Syllabus

Modules:
1. Sampling Theory: Principal steps in a sample survey methods of sampling: random-simple and stratified random sampling, types of SRS and STRS, properties of random samples nonrandom sampling, sampling vs. non-sampling errors.
2. Probability: Concepts of Sample Space and Events, Probability of an Event, Addition and Multiplication Theorems Conditional Probability and Independence of Events Bayes theorem.
3. Probability Distributions: Concept of a Random Variable, Discrete and Continuous Random Variable, Probability Density Function, Mathematical Expectation and Its Properties, Sampling Distribution of Sample Mean and Sample Variance.
4. Theoretical Distributions: Binomial distribution- its properties, Poission distribution and its properties, poission distribution as a limiting case of binomial distribution, normal distributions properties, normal distribution as a limiting case of binomial distribution, Central Limit Theorem.
5. Estimation: parameter and statistic, estimates and estimators, point estimators and its properties (small sample and asymptotic properties), confidence intervals for population parameters.
6. Hypothesis Testing: Defining statistical hypotheses null vs alternative hypotheses, Type I and Type II error, power of a test the concept of degrees of freedom testing hypotheses related to population parameters based on Z, t, chi-square and F-tests.

To understand the fundamentals of Inferential Statistics.

How to apply the knowledge domain of statistics in Industry, Economics, Agriculture, Demography, Education and Psychology.

Hands on training program to solve the statistical problems using simple computer-oriented program.

Course Outcomes:
1. Upon successful completion of the course a student will have a firm understanding of the fundamentals of Inferential Statistics.
2. He/she will be able to understand different applications of statistics in Industry,
Economics, Agriculture, Demography, Education and Psychology. Attempts have been made to demonstrate how a user can solve the problems using simple computer-oriented program.
3. Emphasis is placed not only on solving the problems in various fields but also on drawing inferences from the problems.

Goon A. M, Gupta M. K. and Dasgupta B, Fundamentals of Statistics, Vol-I World Press, Kolkata

Gupta, S.C., Fundamentals of Statistics, Himalaya Publishing House, New Delhi

Nagar and Das, Basic Statistics, Oxford University Press, New Delhi.

Murray R. Speigel, Theory & Problems of Statistics, Schaum’s publishing Series