mathematics
Credits	3
L-T-P	3-0-0
Previous Year Grade Distribution
2 7 15 9 11 3 1 EX A B C D P F
Semester	{{{semester}}}

Syllabus

Syllabus mentioned in ERP

Pre requisite: void Probability: Classical, relative frequency and axiomatic definitions of probability, addition rule and conditional probability, multiplication rule, total probability, Bayes’ Theorem and independence. Random Variables: Discrete, continuous and mixed random variables, probability mass, probability density and cumulative distribution functions, mathematical expectation, moments, moment generating function, Chebyshev’s inequality. Special Distributions: Discrete uniform, binomial, geometric, negative binomial, hypergeometric, Poisson, uniform, exponential, gamma, normal, beta, lognormal, Weibull, Laplace, Cauchy, Pareto distributions. Functions of a Random Variable. Joint Distributions: Joint, marginal and conditional distributions, product moments, correlation, independence of random variables, bivariate normal distribution, simple, multiple and partial correlation, regression. Sampling Distributions: Law of large numbers, Central Limit Theorem, distributions of the sample mean and the sample variance for a normal population, Chi-Square, t and F distributions. Estimation: The method of moments and the method of maximum likelihood estimation, properties of best estimates, confidence intervals for the mean(s) and variance(s) of normal populations. Testing of Hypotheses: Null and alternative hypotheses, the critical and acceptance regions, two types of error, power of the test, the most powerful test and Neyman-Pearson Fundamental Lemma, standard tests for one and two sample problems for normal populations.

Time Table

Day	8:00-8:55 am	9:00-9:55 am	10:00-10:55 am	11:00-11:55 am	12:00-12:55 pm		2:00-2:55 pm	3:00-3:55 pm	4:00-4:55 pm	5:00-5:55 pm
Monday	NC233	NC233
Tuesday					NC233
Wednesday
Thursday
Friday