First Year: Semester I

First Year: Semester II

Second Year: Semester I

Second Year: Semester II

Third Year: Semester I

Third Year: Semester II

Fourth Year: Semester I

Fourth Year: Semester II

Statistics: Its nature and scope. Nature of statistical data. Attributes and variables, population and sample, collection and condensation of data. Frequency distribution. Graphical representation of data. Measures of location: Arithmetic Mean, Median, mode, geometric mean, harmonic mean, quadratic mean, quartiles, deciles and percentiles. Measures of dispersion: range, mean deviation, standard deviation, variance, quartile deviation, coefficient of variation, moments and cumulants of a distribution, skewness and kurtosis. Regression and correlation: Bivariate data. Relationship between the variables. Method of least squares, regression line. Correlation and regression coefficients. Rank correlation and correlation ratio.

Hoel P G, Introductory Statistics, John Wiley, NY

Johnston J. Econometric Methods

Mostafa M G, Methods of Statistics, Bangladesh

Weatherburn C E, A first Course in Mathematical Statistics

Wonnacott & Wonnacott, Introductory Statistics

Yule and Kendal, An Introduction to the theory of Statistics

 

Statistics: Definition, subject matter, application in social science. Summerarization of data: Frequency Distribution, graphical representation of statistical data. Central tendency and dispersion: Mean, median, mode, standard deviation, mean deviation, coefficient of variation, decile, percentile, etc, moments, skewness and Kurtosis. Probability: Concept of probability, laws of probability, mathematical expectations, independence of two or more random variables. Index number: Construction of price, voting and quantity Index, cost of living index.

Wonnacott & Wonnacott Introductory Statistics

Mostafa M G, Methods of Statistics, Bangladesh

Yule and Kendal, An Introduction the Theory of Statistics

 

Statistics: Definition, subject matter, application of statistical tools in economic analysis. Statistical Data: Nature, classification and tabulation, frequency distribution, various methods of graphical representation. Measures of central tendency and dispersion: Mean, mode, median, quartiles and percentiles, variance and standard deviation, coefficient of variation, skewness and kurtosis. Sampling: Population and sample, census and sampling, methods of sampling- simple random sampling, stratified sampling, systematic sampling, two stage sampling, sampling error and non-sampling errors. Index number: Construction of price, quantity, value and cost of living indices, Laspeyere, Paasche and Fisher’s ideal indices, problems in construction, uses of price indices, tests of index number, special purpose indices- cost of living index number. Probability: Definition and related concepts, laws of probability, discrete and continuous random variables, mathematical expectations.

Croxton & Cowdon, Applied General Statistics, Prentice Hall

Klein L, A Text Book of Econometrics

Mirer T, Economic Statistics and Econometrics

Mood & Grabill, Introduction of the Theory of Statistics

Mostafa M G, Methods of Statistics

Walpole R W, Introduction to Statistics

Wonnacott & Wonnacott, Intoductory Statistics, Wiley

Yule & Kendal, An Introduction to the Theory of Statistics, Macmillan.

 

Statistics: definition, subject matter, applications of statistical tools in economic analysis. Statistical data: nature, classification and tabulation, frequency distribution, various methods of graphical representation. Measures of central tendency and dispersion: arithmetic mean, geometric mean, harmonic mean, weighted average, mode, median, quartiles and percentiles, variance and standard deviation, coefficient of variation, skewness and kurtosis.

Probability: Definition and related concepts, laws of probability, conditional probability, Bayes theorem.

Random variables: Definition, discrete and continuous random variables, probability function, distribution function, joint, marginal and conditional probability functions. Mathematical expectation: Expectations of sum and product, conditional expectation and conditional variance. Moments and moment generating function, cumulants.

Index numbers: Different types of index numbers, formulae, construction and tests of index numbers, cost of living index number, uses and importance.

Mostafa M G, Methods of Statistics

Islam M N, An Introduction to Statistics and Probability

Roy M K, Fundamentals of Probability and Probability distributions

Croxton & Cowdon, Applied General Statistics, Prentice-Hall

Mood & Grabill, Introduction to the Theory of Statistics

Walpole R W, Introduction to Statistics, Collier-Macmillan

Wonnacot & Wonnacot, Introductory Statistics, Wiley

 

Random experiment: Sample space. Events. Union and intersection of events. Different types of events. Probability of events. Axiomatic development of probability. Computation of probability. Theorems of total and compound probability. Conditional probability. Bayes theorem. Random variables: Probability function, distribution function, joint, marginal and conditional probability functions. Mathematical expectation: Expectations of sum and product. Conditional expectation and conditional variance. Moments and moment generating functions. Characteristic function. Distributions: Study of binomial, poisson, and normal distribution.

Feller W, Introduction to Probability, Vol-1, 3rd Ed, John Wiley, NY

Hoel P G, Introduction to Mathematical Statistics, John Wiley, NY

Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London

Meyer A, Probability and statistics, Addison-Wesley, USA

Mood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NY

Mosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-wesley, USA

Ross S M, A first Course in Probability, Academic Press, NY

 

Distributions: Detailed study of binomial, Poisson, and normal distribution.

Sampling: population and sample, census and sampling, probability and non-pr0bability sampling, methods of sampling -simple random sampling, stratified sampling, systematic sampling, cluster sampling, Estimation of population total, mean, proportion and their standard errors, determination of sample size, sampling errors and non-sampling errors.

Correlation and regression analysis: bi-variate frequency distribution, correlation, rank correlation, partial and multiple correlation, linear and non-linear regression. Method of least squares, estimation of simple linear regression parameters; theorems used in correlation and regression analysis, introduction to the notion of goodness of fit.

Time series: analysis of economic time series, estimating trends, seasonal and cyclical components.

Income and wealth distributions: study of lognormal distributions, Pareto curve, Lorenz curve. Basic Ideas of analysis of variance.

Mostafa M G, Methods of Statistics

Islam M N, An Introduction to Statistics and Probability

Islam M N, An Introduction to Sampling Methods

Roy M K, Fundamentals of Probability and Probability distributions

Klein L, A Test Book of Econometrics

Mirer T, Economic Statistics and Econometrics

Gupta and Kapoor, Fundamentals of Applied Statistics

 

Sets and their properties. Random experiment, Sample space, events, union and intersection of events, different types of events, probability of events, axiomatic development of probability, computation of probability.

Theorems of total and compound probability, conditional probability, Bayes theorem, realization of m among n events.

Random variables: Definition, Probability function, distribution function, joint, marginal and conditional probability functions.

Mathematical expectation: Expectations of sum and product, conditional expectation and conditional variance, Chebyshev’s inequalities.

Probability Distributions: Binomial , poison, negative binomial, hypergeometric and normal distributions and their applications in solving probability problems.

Law of Large Numbers- Weak and Strong Law

Meyer A, Probability and Statistics , Addison-Wesley, USA

Feller W, Introduction to Probability Theory and its Applications, Vol-1, 3^rd Ed, John Wiley, NY

Mood, Graybill &Boes, Introduction to Theory of Statistics, 3^rd Ed, McGraw Hill, NY

Mosteller, Rourke &Thomas, Probability with Statistical Applications, 2^nd Ed, Addison-Wesley,USA

Parzen E, Modern Probability Theory and its Applications, John Wiley, NY

Ross S M, A First Course in Probability, Academic Press, NY

Ross S M, Introduction to Probability Models, 3^rd Ed, Academic Press, NY

Roy MK. Fundamentals of Probability and Probability distributions.

Islam, M.N., Introduction to Statistics and Probability, 3rd Edition

 

Theory of Statistics: Meaning and scope, variables and attributes, Different scales of measurement, frequency distribution and graphical representation. Summarisation of data: Location, dispersion and their measures, skewness, kurtosis and their measures, moments and cumulants, density functions, moments generating function, cumulant generating function. Characterisation of binomial, poisson, negative binomial, geometric, hypergeometric, multinomial, uniform, normal, and exponential distributions. Transformation of variates, standard errors of statistics. Association of attributes: Basic ideas, independence, association and disassociation, measures of association, partial association, contingency table, association in contingency table.

Bulmer M G, Principles of Statistics, 2^nd Ed, Oliver and Boyd, Edinburgh

Hoel P G, Introduction to Mathematical Statistics, 5^th Ed, John Wiley, NY

Moore P.G, Principles of Statistical Techniques, 3^rd Ed, Cambridge University Press, London

Mostafa M G, Methods of Statistics, Bangladesh

Wonnacott K H & Wonnacott R J, Introductory Statistics, 3^rd Ed, John Wiley, NY

Weatherburn C E, A First Course in Mathematical Statistics, Cambridge University Press, London

Yule G U & Kendal M G, An introduction to the Theory of Statistics, 14 th Ed, Charles-Griffin, London

Islam, M.N., Introduction to Statistics and Probability, 3rd Edition

Condensation and tabulation of data , frequency distribution, graphical representation of data, measures of location, dispersion, skewness and kurtosis, fitting of binomial, poisson and normal distributions, test of independence in contingency table.

Sampling and sampling distribution, sampling from normal and non-normal populations, distribution of various statistics. Distribution of linear functions of normal variates, joint distribution of and , detailed study of , Student’s t and F distributions, distribution of correlation coefficient in the null case, distribution of regression coefficient.

Order Statistics, Joint Distribution of n order Statistics, Marginal Distributions of order Statistics, Distribution of the Median and Range, properties of order Statistics.

Distribution of test Statistics and performance of tests. Test for assigned mean, variance, proportion and correlation. Comparison of means, proportions, variances and correlation. Bartletts test of homogeneity of variances. Test for correlation and regression coefficients. Exact test for table, test for contingency table. Central limit theorem.

Ali A, Theory of Statistics, Vol-II, Bangladesh

Hoel P G, Introduction to Mathematical Statistics, 5th Ed, John Wiley, NY

Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London

Kendall & Stuart, Advanced Theory of Statistics, 4th Ed, Charles-Griffin, London

Mood, Graybill & Boes, Introduction to the Theory of Statistics, 3rd Ed, McGraw Hill, NY

Mostafa M G, Methods of Statistics, Bangladesh

Wonnacott K H & Wonnacott R J, Introductory Statistics, 3rd Ed, John Wiley, NY

Weatherburn C E, A First Course in Mathematical Statistics, Cambridge University Press, London

Islam, M.N., Introduction to Statistics and Probability, 3rd Edition

 

Small and large sample tests for proportion, mean, variance, correlation coefficient, regression coefficient, partial correlation coefficient and multiple correlation coefficient, test for independence in contingency table.

Random experiment: Sample space. Events. Union and intersection of events. Different types of events. Probability of events. Axiomatic development of probability. Computation of probability. Theorems of total and compound probability. Conditional probability. Bayes theorem. Random variables: Probability function, distribution function, joint, marginal and conditional probability functions. Mathematical expectation: Expectations of sum and product. Conditional expectation and conditional variance. Moments and moment generating functions. Characteristic function. Distributions: Study of binomial, poisson, and normal distribution.

Feller W, Introduction to Probability, Vol-1, 3rd Ed, John Wiley, NY

Hoel P G, Introduction to Mathematical Statistics, John Wiley, NY

Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London

Meyer A, Probability and statistics, Addison-Wesley, USA

Mood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NY

Mosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-wesley, USA

Ross S M, A first Course in Probability, Academic Press, NY

 

4 Hours/Week, 4 Credits

Frequency distribution of data: Population and sample. Collection and representation of statistical data. Tabulation of data. Class intervals. Frequency distribution, discrete, continuous and cumulative distributions. Histograms and frequency polygons. Graphical representation of data. Statistical measures: Measures of central tendency - arithmetic mean, median, mode, geometric mean, weighted average, harmonic mean. Measures of dispersion - range, standard deviation, variance, coefficient of variation, moments, skewness, kurtosis. Correlation theory: Linear correlation. Measures of correlation and its significance. Regression and curve fitting: Linear and non-linear regression. Methods of least squares. Curve fitting. Probability: Definition of probability and related concepts. Laws of probability. Discrete and continuous random variables. Mathematical expectations. Conditional probability. Probability distributions: Binomial, poisson and normal distributions and their properties. Stochastic process. Markov chain (discrete and continuous). Queuing theory - Birth death process in queuing. Examples from computer science. Queuing models. (Elementary concepts).

Barlow R J, Statistics

Chisholm J S R & Morris R M, Mathematical Methods in Physics

Hoel P G, Elementary Statistics, John Wiley, NY

Loveday, Practical Statistics and Probability

Melnyk M, Principles of Applied Statistics

Mostafa M G, Methods of statistics, Bangladesh

Mosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USA

Spiegel M R, Theory and Problems of Statistics, McGraw Hill, NY

Topping, Observation of Errors

 

Probability Distribution: Probability Functions, Probability Density Functions, Selected Probability Distributions- Binomial Poison and Normal. Sampling Distributions: Basic Concept of X² , t and F Distributions. Tests of Significance: Basic Concepts; Tests of Significance of Mean, Proportions, Correlation Coefficient and Regression Coefficients. Correlation and Regression Analysis: Bivariate Frequency Distribution; Correlation and Regression Coefficients; Partial and Multiple Correlation; Rank Correlation; Computation of Simple Linear Regression Parameters; Introduction to the notion of goodness of it. Time Series: Analysis of Economic Time Series; Estimating Trends; Seasonal and Cyclical Components. Income and Wealth Distribution: Study of Lognormal Distribution, Pareto Curve, Lorenz Curve.

Croxton & Cowdon, Applied General Statistics, Prentice-Hall

Klein L, A Text Book of Econometrics

Mirer T, Economic Statistics and Econometrics

Mood & Graybill, Introduction to the Theory of Statistics

Mostafa M G, Methods of Statistics

Walpole R W, Introduction to Statistic, Collier-Macmillan

Wonnacot P & Wonnacot R, Introductory Statistics, Wiley

Yule & Kendal, An Introduction to the Theory of Statistic, Macmillan

 

Statistics: Definition. subject matter, application of statistical tools in sociological and economic analysis. Statistical data: nature, classification and tabulation. frequency, distribution, various methods of graphical representation. Measures of central tendency and dispersion: mean, mode, median, quartiles and percentiles, variance and standard deviation, coefficient of variation, Correlation, Rank correlation.

Sampling: Concepts and methods of sampling. Probability: Definition and related concepts. Definition of Normal distribution, t distribution, λ² distribution, F distribution. Test of Hypothesis: Test for mean, Proportion, Corelation-Coefficients and Regression-Coefficient. Test for Independence.

Blalock H M, Social Statistics.

Hagood, Statistics for Sociologists

Kendal & Yule, Introduction to the Theory of Statistics.

Mostafa M G., Methods of Statistics.

Walpole R W., Introduction to Statistics.

Wonnacott P & Wonnacott R. Introductory Statistics.

 

Correlation and Regression: Bivarite data, distribution and use of coefficient of correlation. Coefficient of determination. Time Series: Its components, measurement of trend , method of least squares and moving average. Probability, probability distribution: Probability function, probability density function, binomial, poisson, normal and c ² distributions. Test of hypothesis.

Sampling Theory: Population and sample, census and sample survey, types of sampling, technique and methods for the preparation of a questionnaire. Strength and limitations of the application of statistical techniques in social and political analysis.

Dwyer, Statistical Models for the social & Behavioural Sciences

Goode W J & Panek H, Methods in Social Research

Selltiz C, Research Methods in Social Relations

Young P V, Scientific Social Surveys And Research

Mostafa, M.G, Methods of Statistics, Bangladesh

 

Statistics: Its nature and scope. Nature of statistical data. Attributes and variables, population and sample, collection and condensation of data. Frequency distribution. Graphical representation of data. Measures of location: Arithmetic mean, median, mode, geometric mean, harmonic mean, quadratic mean, quartiles, deciles and percentiles. Measures of dispersion: Range, mean deviation, standard deviation, variance, quartile deviation, coefficient of variation, moments and cumulants of a distribution, skewness and kurtosis. Regression and correlation: Bivariate data. Relationship between the variables. Methods of least squares, regression line. Correlation and regression coefficients. Rank correlation. Probability: Sample space, Event, Probability of event, Random variable, Binomial and Normal distribution; t, c ² and F distribution. Statistical Tests- Test of proportion mean, variance, correlation coefficient, regression coefficient, test for independence of attributes. Sampling:- Simple random sampling, Stratified random sampling, Systematic sampling, cluster sampling. Determination of sample size in S.R.S and Stratified random sampling.

Hoel P G, Introductory Statistics, John Wiley, NY

Johnston J. Econometric Methods

Mostafa M G, Methods of Statistics, Bangladesh

Weatherburn C E, A first Course in Mathematical Statistics

Wonnacott & Wonnacott, Introductory Statistics

Yule and Kendal, An Introduction to the theory of Statistics

Hoel P G, Introduction to Mathematical Statistics, John Wiley,NY

Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London

Mood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NY

Cochran W G, Sampling Techniques, 3rd Ed, John Wiley, NY

 

Sampling from normal population. Sampling distribution of various statistics, Detailed study of c ², t & F distributions. Central limit theorem, Concept of estimation, Point estimation. Characteristics of a good point estimator, methods of point estimation: method of least squares, moment and maximum likelihood. Concept of interval estimation. Methods of interval estimation. Interval estimation of mean and variance, proportion, correlation and regression coefficients.

Bayesian method of point estimation and interval estimation

Test of significance in small and large samples. Comparison of means, proportions and variances. Test of homogeneity of means and variances.

Ali A, Theory of Statistics, Vol-II

Mostafa M G, Methods of Statistics

Islam M N, An Introduction to Statistics and Probability

Roy MK. Fundamentals of Probability and Probability distributions.

Gupta and Kapoor, Fundamentals of Mathematical Statistics

Meyer A, Probability and Statistics , Addison-Wesley, USA

Mood, Graybill &Boes, Introduction to Theory of Statistics, 3^rd Ed, McGraw Hill, NY

Ross S M, A First Course in Probability, Academic Press, NY

Hogg and Tanis, Probability and Statistical Inference

 

Frequency distribution of data: Population and sample, collection and presentation of statistical data, tabulation of data, class intarvals. Frequency distribution - discrete, continuous and cumulative distributions. Histograms and frequency polygons, graphical representation of data. Statistical measures: Measures of central tendency, arithmatic mean, median, mode, geometric mean, harmonic mean, weighted average. Measures of dispersion, range, standard deviation, variance, coefficient of variation, moments, skewness, kurtosis. Correlation theory: Linear correlation, measures of correlation and its significance. Regression and curve fitting: Linear and nonlinear regression, method of least squares, curve fitting. Probability: Definition of probability and related concept, laws of probability, discrete and continuous random variable, mathematical expectations, conditional probability. Probability distribution: Binomial, poisson and normal distribution and their properties.

Barlow R J, Statistics

Chisholm J S R & Morris R M, Mathematical Methods in Physics

Hoel P G, Elementary Statistics, John Wiley, NY

Loveday, Practical Statistics and Probability

Melnyk M, Principles of Applied Statistics

Mostafa M G, Methods in Statistics, Bangladesh

Mosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USA

Spiegel M R, Theory and Problems of Statistics, McGraw Hill, NY

Topping, Observation of Errors

 

Summarization of data: Frequency distribution, Graphical representation and tabulation of statistical data.

Central tendency and dispersion: Mean, median, mode, standard deviation, mean deviation, coefficient of variation, deciles and percentiles.

Correlation and regression: Coefficient of correlation, Linear regression, Curve fitting.

Probability: Concepts of probability, Laws of probability. Probability distribution. Binomial distribution, Normal distribution.

Wonnacott & Wonnacott- Introductory Statistics, Wiley

Mostafa M G, Methods of Statistics, Bangladesh

Jhonston, J- Econometric Methods

G.D. Christian, Analytical Chemistry, John Wiley & Sons, 4^th Ed.

Vogel, Inorganic Quantitative Analysis, 4^th Ed.

 

Definition of Social Statistics Variable, Population, Sample, Tabulation and graphical representation of data. Frequency distribution. Central tendency and its different measures. Dispersion and its different measures. Correlation and its measures.

Probability, Probability distribution, Statistical tests, Drawing of different kinds of samples and estimating mean, total and proportion.

Hoel P G, Introductory Statistics

Mostafa M G, Methods of Statistics, Bangladesh

Wonnacott & Wonnacott, Introductory Statistics

 

Introduction: Definition, uses of statistics in biological science, Variables, Classification, Construction of frequency distribution, Graphical representation of data,. Central tendency, Measures of central tendency, Quantiles, Dispersion, Measures of Dispersion, Moment, Skewness and Kurtosis.

Probability: Elementary theory of probability, laws of probability, additive and multiplicative laws of probability and Bay's theorem. Random variables, probability distribution, derivation, properties and uses of Binomial, Poisson and Normal distribution to observed data.

Techniques of Sampling: The concept of statistical population and parameters Samples and random sample statistical characterization of samples. Definition and use of stadardized normal variate.

Descriptive Statistics: Calculation of the mean, variance and standard deviation, Standard deviation of the mean, Confidence limit of the mean.

Correlation and Regression: Definition, correlation coefficient, product moment correlation coefficient to measure the relationship between variables in a bi-variate distribution. Fitting simple linear regression to observed data by the method of least squares.

Hypothesis: Test of Hypothesis, type I and type II errors and level of significance, preliminary idea on t-test, F-test, Chi square test and their application. Testing hypothesis regarding population mean, equality of two means, population variance equality of two means, population variance equality of two population variances, goodness of fit and independence of two attributes in a contingency table and test of significance of correlation coefficient and regression coefficients.

Principles of experimental design: Field layout and analysis of variance in completely randomized design, randomized block design and Latin square design. Analysis of covariance in a completely randomized design.

Epidemiology: Basic concepts.

Mostafa, M G- Methods of Statistics

Steel, R D G and Torry, J H- Principles and Procedures of Statistics

Hogg, R and Graig, A- Introduction to Mathematical Statistics

 

Syllabus will be designed by course teacher.

Introduction: Definition, uses of statistics in biological science, Variables, Classification, Construction of frequency distribution, Graphical representation of data,. Central tendency, Measures of central tendency, Quantiles, Dispersion, Measures of Dispersion, Moment, Skewness and Kurtosis.

Probability: Elementary theory of probability, laws of probability, additive and multiplicative laws of probability and Bay's theorem. Random variables, probability distribution, derivation, properties and uses of Binomial, Poisson and Normal distribution to observed data.

Techniques of Sampling: The concept of statistical population and parameters Samples and random sample statistical characterization of samples. Definition and use of stadardized normal variate.

Descriptive Statistics: Calculation of the mean, variance and standard deviation, Standard deviation of the mean, Confidence limit of the mean.

Correlation and Regression: Definition, correlation coefficient, product moment correlation coefficient to measure the relationship between variables in a bi-variate distribution. Fitting simple linear regression to observed data by the method of least squares.

Hypothesis: Test of Hypothesis, type I and type II errors and level of significance, preliminary idea on t-test, F-test, Chi square test and their application. Testing hypothesis regarding population mean, equality of two means, population variance equality of two means, population variance equality of two population variances, goodness of fit and independence of two attributes in a contingency table and test of significance of correlation coefficient and regression coefficients.

Principles of experimental design: Field layout and analysis of variance in completely randomized design, randomized block design and Latin square design. Analysis of covariance in a completely randomized design.

Mostafa, M G- Methods of Statistics

Steel, R D G and Torry, J H- Principles and Procedures of Statistics

Hogg, R and Graig, A- Introduction to Mathematical Statistics

 

Syllabus will be designed by course teacher.

Statistics: Its nature and scope. Nature of statistical data. Attributes and variables, population and sample, collection and condensation of data. Frequency distribution. Graphical representation of data. Measures of location: Arithmetic mean, median, mode, geometric mean, harmonic mean, quadratic mean, quartiles, deciles and percentiles. Measures of dispersion: Range, mean deviation, standard deviation, variance, quartile deviation, coefficient of variation, moments and cumulants of a distribution, skewness and kurtosis. Regression and correlation: Bivariate data. Relationship between the variables. Methods of least squares, regression line. Correlation and regression coefficients. Rank correlation. Probability: Sample space, Event, Probability of event, Random variable, Binomial and Normal distribution; t, c ² and F distribution. Statistical Tests- Test of proportion mean, variance, correlation coefficient, regression coefficient, test for independence of attributes. Sampling:- Simple random sampling, Stratified random sampling, Systematic sampling, cluster sampling. Determination of sample size in S.R.S and Stratified random sampling.

Hoel P G, Introductory Statistics, John Wiley, NY

Johnston J. Econometric Methods

Mostafa M G, Methods of Statistics, Bangladesh

Weatherburn C E, A first Course in Mathematical Statistics

Wonnacott & Wonnacott, Introductory Statistics

Yule and Kendal, An Introduction to the theory of Statistics

Hoel P G, Introduction to Mathematical Statistics, John Wiley,NY

Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London

Mood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NY

Cochran W G, Sampling Techniques, 3rd Ed, John Wiley, NY

 

Concept and scope of sampling, sampling versus census, steps of survey, questionnaire, pilot survey, sampling and non-sampling errors, bias and precision, determination of sample size. Probability and non-probability sampling , study of different sampling design, simple random sampling, stratified random sampling, systematic sampling, cluster sampling. Estimation of population total, mean, proportion and their standard errors. Ratio and regression methods of estimation. Basic ideas of two stage, three stage and double sampling.

Cochran W G, Sampling Techniques, 3^rd Ed, John Wiley, NY

Islam M.N., An Introduction to Sampling Methods, Book World, Dhaka.

Desraj, Sampling Theory

Kish L, Survey Sampling

Sukhatme P V, Sampling Theories and Surveys with Applications

 

Drawing samples from population under different sampling designs. Estimation of population mean, total, proportion and their standard errors.

Bivariate quantitative data: Bivariate normal distribution, marginal distribution, conditional distribution, expected values. Regression and correlation. Method of least squares, regression line, correlation and regression coefficients, rank correlation and correlation ratio, regression curves from bivariate distributions.

Multiple linear regression: Three variable regression, estimation of parameters and standard error, separation of effects, multiple and partial correlation. General linear regression model, OLS estimators, Gauss-Markoff theorem, estimation of error variance, coefficient of determination, hypothesis testing.

Polynomial regression: Concepts of polynomial regression, estimating and testing in polynomial regression model, finding the degree of polynomial.

Residual analysis: Basic concepts, analysis of residuals by graphs, Lack of fit of Model adequacy.

Chatterjee S & Price P, Regression Analysis by example, John Wiley, NY

Draper N R & Smith H, Applied Linear Regression, 2^nd Ed, John Wiley, NY

Graybil F A An introduction to Linear Statistical Models, Mc Graw Hill, NY

Johnston J, Econometric Methods, Mc Graw Hill, NY

Koutsoyiannis A, Theory of Econometrics, Mac Milan, London

Montogomery D C & Peck E, An Introduction to Linear Regression Analysis, John Wiley, NY

Seber G A F, General Linear Regression Analysis , Wiley & Sons Ltd, NY

Weisberg S, Applied Linear Regression, second edition John Wiley NY

 

Calculation of correlation coefficient, regression coefficient, partial correlation, multiple correlation, fitting of multiple regression model, separation of effects and tests of hypothesis, fitting of polynomial and analysis of residuals and test for lack of fit.

Group A: Advanced Calculus

Improper integral, gamma and beta functions, their incompleteness and other properties, functions of several variables and limit and continuity, Taylor’s expansion of such functions, maxima and minima of functions of more than one variables, Lagrange’s multipliers, multiple integral, Jacobian of transformation, Dirichlet integral and its extension, Laplace transformation, concepts of fourier series.

Group B: Differential equations

Definition, solution of differential equations, basic theory of linear differential equation, equations of the first order and their solution, homogeneous differential equations, linear differential equations of the second and higher order and their solution.

Ayres F, Differential Equations

Edward, Differential and Integral Calculus

Maxwell E H G, Analytical Calculus, Vol-II & Vol-III

Piaggio H T H, An Elementary Treaties of Differential Equations and their Application

Ross S L, Differential Equations

Widder, Advanced Calculus

 

Theory: Basic ideas of analysis of variance, One-way classification with equal and unequal observations per cell, Two-way and three-way classification with equal number of observations per cell, Experimental error and interpretation of data, Analysis of variance with fixed effect random effect and mixed effect models, Model adequacy checking.

Multiple comparison: Introduction, Tukey’s W-test, Newman-Keuls several range test, Duncan multiple range test, Dunnett’s test.

Experimental designs: Introduction, Principles of experimental design, uniformity trial, choice of size and shape of plots and blocks, estimation and analysis of completely randomized design, randomized block design and Latin square design. Orthogonality of designs. Analysis of replicated Latin square design, Graceo-Latin square design.

Factorial experiment: Introduction to factorial designs, factorial experiment for two and three levels up to n factors.

Cochran WG & Cox DR, Experimental Design, John Wiley & Sons, Inc.

Montgomery, D.C., Design and Analysis of Experiments, 4^th Ed, Wiley

Kempthrone, O., The Design and Analysis of Experiment, Wiley

Das, M.N. and Giri, N.C., Design and analysis of Experiments, Wiley Eastern, New Delhi

Sheffe, H., The Analysis of Variance, John Wiley & Sons, Inc., New York.

Winer, B.J., Statistical Principles in Experimental Design, 2^nd Ed., McGraw-Hill Company, Ltd.

Mann, H.B., Analysis and Design of Experiments, Dover publications, New York

Davis, O.L., Design and Analysis of Industrial Experiments, Oliver & Boyd, Ltd. London

Bhuyan, K.C., Porikhanar Naksha and Vedanka Bishlasion

Bhuyan, M.R., Experimental Design

Analysis of one-way classification with equal and unequal number of observations per cell, analysis of two and three-way classification with single and several observations per cell, analysis of completely randomized design, randomized block design and Latin square design with missing observation, Analysis of replicated Latin square design and Graceo-Latin square design, Analysis of factorial experiments with two and three levels up to n factors, Multiple comparison.

Interpolation and extrapolation, Shifting operators, difference operators and differential operator and their relationships. Newton’s interpolation formulae, Lagrange’s formulae, Newton’s divided difference formulae, central difference formulae (Stirling’s and Bessel’s). Relationship between divided difference and simple difference. Inverse interpolation formulae. Numerical differentiation. Numerical integration by different formulas. Numerical solution of equations by various methods. Convergence of these methods and their inherent errors. Numerical solution of simultaneous linear equation, solution by determinants, by inverse matrices, by iteration and by successive elimination of the unknowns.

Complex functions, elementary single and many valued functions of complex variables, differentiable functions, analytical functions, Cauchy’s theorem for simple contours. Taylor’s theorem, Laurent’s theorem, Liouville’s theorem, different types of singularity, Cauchy’s residue theorem, evaluation of integral by contour integration.

Churchill, Introduction to Complex Variable and Applications

Freeman H, Finite Difference for Actuarial Students

Mactobeat, Complex Variable

Phillips, Complex Variable

Scarborough J B, Numerical Analysis

Shastrey, Numerical Analysis

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Frequency distribution: Measures of central tendency, dispersion; moments, skewness and Kurtosis. Correlation and Regression: Bivarate data, correlation and regression coefficients, regression. Probability: Sample space event, probability of events, theorem, of total and compound probability, conditional probability, bayes theorem. Random variable: Probability function, distribution function, joint, marginal and conditional probability function, expectation and moment generating function. Parent Distributions: Binomial, poisson, negative bionomial, normal and exponential distribution. Sampling Distributions: c ² , t and F distributions. Test of Hypothesis: Test for population, mean, variance, correlation coefficient and regression coefficients.

Spiegel M R, Theory and Problems of Statistics

Hoel P G, Elementary Statistics

Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London

Mood, Graybil & Boes, Introduction to the Theory of Statistics, 3rd Ed, McGraw Hill, NY

Mostafa M G, Methods of Statistics

Milnyk M, Principles of Applied Statistics

Barlow R G, Statistics

Loveday, Practical Statistics and Probability

Mosteller, Rourk & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USA

Goon A M & Gupta M N, Fundamentals of Statistics, Vol-I

 

Sampling from normal and nonnormal populations. Distribution of various statistics, distribution of linear functions of normal variates. Detailed study of c ²,t & F distributions. Concept of estimation. Point estimation. Characteristic of a good point estimator, methods of point estimation. Concept of interval estimation. Methods of interval estimation. Interval estimation of mean and variance of normal distribution. Test of significance in small and large samples. Comparison of means, proportions and variance. Test of homogeneity of variances, Test for r x c contingency tables.

Hoel P G, Introduction to Mathematical Statistics

Hogg and Craig, Introduction to Mathematical Statistics

Mood, Graybill and Boes, Introduction to the Theory of Statistics

Mostafa M G, Methods of Statistics, Bangladesh

 

Point estimation: Basic concepts, principles of point estimation. Method of point estimation: Method of maximum likelihood, method of moments, method of least squares, method of minimum chi-squares, method of minimum variance. Bayes method. Properties of point estimators: Unbiasedness, sufficiency, consistency, efficiency, asymptotic efficiency. Cramer-Rao lower bound. Interval estimation: Concept of central and non-central confidence interval. Confidence interval for parameters of normal, binomial and poisson distribution. Large sample confidence interval. Parametric tests: Basic concepts, Simple hypothesis & composite hypothesis, critical region, best critical region, Neyman-Pearson fundamental lemma, most powerful tests, uniformly most powerful critical region, UMP tests. Non-parametric methods.

Beaumont W, Intermediate Mathematical Statistics ,2nd Ed, Cambridge University Press, London

Cox D R & Hinkley D V, Theoritical Statistics, Chapman and Hall, London

Graybill F A, Introduction to Linear Statistical Models, McGraw Hill, NY

Hoel P G, Introduction to Mathematical Statistics, 4^th Ed, Wiley, NY

Hogg R V and Chaig A T, Introduction to Mathematical Statistics, Macmillan, NY

Mood, Grabyl & Boes, Introduction to the Theory of Statistics, 3rd Ed, McGraw-Hill, NY

Kendall, M G & Stuart A, The Advance Theory of Statistics, Vol-2, 4th Ed, Charles-Grifin, London

Lindley, Statistical Inference

Zacks S, Theory of Statistical Inference, John Wiley, NY

Hollander, M & Wolf, D.A.- Nonparamatric Statistical Methods

 

Drawing sample from univariate and bivariate normal distributions. Point estimation of parameters of univariate distributions by method of moments, method of maximum likelihood and method of least squares. Construction of confidence intervals for parameters of normal distribution, construction of large sample confidence interval for parameters of binomial and poisson distribution. Tests of hypothesis regarding parameters of univariate and bivariate normal distributions, Tests of hypothesis regarding parameters of discrete and continuous distributions. Calculation of best critical region and drawing power curve. Nonparametric tests.

Historical background and evaluation of computer and its development, types of computer according to size and function, peripheral devices of computer system, software and hardware knowledge, idea about RAM, ROM, compiler and interpreter.

Introduction to operating systems (DOS and Windows), word processing, spreadsheet and database. Statistical graphs using computer.

Fortran: Fundamental programming concepts, variables, arrays, statement, assignment, loops, conditions, algorithms and flowcharts, recursion, procedures and functions, calculation of different measures of central tendency, dispersion, skewness, kurtosis, correlation and regression. one dimensional function minimization, solution of simultaneous linear equations, convergence.

Ellis, FORTRAN 77 Programming

Gorre and Stubs, Computers and Information System, McGraw Hill, NY

Kumar R, Programming with FORTRAN 77

Meissner/Organick, FORTRAN 77

Microsoft Corporation, MS-DOS User’s Guide

 

Calculation of different measures of central tendency, dispersion, skewness, kurtosis, correlation and regression. Factorials and binomial coefficients, summation of series, one dimensional function minimization. Statistical graphs using computer.

Multiple regression and linear estimation: Generalized and weighted least squares. Gauss-Markov Aitken’s theorem. Estimation and tests for linear restriction. Heteroscedasticity: Detection and testing for heteroscedasticity, Estimation with heteroscedestic disturbances. Multicollinearity: Concept of exact and near multicollinearrity, Estimable functions, Effects of multicollinearity, Detection and remedial measures of multicollinearity. Autocorrelation: Sources and consequences of autocorrelation, Tests for autocorrelated disturbances, Estimation of parameters. Dummy variables: General concepts, Use of dummy variables in regression analysis. Errors in variables: Basic ideas, Consequences and tests for error in variables, Estimation of parameters. Binary Models, Selection of variables, outliers. Introduction to simultaneous equation models.

Chatterjee, S. and B. Price : Regression Analysis by Example, John Wiley & Sons, New York.

Montgomery, D.C. and E.A. Peck : Introduction to linear Regression Analysis. John Wiley & Sons, New York.

Gujarati, Damodar N.: Basic Econometrics, 3d ed., Mc Graw-Hill, New York.

Maddala, G.S.: Econometrics, Macmillan, New York.

Griffiths W.E. et al : Learning and practicing econometrics, John Wiley & Sons, New York.

Koutsoyiannis, A.: Theory of Econometrics, 2d ed. Macmillan, London

Johnston, J. : Econometric Methods, McGraw-Hill, New York

Judge, George G., et al : The Theory and Practice of Econometrics, John Wiley & Sons, New York.

Draper, N.R. and H. Smith : Applied Regression Analysis, 2d ed., John Wiley & Sons, New York.

Neter, J., W. Wasserman and M.H. Kunter : Applied Linear Regression Models, Richard D. Irwin, Inc., Homewood, Illinois.

 

Fitting of multiple regression models, Tests of parameters of a multiple regression models, Separation of sum of squares. Detection and tests for multicolllnearity, Fitting of model when multicollinearity is present. Tests of autocorrelation and estimation of parameters with autocorrelated disturbances. Fitting of dummy variables model and tests.

Simulation: Introduction, concept and meaning of simulation studies and modeling, basic nature of simulation, discrete and continuous simulation, simulation of random numbers, random number generation, random variate generation, series and their convergence, polynomial and relational functions, incomplete gamma function, incomplete beta function, error function, chi-square probability function, cumulative probability function, exponential integrals, Student’s t distribution, F distribution, cumulative binomial distribution, hypergeometric distribution, simple Monte Carlo integration, multidimensional function minimization.

Statistical packages: SPSS – introduction, operation commands, data definition, manipulation commands and procedure commands like LIST, DESCRIPTIVES, FREQUENCIES, CROSSTABS, T-TEST, ANOVA, REGRESS, etc. SAS – structure of a SAS program, data step, data management and other facilities in the DATA step, saving and recalling SAS programs, input statement, SAS permanent data sets, PROC steps – print, sort, format, means, univariate, tabulate, corr, summary, contents, transpose, freq, ttest, anova, glm, reg, plot, SAS graphics.

Ellis, FORTRAN 77 Programming

SAS, Reference Manual: Language Guide for Personal Computers, Procedures Guide, STAT User’s Guide

Chowdhury A K, SAS Handout

Press W H et al, Numerical Recipes in Fortran – The Art of Scientific Computing, 2^nd Ed, Cambridge University Press

Ripley D Brian, Stochastic Simulation, Wiley, NY

Ross M Sheldon, Simulation, 2^nd Ed, Academic Press, London

Rubinstein Y Reuven, Simulation and the Monte Carlo Method, Wiley, NY

SPSS/PC Reference Manual

 

Getting into SAS, the data, using existing data files, splitting data sets, if conditions, joining data sets, merging data sets, updating and selecting variables, saving program, labeling and formatting, permanent data set, summary statistics, plotting data, making new SAS data sets, analysis of randomized block design, treatment comparisons, analysis of non-orthogonal designs, split-plot analysis, multiple regression in SAS – all possible regressions, sequential methods, model diagnostics, comparisons of regressions, xy plot, bar chart, pie chart.

Basic concept of demography: Demography and population studies, nature and scope of demography, importance of demography, vital statistics, demographic characteristics in Bangladesh.

Sources of demographic data: Census, survey, population register, sample vital registration system in Bangladesh. sources and types of errors in demographic data, detection and reduction of errors, the stock and flow data. Introduction to demographic methods: Rates, ratios, proportions, cohort, age-sex composition, rates of vital events, errors in age data, detection of errors in age data, population pyramid, concept of population change, rates of population growth and its different measures, balancing equation, history of population growth in Bangladesh. Fertility and its measures: Crude birth rate, general fertility rate, age-specific fertility rate, total fertility rate, sex ratio, child woman ratio, cohort fertility rate, marital fertility rate, number of children ever born, cumulative fertility, fertility differentials, gross and net reproduction rate.

Mortality and its measures: Crude death rate, age-specific death rate, live birth, still birth, neo-natal, infant death rate, infant and child mortality, adjusted infant mortality. Nuptiality and its measures: Concept of marriage, divorce, separation, estimation of mean and median age at marriage, estimation of singulate mean age at marriage, nuptiality table. Standardisation of rates and ratios: Concept, need and methods of standardisation. Life table: Definition, importance and classification, function, construction and application, force of mortality. Migration: Definition, types of migration, effect of migration, various measures of migration. Population projections: Definition, importance, various methods of projection, application and use of different methods of projections with special reference to Bangladesh. Growth curve: Fitting of exponential, Gompertz and logistic curve.

Barclay J, Techniques of Population Analysis (John Willey & Sons) NY

Spiegelman, Introduction to Demography

Cox D R, Demography

Kpdekpo G, Demographic Analysis in Africa

Chiang CL, The Life Table and its Application, John Wiley, NY

Bogue D, Principles of Demography

Bartlett M S, Stochastic Population Model in Ecology and Epidemiology

Shyrock, Siegel et al, Methods and Materials of Demography

Pollard A H, Farhat Yusuf & Polard G N, Demography, Willey Eastern, India

Goon A M & Gupta M N, Fundamental of Applied StatisticsVol. II

Keyfitz N, Introduction to Mathematics of Population, Addison-Wesley

Linger J W, A Handbook of Population Analysis, Part A

Bather R W, Mortality Table Construction

Publications of B B S, M I S, Population Division Unit of Planning Commission

Journals - Demography, Population Studies

 

Calculation of various rates, ratios, proportions for demographic data (CBR, CDR, GRR, NRR, TER, SR etc) construction of population pyramid, calculation of various measures of population growth, construction of life tables (complete and abridge), calculation of various measures of population growth, construction of life tables (complete and abridge), calculation of standardised death rate and ratios, fitting of growth curves.

Elements of linear programming: Formulation of linear programming problems, theorems of linear programming. Methods of solution: Graphical method, simplex method, revised simplex method, primal-dual problems and their solutions, degeneracy and cyclical problems, sensitivity analysis. Integer linear programming: Problem formulation, methods of solution, cutting plane algorithm, branch and bound algorithm, transportation problem. Game theory: Two person zero sum games. Equivalence of two person zero sum game and a linear programming problem, methods of solution of the game problems.

Gass S I, Linear Programming

Taha H A, Introduction to Operation Research

Vajda S, Mathematical Programming

Hadley G, Linear Programming

 

Formulation and solution of linear programming and integer linear programming problems, solution of two-person-zero sum games.

Attributes of consumer behavior: The lognormal distribution & example. Engel curve model & example, lognormal demand curves.

Distribution of personal income: Empirical distribution, Pareto`s law, Lorenz curve, concentration ratio, the lognormal distribution, Stochastic model of income distribution.

Time series: General ideas, decomposition, trend, seasonality. Different methods of finding trend & seasonality. Index number: Problems in construction of index numbers, purpose of the index, price index, quantity index, value index, tests of index numbers, cost of living index, family budget method.

Theory of production: Production function, concepts of average productivity, marginal productivity, marginal rate of technical substitution, efficiency of production, factor intensity, returns to scale and

homogeneity of production function, production possibility curve, cost function, minimizing cost for a given level of output, maximization of profit subject to constraint cost, maximization of profit for a given output, Cobb-Douglas production function, constant elasticity substitution (CES) production function.

Dynamic economics: Cobweb model, Harrod-Domar model of economic growth, natural and non-natural technical change, two sector growth model.

Theory of consumer behavior: An individual consumer’s utility function and his budget constraint, perfect competition, first and second order conditions for consumer’s equilibrium, demand function, price, income and cross elasticities of demand.

Input output analysis: Meaning of input output, main features of input output, assumptions, Leontiefs static and dynamic model, Limitations, importance and application of the analysis.

Allen R G D, Mathematical Economics, Mc-Millan, London

Allen R G D, Microeconomic Theory

Bridge J L, Applied Econometrics, North Holland, Amsterdam

Chatfield, Time Series Analysis

Chiang, Fundamental Methods of Mathematical Economics, 3rd ED, McGraw Hill, NY

Cramer J S, Empirical Econometrics

Henderson & Quandt, Microeconomic Theory-A Mathematical Approach, 2nd Ed, Mc Graw Hill, NY

Kendal M G, Time Series

Koutsoyiannis A, Modern Microeconomics

Klein L R, An Introduction to Econometrics

Lange O, An Introduction to Econometrics

Leotief W W, The Structure of American Economy

Watson D S, Price Theory and its Uses

 

Construction of price, quantity, value index and cost of living index, determination of trend, seasonal variation and cyclical fluctuation by various methods, periodogram and correlogram analysis, fitting of Pareto and lognormal distribution, Lorenz curve and Gini`s concentration ratio, estimation of production function.

Computation of Engel`s elasticities.

Industrial statistics: Assignable and non-assignable causes of variations, problems and principle of statistical quality control, control charts for variables, control charts for attributes, special control charts.

Acceptance sampling procedure: Introduction, acceptance sampling by attributes, consumer’s and producer’s risk, acceptance sampling by variables, continuous sampling plan. Sequential sampling O C, A S N, S P R T.

Educational statistics: Introduction, education and psychology, scaling, measurement of different scores, IQ, Planning reliability, validity of tests.

Official statistics: Questionnaire, schedule and data collection, coding, editing and tabulating plans. Official statistics of Bangladesh with special reference to population, economy, critical evaluation of the sources and their limitations.

Banks J, Principles of Quality Control

Duncan A J, Quality Control and Industrial Statistics

Grant, Statistical Quality Control

Guilford J P, Educational Statistics and Psychometric Methods

Guilford J P & Bejamin F, Fundamental Statistics in Psychology and Education, 6^th Ed

Wordsworth, Stephans & Godfrey, Modern Methods for Quality Control and Improvement

Publications of B B S, Bangladesh Bank, NIPORT and other organizations.

 

Different types of control charts, OC curve for single sampling and double sampling plans, calculation of AOQ and AOQL for single sampling, double sampling and continuous sampling plans. OC and ASN functions for multiple sampling plans. Calculation of different scores and their standardization, calculation of IQ.

Review: Introduction and review of analysis of variance, Contrast, Orthogonal contrasts, Discussion of models related with analysis of variance, test of additively of models, Comparison of treatments, Model adequacy: Variance-Stabilizing transformation.

Linear estimation, Estimable parametric functions and conditions for estimability, Methods of estimation for analysis of variance models, Solution of normal equations for less than full rank, Optimality properties of least squares estimators, Test of hypothesis.

Factorial experiment: Confounding, total, partial and balanced confounding in two and three levels up to n factors, Fractionally replicated factorial experiment and mixed factorial experiment.

Split-plot design, analysis of split-plot design, Split-split-plot design, analysis of split-split-plot design, Strip-plot design, analysis of strip-plot design, Nested design, analysis of nested design.