Second Year Course Units

Physical Science

Course No.	Course Module	Credits	Hours	Combination
Sem I				P1	P2	P3	P4	P5	P6
ST2001	Basic Elements of Inference	2	30L	o	x	o	x	o	x
ST2002	Hypothesis Testing / Data Analysis-I	2	15P/15L		x		x		x
ST2004	Analysis of Variance & Design of Experiments	1	30L	o	o	o	o	o	o
Sem II
ST2003	Introduction to Non Parametric Methods	2	30L/30P		x		x		x
ST2005	Hypothesis Testing / Data Analysis-II	2	15P/15L	o	o	o	o	o	o

Note:

Students must select core courses (x) from at least 3 subjects out of the 4 subjects avilable within each steam.
AM core courses are compulsory for all students.
Abbreviations : x - core courses, o - electives, L - lectures, P - practicals, C - credits

Combinations

P1 - Physics,Chemistry, Applied Math., Computer Science
P2 - Physics, Applied Math., Statistics, Computer Science
P3 - Physics, Applied Math., Pure Math., Computer Science
P4 - Chemistry, Applied Math., Statistics, Computer Science
P5 - Chemistry, Applied Math., Pure Math., Computer Science
P6 - Applied Math., Statistics, Pure Math., Computer Science

ST 2001 : Basic elements of inference (30L, 2C)

Dependencies: AM 1001

Syllabus: Definitions of population, sample, parameter, statistic, and estimation; sampling distribution; point estimation, bias, error; interval estimation; margin of error, confidence intervals for mean and proportions, one sided and two sided tests, testing a two sided hypothesis using confidence intervals, level of significance (P-value), type I and type II errors associated with decision making, randomization test and exact p-value, determination of sample size, large sample tests for proportions.

Evaluation Criteria: End-of-semester examination and assignments

Suggested Readings: Introduction to Statistics: Concepts and Application (A. Sweeney and William), A Concise course in A-level Statistics (J. Crawshaw, J. Chambers)

ST 2002 : Hypothesis Testing / Data Analysis I (15L/30P, 2C)

Syllabus: Inferences about the mean of a normal population single sample Problems, point & interval estimation Single sample Problems, Point & interval estimation of hypothesis tests when s is known and when s is unknown. The distribution, Concepts of degrees of freedom Two sample problems, independent sample with (a) known Population Variances & (b) unknown but equal variances, Pooled variance, paired samples, confidence limits and hypothesis tests for the differences between the two population means.

Evaluation Criteria: End-of-semester examination and assignments

Suggested Readings: Fundamental of Mathematical Statistics (S.C. Gupta, V.K.K. Kapoor), Introduction to Mathematical Statistics (Robert V. Hogg and Allen T. Craig)

ST 2003 : Introduction to non–parametric methods (30L, 2C)

Dependencies: ST 1001

Syllabus: Introduction, one sample tests, randomization tests Wilcoxon’s one sample tests, Sign test, Sign Rank tests, Mann Whitney test, Simple Contingency tables, testing for independence, Fishers exact test, K.S.test, Kruskal-Wallis test, Friedman’s test

Evaluation Criteria: End-of-semester examination and assignments

Suggested Readings: Non Parametric Statistics (Sidney Siegal, N. john Castellan), Practical Non Parametric Statistics (William Conover), Non Parametric Statistical Test Based On Ranks (Lehnmann)

ST 2004: Analysis of variance & Design of Experiments (30L, 2C)

Dependencies: ST 1001

Syllabus: Principles of design, Replication and randomization, Model for a completely randomized design, Analysis of ariance for One – Way Classification, standard errors for specific comparisons.

Evaluation Criteria: End-of-semester examination and assignments

Suggested Readings: Experimental Design (W.G. Cochrn and G.M. Cox), The Design of Experiments (R. Mead), Statistical methods in agriculture and Experiment Biology (R. Mead and R.M. Curnow

ST 2005: Hypothesis testing /Data Analysis II (15L/30P, 2C)

Syllabus: Hypothesis testing for variance being equal to a specified value in the case of single sample and being equal to variance of a second population in the case of a two sample problem F distribution. Types of errors associated with hypothesis testing, Type I and Type II errors, Power of the test, power curves. Testing for parameters in the Poisson and Binomial distributions, Comparison of two Binomial probabilities, Chi – Square test.

Evaluation Criteria: Take-Home and In-Class practical assignments

Suggested Readings: Fundamental of Mathematical Statistics (S.C. Gupta, V.K.K. Kapoor), Introduction To Mathematical Statistics (Robert V. Hogg and Allen T. Craig)

Physical Science