Ph.D./M.Phil Course work Syllabus


Research Methodology

UNIT – I

Introduction: Definition of Research, Qualities of Researcher, Components of Research Problem, Various Steps in Scientific Research, Types of Research; Hypotheses Research Purposes - Research Design - Survey Research - Case Study Research.

UNIT-II


Data Collection: - Sources of Data: Primary Data, Secondary Data; Procedure Questionnaire - Sampling Merits and Demerits - Experiments - Kinds - Procedure; Control Observation - Merits
- Demerits - Kinds - Procedure - Sampling Errors - Type-I Error - Type-II Error.

UNIT-III

Statistical Analysis: Introduction to Statistics - Probability Theories - Conditional Probability, Poisson Distribution, Binomial Distribution and Properties of Normal Distributions, Point and Interval Estimates of Means and Proportions; Hypothesis Tests, One Sample Test - Two Sample Tests / Chi-Square Test, Association of Attributes - t-Test - Standard deviation - Co-efficient of variations - Index Number, Time Series Analysis, Decision Tree.

UNIT -IV


Statistical Application: Correlation and Regression Analysis - Analysis of Variance, Completely Randomized Design, Randomized Complete Block Design, Latin Square Design - Partial and Multiple Correlation - Discriminate Analysis - Cluster Analysis - Factor Analysis and Conjoint Analysis - Multifactor Evaluation, Two-factor Evaluation Approaches.

UNIT - V


Research Reports: Structure and Components of Research Report, Types of Report, Good Research Report, Pictures and Graphs, Introduction to SPSS.

 

Computer Application


·         Introduction
Classification of computers, computer memory, types of software’s: application of system software’s operating systems and types, single user, multi user, multi-tasking single tasking, application of computer for business and research.
·         Data Communication and networks
Data communication concepts, local area network, wide area network, internet, intranet, extranet, website. Email, search engines-enterprise E communication and E collaboration
·         MS Office and its application
File handing in window, various versions of MS Office, M S-Word: Test formatting, Mail merge, Macro, M S-Excel: Features, various formulas and functions M.S. Power Point: Creating presentations and adding effects.
·         SPSS
Introduction to SPSS: Definition, objectives and features, data analysis using SPSS: Data entry creating variables, switching to data labels, data analysis: Frequencies, recording into different variables, cross tabulations and layers.
·         Application of Internet in research
INFLIBNET, Use of Internet, sights (DOAJ), Use of E Journals, Use of E- library, use of EBSCO HOST online database of Academic Libraries.

Quantitative Method

1.      Meaning and definition of quantitative method
2.      Arranging data to convey meaning – Tables, Graphs and Frequency Distribution
3.      Measures of Central Tendency and Dispersion
4.      Simple and Multiple regression and correlation
5.      Association of Attributes
6.      Probability – probability Distributions, Binomial, Poisson and Normal
7.      Liner Programming - Formulation and Graphical solution to two variables – Assignment Problems, Transportation problems
8.      Queuing Theory – Single Server and Multi-Server
9.      Markov chains with Simulation Techniques – Monte Carlo Simulation
10.  Game theory – 2x2 zero sum game with dominance – pure strategy and mixed strategy
11.  Decision Theory – 5 criteria of decision making
12.  Chi-square
13.  Discriminant Analysis
14.  Factor Analysis
15.  Cluster Analysis
16.  Multidimensional Scaling
17.  ‘T’ Test
18.  ‘F’ Test


Reviewing of Published Research in the Relevant Field

·         Examining the methods of evaluating and interpreting published research.
·         Developing skills needed to research available literature for information relevant to a given topic.
·         Exploring the principles and techniques of topic/project development and testing.
·         Examining the methods of evaluating and interpreting data collected in the research process.
·         Developing an understanding of the various statistical methods that can be used to analyze data.
·         Demonstrating the ability to use statistical analysis tools and apply them in decision making activities.
·         Demonstrating the ability to create a template document that can be used to complete your research project or thesis


The above phase of course work classes shall be completed in a semester. The university shall manage part time or continue/residential classes for course work.


Study plan-
The course work classes are mandatory to attend 3 days in a month alternatively. The assignment should be submitted time to time.
Evaluation examination held in end of course time.