The aim of this course is to provide a strong mathematical and conceptual foundation in the methods of statistical inference, with an emphasis on practical aspects of the interpretation and communication of statistically based conclusions in research. Content includes: review of the key concepts of estimation, and construction of Normal-theory confidence intervals; frequentist theory of estimation including hypothesis tests;  methods of inference based on likelihood theory, including use of Fisher and observed information and likelihood ratio; Wald & score tests.

To produce the students, that has applicable knowledge about Inferential Statistics, which they apply in different fields. 

1. To impart applied knowledge about Inferential Statistics and its tools
2. To impart skills on the data collection, description measures of data interpretation of results, and decision making

After successfully completing the course, students will be able to:

Understand the philosophy and basic concepts of interval estimation and testing of hypothesis. Conduct appropriate interval and hypothesis tests for comparing population parameters. Demonstrate the ability to derive power functions and design of uniformly most powerful tests for continuous and discrete variables. Demonstrate understanding of the theory of maximum likelihood ration tests, sequential tests. Exhibit skills in interpreting and communicating the results of statistical analysis, orally and in writing.

CONTENTS

Interval Estimation: Pivotal and other methods of finding confidence interval, confidence interval in large samples, shortest confidence interval, optimum confidence interval. Bayes’ Interval estimation. Tests of Hypotheses: Simple and composite hypotheses, critical regions. Neyman-Pearson Lemma, power functions, uniformly most powerful tests. Deriving tests of Hypothesis concerning parameters in normal, exponential, gamma and uniform distributions. Randomized Tests. Unbiased tests, Likelihood ratio tests and their asymptotic properties. Sequential Tests: SPRT and its properties, A.S.N. and O.C. functions.

1. Hogg,A.V., McKean, J.W., and Craig, A.T. (2005). Introduction to Mathematical Statistics 6th ed. Pearson Prentice Hall, USA,
2. Casella, G., and Berger, R. L. (2002) Statistical inference. 2nd  ed. Duxbury Press, CA, USA.
3. Mood, A. M. Graybill, F. A. & Boes, D.C. (1997). Introduction to the Theory of Statistics, McGraw Hill,

Distribution of Marks:
Mid Exam:           30
Final exam:         50

Sessional (Assignment,Presentation,Participation,Attendance,Quizes)    20
Scheduled on:      

BS 8(R):      Monday (09:00-10:00)    Thursday (12:00-01:00)      Friday    (10:00-11:00)

BS 8(SS):    Monday (02:00-03:00)    Wednesday (04:00-05:00)      Friday    (12:30-01:30)