• Acquire a theoretical and practical knowledge on various
• Techniques of differentiation and integration and their applications

• Rules of differentiation
• Derivatives
• Differentiation of trigonometric
• Exponential and logarithmic functions
• Implicit functions
• Higher order differentiation
• Partial differentiation
• Total differentiation
• Extreme values of a function
• Sketch the graph of a function
• Optimization of a  function  of  two  variables
• Boarded Heizen

• Lagrange multiply method

• Indefinite   integral
• Integration   by   substitution
• Integration by parts
• Integration by partial fractions
• Definite integral: Double integration
• Finding area using integral

Recommended Readings

•  Strauss M.J, Bradley G.L. and Smith K.J. (2002) Calculus. Prentice Hall.

•  Chaing A.C. and Kevin W. (2009)  Fundamental Methods of Mathematical Economics.4^th edition,  Mc Graw-Hill, New York.

Learning Outcomes

On completion of this course unit, students will be able to

•  obtain the theoretical and application knowledge on probability and probability distributions

Conditional probability and independence

• Probabilities
• Bayes’ Theorem
• Independent events

• Discrete  random  variables
• Continuous random variables
• Expected value
• Variance
• Expectations and variance  and  a  function  of  a  random  variable
• Moment generation function

• The  Bernoulli Binomial distribution
• The Poisson distribution
• The Geometric distribution
• Negative  Binomial  distribution
• The  Hyper- geometric distribution
• The Uniform distribution

• The  Uniform  distribution
• Normal distribution
• Exponential distribution
• The Gamma distribution
• The Beta distribution   

• The  joint  distribution functions

• discrete case and continuous       

Co- variance and correlation

Joint probability distribution of functions of random variables

Recommended Readings

• Ross S. (2003) A First Course in Probability.  Pearson Education.

•  ජයතිස්ස. ඩ්බ්. ඒ. (2001). සංඛ්‍යාන විද්‍යාව:  සම්භාවිතාව සහ ව්‍යාප්ති න්‍යාය. කතෘ ප්‍රකාශන
  

• Obtain theoretical knowledge on regression, Correlation, Time Series and Index numbers that are mainly use in data analysis

• Scatter Diagram
• Regression LineFree hand method
• Least Square method
• Coefficient of Determination
• Predictions

• Product Movement Correlation
• Rank Correlation

• Components of a Time Series
• Estimation of Trend, Seasonal,  Cyclical  and  irregular  components  of  Time  series forecasting

• Simple  Relative  Indices
• Simple  aggregate Indices
• Rated  aggregate  indices
• Laspeyer  Paaschey’s  index
• Marshell Addedge Index
• Fisher’s Index
• Consumer price Index

 Recommended Readings

• Arora P.N. and  Arora S. (2007)Comprehensive Statistical Method.  S. Chand and Company.

• Rogger P. and Patterson J.H. (1987) Statistical Methods for Business and economics. Richard D. Irwin Homiwood Illinonis.

Learning Outcomes

On completion of this course unit, students will be able to

• Use matrix algebra to build up statistical models and analyzing statistical data
• Understand statistical theories using linear algebra

• Real vectors
• Vector equality
• Elementary vector operations
• Orthogonal vectors
• Orthonormal vectors

• Real matrices
• Matrix equality
• Special matrices
• Triangular, symmetric, diagonal, identity, elementary matrix operations

• Properties of the determinant
• Application of determinant to system of equations (Cramer’s rule)

• Properties of inverse
• Inversion by Gaussian elimination
• Application of inverse to system of equations

• Eigen values
• Eigen vectors

Recommended Readings

• Biswas S. (1996) A text book of Matrix Algebra. New Age International (Pvt) Ltd, New Delhi.

• Sancheti D. C. and Kapoor V. K. (2009) Business mathematics. Sultan Chand and Sons.

• Identify the historical development of computers
• Understand the functions of a computer system
• Identify the computer software and hardware
• Understand the services of operating system
• Understand the data communication and computer networks
• Learn the applications of computers in various disciplines

 
Course Content 

• History   of   computers
• Computer   generations
• Computer revolution

• Central processing unit
• Input Output devices
• External storage devices.

• Digital computers
• Analog computers
• Hybrid computers.

• On the basis of operating principles
• On the basis of aim of application
• On the basis of size and speed.

• System software and application software
• Compilers
• Interpreters
• System utility software

• Simple architecture of a typical computer
• Number conversion system

Operating system

Computer  Languages

• High  level  languages  and  Low  level languages

• Introduction  to data communication
• Introduction to computer networks
• Advantages of computer networks
• Networks topologies
• Data communication Hardware systems

• Scientific and business applications: Computers for medicine and sports
• The use of computers in government and politics
• Computer for research

Recommended Readings

• French C.S. (2004) Data Processing and Information Technology, 10^th edition, Thomson Learning.

• Carpinelli J.D. (2002) Computer Systems- Organization and Architecture, Pearson Education (Singapore) Pvt Ltd., Indian Branch.

• Forouzan B. (2006) Data Communications and Networking, 4^th edition, Tata McGraw-Hill Publishing Company Ltd.

Learning Outcomes

On completion of this course unit, students will be able to

• Obtain the theoretical and practical knowledge on the computer applications
• Analyze a given data set using appropriate Statistical package

• Working with worksheets
• Applying built in functions
• Data analyzing – creating Pivot tables, Creating graphs

• Creating Relational database
• Working with tables, forms and quires, generating reports

• Calculating descriptive statistics
• Summarizing data
• Parametric tests
• Regression analysis
• Chi-test
• Analysis of variance.

• Introduction
• Data description and simple interface
• Regression analysis
• Analysis of variance

Recommended Readings

• Bryman A. and Cramer D.,(1997) Quantitative data Analysis with SPSS for Windows, Routiedge.

• Fennings R. (1999) Using Microsoft Access 2000, Prentice-Hall of India Pvt Ltd.

Learning Outcomes 

At the end of this course unit, students will be able to

• understand the research methodology; theories and applications

Course Content

• Scientific Method; Deductive Method and Inductive Method
• Theoretical Research and Applied Research
• Ethics in Social Research

Identifying main and specific objectives of research

Identifying Research Questions

Literature Review and Constructing Research Hypotheses

Methods of Primary data Collection

Secondary Data Sources


Introduction to Data Analysis

• Qualitative Methods
• Quantitative Methods

Writing a Research Report

Recommended Readings

•  Emory C.W. (1980) Business Research Methods Homewood, Richard D Earwin Inc, Illnois.

• Kothari C.R. (1998) Research Methodology, Wishwa Prakshan Publication, New Delhi.

• Santosh Gupta, (1993) Research Methodology and Statistical Techniques, Deep and Deep Publication, New Delhi.

• Sarantakos, S, (1998) Social Research (Second Edition), Macmillon Press Ltd, London.

Learning Outcomes

On completion of this course unit, students will be able to                                     

• Gain practical skills in effective presentations                   
• Learn how to deal with an audience, control nervousness and handle themselves with poise and confidence                
• Develop and use factual, Logical and interesting supporting material                                        
• Give presentations with confidence, competence and clarity    
• Improve the ability to speak to a wide range of groups in different settings                            

• Use visual aids and support materials to make presentations more interesting (Power Point Slides, Transparencies, White board, and handouts)

• Understand the kind of audience

• Develop presenter’s personality

• Good  eye  contact  with  proper  gestures  and  hand movements  while  speaking  to  the  audience;  A  positive  body language

• Develop facial expressions to become a more friendly, warm, and approachable person 

Recommended Readings

• Kaye E. (2002) Maximize your Presentaion Skills: How to Speak, Look and Act on Your Way to the Top, 1^st edition, Prima Lifestyles.

• Kalish K. (1997) How to Give a Terrific Presentation, AMACOM.

• Zelazny G. (2000) Say It with Presentations: How to Design and Deliver Successful Business Presentations, McGraw- Hill.

• George and. Morrisey L. (1997) Loud and Clear: How to Prepare and Deliver Effective Business and Technical Presentations, 4^th edition, Addison – Wesley.

Learning Outcomes 

On completion of this course unit, students will be able to

• Learn various methods of point estimators and their characteristics
• Understand interval estimators, Confidence intervals and confidence limits
• Understand the various concepts related to the testing of hypothesis

• Unbiasedness, efficiency and consistency
• Sufficiency and their importance in estimation theory
• Minimum variance unbiased estimation
• Various methods of point estimation
• Method of maximum Likelihood
• Method of moments

• Confidence interval for mean
• Confidence interval for two different means  
• Confidence interval for proportions
• Confidence interval for variance
• Confidence interval for two different variances

• Type of Hypothesis
• Type I and II error
• P-value
• Significance levels
• Two sided test
• One sided test
• Decision rule
• Power of the test
• Large Sample Hypothesis  tests
• Small sample Hypothesis tests
• Population mean
• Population Variance and Standard Deviation
• Population proportional

Recommended Readings

•  Pfaffenberger R.C. (1977 ) statistical methods for Business and economics, Ricard D. Irwin, Inc.

•  Guptha S.C. and Kapoor V.K.(2009) Fundamentals of Mathematical Statistics, Sultan Chand and Sons.

Learning Outcomes

On completion of this course unit, students will be able to

•  Formulate Quantitative model for decision making process
•  Solve Quantitative models
•  Analyze the solution

Course Content 

The steps of Operational Research Project

Modeling

Linear Programming

• Graphical Method
• Simplex Method
• Duality
• Sensitivity Analysis

• Mathematical model of Transportation problem
• North West Corner Rule
• Vogel’s Approximation Method
• Modify Distribution Method

• Mathematical representation of Assignment Problem
• Formulation of an Assignment Problem
• The Hungarian method
• The assignment technique for minimizing and maximizing
• Unequal sources and destinations

• Project Evaluation and Review Technique
• Critical Path Analysis
• Time Cost trade off
• Shortest Route Problem
• Minimum Spanning Tree Problem
• Max Flow Problem

Recommended Readings

• Wagner H.M. (2004) Principles of Operations Research with Applications to Managerial Decisions, 2^nd edition, Prentice-Hall of India Pvt Ltd.

• Hamdy A.T. (2001) Operations Research, 6^th edition, Easton Economy Edition, India.

• Lucey T. (1996) Quantitative techniques, 5^th edition, DP Publications, London.

• Vonderembse M.A. and White G.P. (1994) Operational Management – Concepts, Methods and Strategies,3^rd edition, West publishing Company.

• a theoretical and technical knowledge to empirical testing and verifying economic theories

• Nature and Sources of Data for Economic Analysis
• Types of Data
• Sources of Data
• Accuracy of Data

• Linear Models
• Non-linear Models

•  Introduction
• Correlation Coefficient
• Rank Correlation Coefficient
• Partial Correlation Coefficient
• Limitation of the theory of Linear Correlation

• Introduction
• Two-variable Linear Regression Models
• Assumptions
• Estimation of the Models using Ordinary Least Squares Method (OLS)
• Defining Estimates
• Statistical or First Order Tests of Significance of the OLS Estimates
• Coefficient of Determinant, z, t and F Tests
• Confidence Intervals
• Desirable Properties of OLS Estimates

• Models with Two- explanatory Variables
• The General Linear Regression Models
• Assumptions
• Estimation of the Models using Ordinary Least Squares Method (OLS)
• Defining Estimates
• First Order Tests of significance of the OLS Estimates

Recommended Readings

• Gujarati, Damodar, N. (2004) Basic Econometrics, Tata McGraw-Hill, New Delhi.

• Koutsoyiannis, K. (2001) Theory of Econometrics: An Introductory Exposition of Econometric Methods, 2^nd Edition, PALGRAVE, New York.

• Madala, G. S. (1992) Introduction to Econometrics, Macmillan, New York.

• Pindyck, R. S. and D. L. Rubinfeld. (1990) Econometric Models and Econometric Forecasts, 4^th Edition, McGraw-Hill, New York.

Learning Outcomes

On Completion of this Course Unit, students will be able to

•  Identify the importance of information to management
•  Understand the concept of Information systems and Database systems
•  Design, create, maintain and manage database systems
•  Designing and coding Visual Basic Projects

• Definition
• Data Processing System
• Management Information system
• Decision Support System

System Development Life Cycle

Database and Database Management Systems (DBMS)

•  Functions  of DBMS
• Advantages and Disadvantages of DBMS

• Introduction
• Functions of Database
• Properties of Database

• Introduction
• Data and Database Administration
• Normalization
• Entity relationship diagramming
• Object Modeling
• Relational Data Model
• Classic Data Model
• Object Oriented Data Model

Database Protection

Database management

• Database Interface
• Structured Query Language (SQL)
• Distributed database systems

• Introduction
• Objects and Methods
• Working with forms
• Selecting and Using Controls
• Creating and Using Menus and Toolbars
• Storing and Retrieving data

Recommended Readings

• Hansen G.W. and Hansen J.V. (2005) Database Management and Design, Prentice Hall of India Pvt Ltd.

• Elmasri R., Navathe S.B., Somayajulu D. V. L. N. and Gupta S.K.(2004) Fundamentals of Database Systems, Dorling Kindersley (India) Pvt Ltd.

• Davies P.B. (1996) Database Systems, Macmillan press Ltd.

•  Bradley J.C. and Millspaugh A.G. (2002) Programming in Visual Basic 6, McGraw-Hill Irwin Inc.

Learning Outcomes

On completion of this course unit, students will be able to

•  Analyze complex data and interpret large data sets
•  Use the theoretical knowledge for decision making

• Characteristics and applications

• Multiple Regression
• Multiple discriminant analysis
• Multivariate analysis of Variance
• Canonical correlation analysis
• Factor Analysis
• Important methods of Factor Analysithe centroid method, the principal components method, the maximum likelihood method Rotation in factor analysis R-type and Q-type factor analysis
• Cluster analysis
• Multi-dimensional scaling
• Latent structure analysis

 A statistical package will be used throughout the course

Recommended Readings

• Aczel A. D. (1993) Complete Business Statistics, 2^ND edition
• Richaer D. Irwin, Inc. Kothari C. R. (2004) Research methodology – Methods and Techniques, 2^nd edition, New Age International Publishers.

Learning Outcomes 

On completion of this course unit, students will be able to

•  Understand various methods of non parametric tests and concepts related to the testing of hypothesis
•  Obtain the theoretical and practical knowledge on the analysis of non parametric

Course Content 

• Introduction to Non Parametric methods
• Advantages of Non Parametric Methods
• Disadvantages of Non Parametric Methods

• Chi Square Tests : Introduction to Chi Square Test, Degrees of freedom, Chi Square Distribution
• Test of the hypothesis of equal probability
• Test of the hypothesis of Independence(Difference)
• Test of the hypothesis of Normality
• Calculation of Chi Square for 2x2 tables
• Yate’s correction for continuity
• Chi Square from percentages
• General observations on Chi Square

• The sign test for paired data
• One sample sign test
• Rank sum test
• Mann-Whitney Test (U - Test)
• Kruskal – Wallis Test (H – Test)
• One Sample Runs Test
• Median test for Randomness (Runs above and below the Median)
• Spearman’s Rank correlation Test
• Testing Hypothesis about Rank Correlation
• Kolmogorov- Smirnov Test
• Kendall test of Concordance
• Median test for two Independent samples
• Wilcoxon Signed – Rank test
• The matched – pairs sign test

Recommended Readings

• Arora P.N., Arora Sumeet and Arora S (2007) Comprehensive Statistical Methods,  S. Chand, India.

• Conover W.J. (1999) Practical Non parametric Statistics, John Wiley & Sons, INC.

Learning Outcomes

By following the Internship Programme the students will be able

• to exploit the opportunity to gain exposure to world of work
• to develop their soft skills and attributes
• to make use of their knowledge of economics in carrying out work – related activities

Course Content      

For this programme it is essential to establish links by the department staff and/or by students themselves with government agencies, private enterprises and Non – Governmental Organizations (NGOs) in order to provide internship opportunities for all special degree students in their third year. The Internship period will be about 3 months. Under this programme students are required to work minimum 2 days a week at the assigned institution while on the other days they will attend lectures/tutorials at the University.

Learning Outcomes 

On completion of this course unit, students will be able to gain

•  theoretical and practical skills in data tabulation, processing and analysis

Course Content        

• Understanding data in statistical analysis (primary and secondary data, time series, cross – sectional and panel data)

• Quantitative vs Qualitative data

• Numerical vs Descriptive data Data Editing (non – response, errors and missing data and what to do about them)

• Data management organization and presentation (Graphical and pictorial presentations, SPSS and Excel demonstration of graphical and pictorial presentations)

• Tabular presentation (SPSS demonstration) Correlation

• Regression and Time Series analysis using Statistical Packages

Recommended Readings

• Stephens S. M. (2008) Schaum’s Statistics (Schaum’s Outline Series). 3^rd Edition, McGraw – Hill, New York.

• Ross S. M. (1996) Introductory Statistics, Mc Graw Hill Company Inc.

• Gupta C.B. and Gupta V. (1999) An Introduction to Statistical Methods, Vikas Publishing House, New Delhi.

Learning outcomes         

On completion of this course unit, students will be able to acquire

• a theoretical and practical knowledge to empirical testing and verifying economic theories

• Two-variable Regression Model
• Multiple Regression Model
• Relaxing the assumption of the Classical Model
• Heteroscadasticity
• Autocorrelation
• Multicolinearity
• Generalized least square method

• Linear probability model (LPM)
• Logit model
• Probit model
• Panel data regression models
• Dynamic econometric models
• Distributed-Lag model
• Autoregressive model                

• Introduction
• Identification problem
• Simultaneous equation methods

• Concept and Forecasting
• Estimation of the models using computer packages         

Recommended Readings

• Gujarati, Damodar, N. (2004) Basic Econometrics, Tata McGraw-Hill, New Delhi.

• Koutsoyiannis, K. (2001) Theory of Econometrics: An Introductory Exposition of Econometric Methods, 2^nd Edition, PALGRAVE, New York.

• Madala, G. S. (1992) Introduction to Econometrics, Macmillan, New York.

• Pindyck, R. S. and D. L. Rubinfeld. (1990) Econometric Models and Econometric Forecasts, 4^th Edition, McGraw-Hill, New York.

Learning Outcomes 

On completion of this course unit, students will be able to

• Solve Integer Linear Programming and Binary Linear Programming Problems
• Identify Queuing models and solve problems
• Identify the appropriate Stock control models based on the situation of the business
• Solve problems of Decision theory and Game Theory

• Fractional cut for Pure Integer
• Linear Programming
• Fractional cut for Mixed Integer Linear Programming
• Branch and Bound Algorithm

• The simple queue (M/M/1)
• M/M/1 system with discourage arrivals
• M/M/1 system with responsive server
• Multi server queue
• M/M/1 with finite waiting room capacity
• M/M/1 with finite population

• The Simple Stock Control Model
• Stock Control with Discounts
• Stock Control When Demand rate is Variable and lead Time is non zero
• Stock Control with Backlogging
• Stock Control with Gradual replenishment
• Purchasing model with Shortages

• Two Person Zero-sum games
• Mixed Strategy solution 2 X n Games
• A general method of solution
• Two Person non Zero-sum games
• Nash Equilibrium and Non- Cooperative solutions

• Decision making under certainty
• Complete enumeration
• The Expected value
• The Expected Opportunity Loss
• The value of perfect information
• Decision Under Uncertainty: Criteria of choice – Laplace, Criterion of pessimism,  Criterion of Optimism, Savages Criterion
• Decision Trees
• Applications of revised probabilities using Bayer’s Theorem

Recommended Readings

•  Wagner H.M., (2004) Principles of Operational Research with applications to Managerial Decisions, Prentice Hall of India Pvt. Ltd.

•  Murty K.G., (2002) Operations Research Deterministic Optimization Models, Prentice Hall, Newjersey.

•  Hamdy A.T. (2001) Operations Research, 6^th edition, Easton Economy Edition, India

Learning Outcomes

On successful completion of the course unit, students will be able

• to understand the basic principles and methods underlying sample surveys
• to assess the appropriateness of various sampling schemes and to calculate precisions and sample sizes
• to achieve specific precisions or costs to have a basic understanding of the ideas underling the scale type classification and the concepts of  validity and  reliability
• to  have a general knowledge of practical survey methods and statistics in society

Course Content 

An Overview of Sampling

• Probability sampling and non- probability sampling

• Estimation of Mean and Population Total
• Confidence Intervals
• Proportions and Percentage without and with replacement
• Determination of sample size
• Ratio Estimators and Regression Estimators

• Estimation of Mean and Population Total
• Confidence Intervals
• Determination of sample size

• Cluster sampling with equal cluster size
• Estimation of mean and Population Total
• Confidence Intervals

• Estimation of mean and population Total
• Confidence Intervals
• Determination of sample size

• Purposive sampling
• Quota sampling
• Convenience sampling
• Snowball Sampling
• Self- Selection

Recommended Readings

• Cochran, W.G. (1977) Sampling techniques, New York, Wiley.

• Scheaffer R.L., Mendenhall W. and Ott L (1996) Elementary Survey Sampling, 5^th edition, Duxbury.

• Barnett V. (1991) Sampling Survey: Principles and Methods,London, Arnold.

• Holnville G., JowelR. l and associates (1985) Survey Research Practice, Gower.

• Ardilly P. and Tille Y. (2006) Sampling Methods: Exercises and Solutions, New York.

• Translate an experimental description into a statistical model, including identifying model restrictions and assumptions
• Develop appropriate hypothesis tests and statistical comparisons for experimental designs
• Analyze experiments in the presence of common difficulties, including missing and unbalanced data

Course Content

Introduction

• Terminology of Experimental Designs
• Principles of Experimental Designs
• Analysis of Variance

Randomized Block Design

Latin Square Design

Analysis of Covariance

Missing Plot Techniques

Factorial Experiments

Split-Plot Design

Balanced Incomplete Block Design

Recommended Readings

• Anderson V. L. Mclean R. A. (1974) Designs of Experiments, Mercel Dekker Inc.

• Cox D. R. (1958) Planning of Experiments, John Wiley Sons, New York.

• Gupta, S. C. and Kapoor, V. K. (2007) Fundamentals of Applied Statistics, 4^th Edition, Sultan Chand and Sons, New Delhi.

Learning Outcomes 

On completion of this course unit, students will be able to

•  Analyze categorical data
•  Obtain the knowledge on Statistical Quality Control and control charts

• Application of Chi Square test
• Analysis of contingent tables
• Fitting data to theoretical distribution
• Applications of Log linear models and Logistic

• Product Control and Process Control
• Control charts for variables: X chart, R chart
• Control charts for attributes: T-Chart, np Chart, C- chart
• Product Control: Acceptance sampling method, One stage acceptance sampling

Recommended Readings

•  Grant E. L. and Leavenworth R.S. (2008) Statistical Quality Control. 7^th edition. McGrow – Hill.

•  Montgomery D.C. (1996) Introduction to Statistical Quality Control, Jhon Wiley and Sons.

•  Arora P.N., Arora Sumeet and Arora S (2007) Comprehensive Statistical Methods,  S. Chand, India.

Learning Outcomes 

On completion of this Course unit, students will be able to

•  acquire Knowledge on democratic Statistics

Course Content     

Introduction and scope of in subject

• Uses of Vital Statistics
• Methods of Obtaining Vital Statistics
• Measurement of Population
• Rates and Ratios of Vital Events

• Crude Death Rate (C.D.R.)
• Specific Death Rates (S.D.R)
• Infant Mortality Rate (I.M.R)
• Standardized Death Rates
• Mortality Table (Or Life Table)
• Stationary Population
• Stable Population
• Central Mortality Rate
• Force of Mortality
• Assumptions
• Descriptions and Construction of Life Table
• Uses of Life Tables
• Abridged  Life  Table: Reed – Merrell Method, Greville’s Method, King’s Method

• Crude Birth Rate (C.B.R.)
• General Fertility Rate (G.F.R.)
• Specific Fertility Rate (S.F.R.)
• Total Fertility Rate (T.F.R.)

• Pearl’s Vital Index
• Gross Reproduction Rate (G.R.R.)
• Net Reproduction Rate (N.R.R.)
• Graduation of Mortality Rates
• Makeham’s Graduation Formula
• Gomertz Makeham Formula for Mortality
• Makeham’s Second Law of Mortality

Recommended Readings

• Siegel J.S. and Swanson D.A. (2004) A Method and Materials of Demography.2^nd edition. Amsterdam: Elsevier.

• Craig D.H. (1995) Demographic Projection techniques for Regions and Smaller Areas. Vancouver: University of British Columbia Press.

• William P. (2000) From Birth to Death: A Primer In Demography for the Twenty First Century, NJ: Transaction publishers, New Brunswick

Learning Outcomes 

On completion of this course unit, students will be able to do an independent research with the aim of training researchers

Course Content      

A dissertation of about 8000-10000 words of research work should be submitted.

Students will be given guidance and supervise their work by competent lecturer or lecturers assigned by the department

The topic of the research may be selected by the student

The topic has to be approved by the relevant supervisor and the Head of the Department

Recommended Readings

• Das D.K.L. (2007) Practice of Social Research, Rawat Publications, New Delhi.

• Nicholas W. (2005) Your Research Project: A step by step guid for the first time researcher, Vistar Publications, New Delhi.