On completion of this course unit, students will be able to:
 Acquire a theoretical and practical knowledge on various
 Techniques of differentiation and integration and their applications
Definition
 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
Solving differential equations
Application of calculus in social sciences
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 GrawHill, 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
Course Content
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
On completion of this course unit students will be able to
 Obtain theoretical knowledge on regression, Correlation, Time Series and Index numbers that are mainly use in data analysis
Course Content
Simple Regression 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
Course Content
Vectors
 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.
On completion of this course unit, students will be able to
 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
Introduction
 History of computers
 Computer generations
 Computer revolution
Basic components of a computer
 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 McGrawHill 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
Course Content
Excel
 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
 Chitest
 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, PrenticeHall 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
Course Content
Difference between Point estimate and Interval estimate
Various characteristics of Point estimators
 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
 Pvalue
 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, PrenticeHall 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.
On completion of this course unit, students will be acquiring
 a theoretical and technical knowledge to empirical testing and verifying economic theories
Course Content
Definitions and Scope of Econometrics
 Nature and Sources of Data for Economic Analysis
 Types of Data
 Sources of Data
 Accuracy of Data
 Linear Models
 Nonlinear Models
Correlation Theory
 Introduction
 Correlation Coefficient
 Rank Correlation Coefficient
 Partial Correlation Coefficient
 Limitation of the theory of Linear Correlation
 Introduction
 Twovariable 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
Dummy Variables
Regression and Analysis of Variance
Relaxing the Assumption of the Classical Model
Estimation of the models using Computer Packages
Recommended Readings
 Gujarati, Damodar, N. (2004) Basic Econometrics, Tata McGrawHill, 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, McGrawHill, 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
Course Content
Information Systems
 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, McGrawHill 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
Course Content
Introduction to Multivariate Analysis
 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 Rtype and Qtype factor analysis
 Cluster analysis
 Multidimensional 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
Non Parametric Methods
 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
 MannWhitney 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
Course contents
Methodology of Econometric Research
Regression analysis
 Twovariable Regression Model
 Multiple Regression Model
 Relaxing the assumption of the Classical Model
 Heteroscadasticity
 Autocorrelation
 Multicolinearity
 Generalized least square method
Qualitative response regression models
 Linear probability model (LPM)
 Logit model
 Probit model
 Panel data regression models
 Dynamic econometric models
 DistributedLag 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 McGrawHill, 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, McGrawHill, 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
Course Content
Integer Linear Programming
 Fractional cut for Pure Integer
 Linear Programming
 Fractional cut for Mixed Integer Linear Programming
 Branch and Bound Algorithm
Queuing Theory
 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 Zerosum games
 Mixed Strategy solution 2 X n Games
 A general method of solution
 Two Person non Zerosum 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.
On completion of this course unit, students will be able to
 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
SplitPlot 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
Course Content
Analysis of Categorical data
 Application of Chi Square test
 Analysis of contingent tables
 Fitting data to theoretical distribution
 Applications of Log linear models and Logistic
Statistical quality control
 Product Control and Process Control
 Control charts for variables: X chart, R chart
 Control charts for attributes: TChart, 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 800010000 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.