B.Sc (Honors) in Statistics
Session:
2005-2006 to 2008-2009
The B.Sc. (Honours) course in Statistics
shall comprise of the courses on Statistics, Mathematics,
Economics, Computer Science, English and Bengali. The course is
spread over four academic years. Each year is divided into two
semesters. Final examinations are held at the end of each semester
and there are also incourse examinations. A student is to
successfully complete 140 credit hours of courses to obtain the B.
Sc (Honours) degree.
ENG-103 and ENG-104 are alternative to
BNG-101 and BNG-102 (L) .
There will be a
distribution of marks for a course in class participation,
assignments and mid semester examination and final examination as
follows.
Class
participation :
10%
Assignments
and mid-semester examination
: 20%
Final
examination :
70%
The grading
system consists of Letter grading, corresponding Grade point and
calculation of Grade point average (GPA). Letter Grade and
corresponding Grade point will be awarded as follows:
|
Numerical
Grade |
Letter
Grade |
Grade Point |
|
80% or
above |
A+ |
4.00 |
|
75% to less
than 80% |
A |
3.75 |
|
70% to less
than 75% |
A- |
3.50 |
|
65% to less
than 70% |
B+ |
3.25 |
|
60% to less
than 65% |
B |
3.00 |
|
55% to less
than 60% |
B- |
2.75 |
|
50% to less
than 55% |
C+ |
2.50 |
|
45% to less
than 50% |
C |
2.25 |
|
40% to less
than 45% |
C- |
2.00 |
|
Less than
40% |
F |
0.00 |
|
Incomplete |
X |
----- |
The
distribution of courses for respective academic years and semester
is given below along with the details of syllabus of the courses:
First Year:
Semester I
First Year:
Semester
II
Second Year:
Semester
I (3rd Semester)
Second Year:
Semester
II (4th Semester)
Third Year:
Semester I (5th
Semester)
Third Year:
Semester
II (6th Semester)
Fourth Year:
Semester I (7th Semester)
Fourth Year:
Semester II (8th Semester)
Detailed Syllabus
STA-121 PROBABILITY
Theory:4
Hours/Week, 4 Credits
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
Books
Recommended:
Meyer A,
Probability and Statistics , Addison-Wesley, USA
Feller W,
Introduction to Probability Theory and its Applications, Vol-1, 3rd
Ed, John Wiley, NY
Mood, Graybill
&Boes, Introduction to Theory of Statistics, 3rd Ed,
McGraw Hill, NY
Mosteller,
Rourke &Thomas, Probability with Statistical Applications, 2nd
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, 3rd Ed, Academic
Press, NY
Roy MK.
Fundamentals of Probability and Probability distributions.
Islam, M.N.,
Introduction to Statistics and Probability, 3rd Edition
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STA-122 PRINCIPLES OF
STATISTICS
Theory: 4
Hours/Week, 4Credits
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.
Books Recommended:
Bulmer M G,
Principles of Statistics, 2nd Ed, Oliver and Boyd,
Edinburgh
Hoel P G,
Introduction to Mathematical Statistics, 5th Ed, John
Wiley, NY
Moore P.G,
Principles of Statistical Techniques, 3rd Ed, Cambridge
University Press, London
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
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
STA-122L
PRINCIPLES OF STATISTICS (Lab)
Lab:4Hours/Week,2
Credits
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.
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MAT-101A ALGEBRA
2Hours/Week, 2
Credits
Review
of permutation and combination.
Complex numbers:
Definition of complex numbers and their properties. DeMoivre’s
theorem (for integral and rational exponents) and its applications.
Inequalities:
Cauchy, Holder, Chebychev and Jensen’s inequality.
Determinants:
Elementary idea of determinant, solution of system of equations by
determinant.
Theory of equations:
Polynomials,
division algorithm, fundamental theorem of algebra, multiplicity of
roots, relation between roots and coefficients of algebratic
equations, Descartes rule of signs.
Books Recommended:
Bemard & Child, Algebra
Hall & Knight,
Higher Algebra
Rahman, M. A.,
Algebra and Trigonometry
ENG-101 ENGLISH LANGUAGE-I
Theory: 2
Hours/Week, 2 Credits
ENG-102L ENGLISH
LANGUAGE-I (Lab)
Lab:
2 Hours/Week, 1 Credit
Syllabus will
be designed by course Teacher
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STA-123 THEORY OF STATISTICS
Theory:
4Hours/Week, 4 Credits
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.
Books Recommended:
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
STA-123L THEORY OF
STATISTICS (Lab)
Lab:4 Hours/Week,
2 Credits
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.
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MAT-103A CALCULUS
4 Hours/Week, 4
Credits
Group-A:
Differential Calculus
Functions of a
real variable and their graphs. Limits continuity and derivative.
Physical meaning of derivatives of a function, higher derivatives,
Liebnitz’s theorem. Rolle’s theorem, Mean Value theorem. Taylor’s
theorem. Taylor’s and Maclaurim’s series without proof. Maximum and
minimum of a function, functions of two and three variables, partial
and total derivatives, concavity and convexity of a function.
Trangents and normals.
Group-B: Integral Calculus
Physical
meaning of integration of a function, evaluation of indefinite
integral, definition of Reimann integral, fundamental theorem of
integral calculus and its application to definite integral, double
and triple integration, application of integration in finding
lengths, areas and volumes.
Books Recommended:
Das & Mukherjee,
Differential Calculus
Das & Mukherjee,
Integral Calculus
Thomas &
Finney, Calculus and Analytic Geometry
Tiemey,
Calculus and Analytic Geometry
Swokosky,
Calculus Analytic Geometry
Edward,
Differential and Integral Calculus
[top of the page]
MAT-109
LINEAR ALGEBRA
4 Hours/Week, 4
Credits
Definition of
matrix, different types of matrices, addition and multiplication of
matrices, adjoint and inverse of a matrix, Cramer’s rule and its
application.
Elementary row
operations and Echelon forms of matrices, rank, row rank column rank
of a matrix and their equivalence, use of rank and Echelon forms in
solving system of homogeneous and non homogeneous equations.
Vector space
and subspace over real and direct sum, linear combination, linear
dependence and independence of vectors, basis and dimension of
vector space, quotient space and isomorphism theorems. Linear
transformations, kemel, rank and nullity, nonsingular
transformations and matrix representation, changes of basis.
Eigenvector,
eigenvalues, characteristic equations and Cayley-Hamilton theorem.
Similar
matrices, canonical forms, orthogonal and hermitian matrices, inner
product, orthogonal vectors, orthogonal bases, Gram-Schmidt
orthogonalization process.
Bilinear and
quadratic forms.
Books Recommended:
Hamilton A G,
Linear Algebra
Ayres F,
Martices
Kolman B,
Elementary Linear Algebra
Bering E D,
Linear Algebra and Matrix Theory
Lipschutz S,
Linear Algebra
Morris A O,
Linear Algebra
Khanna M I,
Linear Algebra
Rahman M A,
College Linear Algebra
BNG-101 BENGALI LANGUAGE
Theory:2Hours/Week, 2Credits
Syllabus
will be designed by course Teacher
BNG-102L BENGALI LANGUAGE
(Lab)
Theory:
2Hours/Week, 1 Credit
Syllabus
will be designed by course Teacher
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ENG-103 ENGLISH LANGUAGE-II
Theory: 2
Hours/Week, 2Credits
Syllabus will
be designed by course Teacher
ENG-104L ENGLISH
LANGUAGE-II (Lab)
Theory: 2
Hours/Week, 1Credit
Syllabus will
be designed by course Teacher
[top of the page]
ECO-101 PRINCIPLES OF
ECONOMICS-I
4
Hours/Week, 4Credits
Introduction:
Definition and scope of Economics, basic concepts and tools used in
economic problems. Production Possibility Frontier-positive versus
normative economics, microeconomics versus macroeconomics, measuring
economic variables.
Demand, supply and the market:
Concepts of demand and supply, market equilibrium, law of demand,
demand and supply schedules and curves, determinants of demand and
supply-shifts in demand and supply curves, applications of demand
and supply, price ceiling and price floor etc. Own price, cross
price and income elasticity of demand and point and arc elasticity
of demand, application of elasticity concepts.
Economics of consumers behavior:
Utility analysis, Consumers surplus paradox of value, law of
diminishing marginal utility, cardinal and ordinal utility,
consumers preference, indifference curve analysis: properties of
indifference curves, goods, bads and neutrals and different shapes
of indifference curves, budget constraint, consumers, equilibrium,
changes in income and prices, complements and substitutes,
elementary concepts of income and substitution effects of a price
change.
Economics of the firm:
Production and costs, production function. Total, average and
marginal product, law of diminishing returns, stages of production,
short run and long run production and cost concepts and relevant
graphical analysis, isoquant, isocost producer’s equilibrium,
returns to scale.
Theory of business organization:
Business firm and the market; why do firm exist, objectives of the
firm, different types of business firm and their advantages and
disadvantages, financing corporate activity.
Market:
Taxonomy of market, perfect competition and monopoly: price and
output determination.
Pricing of
factors of production: Concepts of wage, interest rate, rent and
profit determination.
Books Recommended:
Amold R A,
Economics, West Publishing Company
Ferguson &
Gould, Microeconomic Theory
Fisher S,
Dronbusch R& Schaualansee R, McGraw Hill, 2nd Ed
Samuelson P A &
Nordhaus W, Economics, McGraw Hill, 13th Ed
A.
Kautsoyiannis: Modern Microeconomic; Macmillan 1979
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STA-221 SURVEY METHODS
Theory: 4 Hours/ Week, 4 Credits
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.
Books
Recommended:
Cochran W G,
Sampling Techniques, 3rd 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
STA-221L SURVEY METHODS
(Lab)
Lab: 4Hours/Week,
2 Credits
Drawing samples from population under
different sampling designs. Estimation of population mean, total,
proportion and their standard errors.
[top of the page]
STA-222
REGRESSION ANALYSIS
Theory: 4
Hours/Week, 4 Credits
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.
Books Recommended:
Chatterjee S &
Price P, Regression Analysis by example, John Wiley, NY
Draper N R &
Smith H, Applied Linear Regression, 2nd 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
STA-222L
REGRESSION ANALYSIS (Lab)
Lab: 4 Hours/Week,
2 Credits
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.
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MAT-207 ADVANCED CALCULUS AND DIFFERENTIAL EQUATIONS
3 Hours/Week, 3
Credits
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.
Books
Recommended:
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
[top of the page]
STA-223
DESIGN AND ANALYSIS OF EXPERIMENTS-I
Theory:4Hours/week, 4 Credits
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.
Books Recommended:
Cochran WG &
Cox DR, Experimental Design, John Wiley & Sons, Inc.
Montgomery,
D.C., Design and Analysis of Experiments, 4th 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, 2nd 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
STA-223L DESIGN AND ANALYSIS OF EXPERIMENTS-I (Lab)
Lab:4Hours/week, 2 Credits
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.
[top of the page]
MAT-208
NUMERICAL METHODS AND COMPLEX VARIABLE
4Hours/Week, 4 Credits
Group-A:
Numerical Methods
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.
Group-B:
Complex Variable
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.
Books
Recommended:
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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[top of the page]
MAT-209 REAL ANALYSIS
4 Hours/Week, 4 Credits
Sets:
Function, relation, equivalence relation, real value function, open
set, dense set, countability, compact and connected sets, monotonic
class of sets, additive class of sets.
Sequence:
Convergence of sequence, monotonic sequence, upper limit and lower
limit.
Infinite Series:
Meaning of sum, series of positive terms, alternative series,
absolute and conditional convergence, test for convergence.
Limit Points:
Bolzano-Weierstrass theorem, properties of continuous function,
uniform continuity Hine-Borel theorem.
Derivatives:
Roll’s theorem, mean value theorem and Taylor’s theorem with
remainder in Lagrange’s and Cauchy’s form, expansion of functions.
Power series:
Interval and radius of convergence, differentiation and integration
of power series, Abel’s continuity theorem.
Riemann Integral:
Definition of Riemann integration, fundamental theorem and mean
value theorem of integral calculus, improper integral and their test
for convergence.
Books
Recommended:
Rudin W, Principles of
Mathematical Analysis
Apostal T,
Mathematical Analysis
Hardy G H, A
Course on Pure Mathematics
Bartle, Real
Analysis
Hobson E. The
Theory of functions of a Real Variable and Theory of Fourier Series
Phillips, A
Course Analysis
Burkill K G, A
First Course in Mathematical Analysis
Binmore M N,
Mathematical Analysis
Khanna M L,
Real Analysis
Chatterjee P N,
Real Analysis
[top of the page]
ECO-201 PRINCIPLES OF
ECONOMICS-II
4 Hours/Week, 4 Credits
Introduction to macroeconomics:
Definition of macroeconomics, macroeconomic performance.
Measuring national product and
national income:
GNP: concept and measurement, GNP and national income, national
income and personal disposable income, GNP and spending, nominal and
real GNP; GNP as a measurement of welfare.
Determination of national income and
investment:
The circular flow, components of aggregate demand and planned
spending, aggregate demand, equilibrium output, changes in
equilibrium output, the multiplier, investment.
Money and banking:
Definition and functions of money, different kinds of money.
Quantity Theory of money. Banking-Goldsmith banking, modern banking,
commercial banks and credit expansion, money and near moneys.
Central banking and monitory system:
Functions of central bank, money supply, open market operations,
money multiplier, high powered money and the money stock;
independence of central bank.
Taxes and government expenditure:
Principles of taxation, types of taxation, heads of government
expenditure.
Budget and fiscal policy:
The government in circular flow, objectives of the fiscal policy.
Inflation:
Concepts, anticipated and unanticipated inflation, costs of
inflation, money and price level; Demand pull vs cost push
inflation.
International trade:
Concepts of absolute and comparative advantage, terms of trade,
economics of protection, tariff & quota, arguments for and against
protection.
Books Recommended:
Amold R A, Economics
Fisher S,
Dorbusch R & Schmalensee R, Economics, 2nd Ed, McGraw Hill, N Y
Luckett D G,
Money and Banking, 3rd Ed, McGraw Hill, N Y
Samuelson PA &
Nordhaus W, Economics 13 th Ed, McGraw Hill, N Y
Ruffin &
Gregory, Macroeconomics
Wonncott P &
Wonnacott R, Economics 3rd Ed, McGraw Hill, N Y
[top of the page]
STA-321
STATISTICAL INFERENCE
Theory: 4
Hours/Week, 4 Credits
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.
Books
Recommended:
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, 4th 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
STA-321L STATISTICAL
INFERENCE (Lab)
Lab: 4 Hours/Week,
2 Credits
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.
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STA-322 STATISTICAL
COMPUTING-I
Theory:
2Hours/week, 2 Credits
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.
Books
recommended:
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
STA-322L
STATISTICAL COMPUTING-I (Lab)
Lab: 4Hours/week,
2 Credits
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.
[top of the page]
STA-323
ECONOMETRICS
Theory:4Hours/week, 4 Credits
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.
Books
recommended:
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.
STA-323L
ECONOMETRICS (Lab)
Lab:4Hours/week, 2
Credits
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.
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STA-324
STATISTICAL COMPUTING-II
Theory: 3
Hours/week, 3 Credits
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.
Books
recommended:
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, 2nd Ed, Cambridge University Press
Ripley D Brian,
Stochastic Simulation, Wiley, NY
Ross M Sheldon,
Simulation, 2nd Ed, Academic Press, London
Rubinstein Y
Reuven, Simulation and the Monte Carlo Method, Wiley, NY
SPSS/PC
Reference Manual
STA-324L
STATISTICAL COMPUTING-II (Lab)
Lab: 4Hours/Week,
2 Credits
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.
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STA-325 DEMOGRAPHY
Theory: 4
Hours/Week, 4 Credits
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.
Books
Recommended:
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
STA-325L DEMOGRAPHY (Lab)
Lab: 4
Hours/Week, 2 Credits
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.
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STA-326 LINEAR PROGRAMMING
Theory:3
Hours/Week, 3 Credit
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.
Books
Recommended:
Gass S I, Linear Programming
Taha H A,
Introduction to Operation Research
Vajda S,
Mathematical Programming
Hadley G,
Linear Programming
STA-326L LINEAR
PROGRAMMING (Lab)
Lab: 2Hours/Week,
1 Credit
Formulation and
solution of linear programming and integer linear programming
problems, solution of two-person-zero sum games.
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STA-421 ECONOMIC STATISTICS
Theory: 4
Hours/Week, 4 Credits
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.
Books
Recommended:
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
STA-421L ECONOMIC
STATISTICS (Lab)
Lab: 4 Hours/Week,
2 Credits
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.
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STA-423 APPLIED STATISTICS
Theory : 4
Hours/Week, 4 Credits
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.
Books
Recommended:
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, 6th
Ed
Wordsworth,
Stephans & Godfrey, Modern Methods for Quality Control and
Improvement
Publications of
B B S, Bangladesh Bank, NIPORT and other organizations.
STA-423L APPLIED
STATISTICS (Lab)
Lab: 4
Hours/Week, 2 Credits
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.
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STA-424 DESIGN AND ANALYSIS OF
EXPERIMENTS-II
Theory : 3 Hours/Week, 3 Credits
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.
Books Recommended:
Cochran WG &
Cox DR, Experimental Design, John Wiley & Sons, Inc.
Montgomery,
D.C., Design and Analysis of Experiments, 4th Ed, Wiley
Kempthrone, O.,
The Design and Analysis of Experiment, Wiley
Federer, W.T.,
Experimental Design, Oxford & IBH publishing company, Pvt., Ltd.
Gomez, K.A. &
Gomez A.A., Statistical Procedures for Agricultural Research , 2nd
Ed
Yates, F.,
Design and Analysis of Factorial Experiments, Harpenden, Herts,
England
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.
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
STA-424L
DESIGN AND ANALYSIS OF EXPERIMENTS-II (Lab)
Lab : 2 Hours/Week, 1 Credit
Total, partial and simultaneous confounding, Fractionally replicated
factorial experiment, Analysis of split-plot design, split-split
plot design, strip-plot design and nested design.
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STA-425 STOCHASTIC
PROCESSES
Theory:4 hours/week, 4 Credits
Set
Functions:
The concept of measurability, simple function, elementary properties
of measures, outer measures, measurable sets and Lebesgue measure,
non-Lebesgue measurable sets.
Convergence of Random Variables:
Characteristic functions with properties, probability generating
functions with properties, conditions.
Modern Probability Theory:
Probability of a set function, Borel field and extension of
probability measure, probability measure notion of random variables,
probability space, distribution functions, expectation and moments.
Stochastic Process:
Definition,
different types of stochastic processes, recurrent events, renewal
equation, delayed recurrent events, number of occurrence of a
recurrent event.
Markov Chain:
Transition matrix, higher transition probabilities, classification
of states and chains, ergodic properties, evaluation of Pn.
Finite Markov Chain:
General theory of random walk with reflecting barriers, transient
states, absorption probabilities, application of recurrence time,
gambler’s ruin problem.
Homogeneous Markov Process:
Poisson process, simple birth process, simple death process, simple
birth death process, general birth process, effect of immigration,
non-homogeneous birth death process. Queueing theory.
Books Recommended:
G.R. Grimmett
and D.R. Stirzaker. Probability and random processes. Oxford Science
Publications.
R.B. Ash. Real
analysis and probability. Academic Press.
N.T.J. Bailey.
The element of stochastic processes. Wiley.
M.S. Bartlett.
An introduction to stochastic processes. Wiley.
P. Billingsley.
Probability and measure Wiley.
K.L. Chung.
Elementary probability theory with stochastic processes.
D.R. Cox and W.
Miller. The theory of stochastic processes, Chapman and Hall.
S. Karlin and
H.M. Taylor. A first course in stochastic processes. Academic Press.
H.M. Taylor and
S. Karlin. An introduction to stochastic modeling. Academic Press.
S.M. Ross.
Introduction to probability models. Academic Press.
S. Ross.
Stochastic processes. Wiley.
U.N. Bhat.
Elements of applied stochastic processes. Wiley.
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STA-426 MULTIVARIATE METHODS
Theory:4
Hours/Week, 4 Credits
Non-central
distribution: Non-central λ2, F and t-distributions,
their properties.
Multinormal distribution: Derivation of Multinormal distribution,
Marginal, Conditional, Moments & moment generating function.
Properties of Multinormal distribution.
Tests of Mean
vector: Hotelling's T2, Mahalanobish D2,
Wishart distribution,
Distribution of Quadratic forms: Distribution of General quadratic
form, Properties: Expected values, Moment and Moment generating
function.
Books Recommended:
Anderson, T.W.-
An Introduction to Multivariate Analysis, Wiley and sons, NY
Graybill, F.A.-
An Introduction to Linear Statistical Models, Vol-1, 2nd Ed, Mc-Graw-Hill,
NY
Manly B.F.J-
Multivariate Statistical methods-a primer, Chapman and Hall, London
Johnson R.A.
and Wichern D.W.- Applied Multivariate Analysis, Prantice Hall, New
Jersey
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STA-426L MULTIVARIATE
METHODS (Lab)
Lab 2 Hours/Week,
1 Credit
Syllabus will
be designed by course teacher.
STA-427
BIO-STATISTICS & EPIDIMIOLOGY
Theory: 4
Hours/Week, 4 Credits
Bio-statistics
Overview:
Roots,
Development and nature of discipline, Current focuses and
challenges.
Basic Quantities:
Lifetime distribution, Survival function, Hazard function,
Interrelationships, Mean residual life function, Median Life time,
Censoring, Truncation, Right an left censoring, Type-I and Type-II
censoring, Random censoring.
Parametric Methods:
Likelihood construction for censored and truncated data, Inference
procedure for Exponential, Weibull, Gamma, Normal, Lognormal,
extreme value distribution for complete and censored data.
Nonparametric Methods:
Estimation of
survival function, hazard function; Reduced sample method, Product
limit method, Actuarial Method, Estimation and standard error, Gehan
test, Mantel -Haenszel test, Log-rank test.
Regression:
Exponential and Weibull regression models, Logistic regression,
Estimation and tests. Proportional Hazards Models.
Epidemiologic Concept:
Epidemiology, Health and Disease, Sources of Data of Community
Health: Census, Vital Statistics and Morbidity Data.
Study Designs:
Case-control, Cohort, prospective, retrospective, Longitudinal
Studies. Clinical Trials.
Measure of Disease frequency:
Incidence, Prevalence, Sensitivity and specificity. Estimation of
Risk and Rate.
Measure of
effect and measures of association: Measure of effect, Measures of
association, standard measures, Prevalence ratio, Relative Risk,
Attributable risk, Odds ratio, Standard errors of Estimates for
different types studies, McNemar Test
Matching:
Purpose and effect of matching, Matching in case-control studies,
Matching in Cohort Studies.
Books
Recommended:
Lawless, J.F.:
Statistical Models and Methods for Lifetime data
Cox, D. R. and
Oakes, D: Analysis of Survival Data
Kalbfleisch,
J.D. and Prentice R.L.: The Statistical Analysis of failure Time
Data
Kleinbaum, D.G.,
Kupper, L.L. and Morgenstern, H. Epidemiologic Research: Principles
and Quantitative Methods
Rothman, K.J.
and Greenland, S. :Modern Epidemiology
Elandt-Jhonson,
R.C. and Jhonson N.L.: Survival Models and Data Analysis
Lee, E.T:
Statistical Method for survival Data Analysis
Pocock,
William: Clinical Trials
STA-427L
BIO-STATISTICS & EPIDIMIOLOGY (Lab)
4 Hours/Week, 2
Credit
Syllabus
will be designed by course Teacher
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