Page 132 - CatalogNEP-PS

and Ratio scale; scaling techniques. Classification, analysis and presentation of data.
Statistical treatment of collected data. Arithmetic mean, geometric mean and standard
deviation.
UNIT-V Testing of Hypothesis (9 Hours)

37. Meaning, Characteristics and concepts relating to testing of Hypothesis (Parameter and
statistic, Standard error, Level of significance, type-I and Type-II errors, Critical region,
one tail and two tail tests); Procedure of testing Hypothesis. Sampling schemes like,
simple random sampling without replacement, simple random sampling with replacement
and stratified random sampling.

SUGGUESTED READINGS:

1. C.R. Kothari, ―Research Methodology‖, New Age Publishers, 2004
rd
2. R. Kumar, ―Research Methodology‖,3 edition, 2011.
3. A.M. Goon, M.K. Gupta and D. Gupta, ―Fundamentals of Statistics‖, Vol. I, 8th Edn. The
World Press, Kolkata, 2002.
th
4. S. C. Gupta and V.K. Kapoor, ―Fundamentals of Mathematical Statistics‖, 4 Edition
(Reprint), Sultan Chand &Sons, 2008.

Minor II:

Comp.311 Programming Using Python 2+1

LEARNING OBJECTIVES:

The primary objective of this course is:
 Introduces programming concepts using Python to Computer Science students.
 Focuses on the development of Python programming to solve problems of different
domains.
 Introduces the concept of object- oriented programming

LEARNING OUTCOMES:

This course will enable the students:
 Understand the basics of programming language
 Develop, document, and debug modular Python programs.
 Apply suitable programming constructs and built-in data structures to solve a problem.
 Use and apply various data objects in Python.
 Use classes and objects in application programs and handle files.

THEORY (30 Hours)

UNIT I: (4 Hours)

Introduction to Programming
Problem solving strategies; Structure of a Python program; Syntax and semantics; Executing
simple programs in Python.

UNIT II: (10 Hours)
CreatingPythonPrograms

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