Embed Size (px)
Citation preview
SHAH JALAL UNIVERSITY OF SCIENCE & TECHNOLOGY, SYLHETB. Sc. (Honours) in Statistics
Session: 2008-2009 to 2011-2012
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 Point80% or above A+ 4.0075% to less than 80% A 3.7570% to less than 75% A- 3.5065% to less than 70% B+ 3.2560% to less than 65% B 3.0055% to less than 60% B- 2.7550% to less than 55% C+ 2.5045% to less than 50% C 2.2540% to less than 45% C- 2.00Less than 40% F 0.00Incomplete 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 ICourse No. Course Title Hours/Week
(Theory+Lab.) Credits
STA-121 Probability 4 + 0 4.0STA-122 Principles of Statistics 4 + 0 4 .0STA-122L Principles of Statistics (Lab) 0 + 4 2 .0MAT-101A Algebra 2 + 0 2.0ENG-101 English Language-I 2 + 0 2.0ENG-102L English Language-I (Lab) 0 + 2 1.0
Total 12 + 6 15.0
First Year: Semester IICourse No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-123 Theory of Statistics 4 + 0 4 .0STA-123L Theory of Statistics (Lab) 0 + 4 2 .0MAT-103A Calculus 4 + 0 4 .0MAT-109 Linear Algebra 4 + 0 4 .0BNG-101 Bengali Language I 2 + 0 2 .0BNG-102L Bengali Language I (Lab) 0 + 2 1 .0ENG-103 English Language-II 2 + 0 2 .0ENG-104L English Language-II (Lab) 0 + 2 1 .0STA-100 Viva 0 + 0 2 .0
Total 16 + 8 19.0
1
Second Year: Semester I (3rd Semester)Course No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-221 Survey Methods 4 + 0 4.0STA-221L Survey Methods (Lab) 0 + 4 2.0STA-222 Regression Analysis –I 4 + 0 4.0STA-222L Regression Analysis –I (Lab) 0 + 4 2.0MAT-207 Advanced Calculus & Differential Equations
(Pre-requisite MAT-103 A)3 + 0 3.0
ECO-101 Principles of Economics-I 4 + 0 4.0Total 15 + 8 19.0
Second Year: Semester II (4th Semester)Course No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-223 Design and Analysis of Experiments-I 4 + 0 4.0STA-223L Design and Analysis of Experiments-I (Lab) 0 + 4 2.0MAT-208 Numerical Methods & Complex Variable 4 + 0 4.0MAT-209 Real Analysis 4 + 0 4.0ECO-201 Principles of Economics -II 4 + 0 4.0STA-200 Viva 0 + 0 2.0
Total 16 + 4 20.0
Third Year: Semester I (5th Semester)Course No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-321 Statistical Inference 4 + 0 4.0STA-321L Statistical Inference (Lab) 0 + 4 2.0STA-322 Statistical Computing-I 2 + 0 2.0STA-322L Statistical Computing-I (Lab) 0 + 4 2.0STA-323 Regression Analysis -II 4 + 0 4.0STA-323L Regression Analysis -II (Lab) 0 + 4 2.0
Total 10 +12 16.0
Third Year: Semester II (6th Semester)Course No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-324 Statistical Computing II 3 + 0 3.0STA-324L Statistical Computing II (Lab) 0 + 4 2.0STA-325 Demography 4 + 0 4.0STA-325L Demography (Lab) 0 + 4 2.0STA-326 Linear Programming 3 + 0 3.0STA-326L Linear Programming (Lab) 0 + 2 1.0STA-300 Viva 0 + 0 2.0
Total 10 + 10 17.0
Fourth Year: Semester I (7th Semester)Course No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-421 Economic Statistics 4 + 0 4.0STA-421L Economic Statistics (Lab) 0 + 4 2.0STA-423 Applied Statistics 4 + 0 4.0STA-423L Applied Statistics (Lab) 0 + 4 2.0STA-424 Design & Analysis of Experiments II 3 + 0 3.0STA-424L Design & Analysis of Experiments II (Lab) 0 + 2 1.0
Total 11+ 10 16.0
2
Fourth Year: Semester II (8th Semester)Course No. Course Title Hours/Week
(Theory+Lab.)Credits
STA-425 Stochastic Processes 4 + 0 4.0STA-426 Multivariate Methods 2 + 0 2.0STA-426L Multivariate Methods (Lab) 0 + 2 1.0STA-427 Bio-statistics & Epidemiology 4 + 0 4.0STA-427L Bio-statistics & Epidemiology (Lab) 0 + 4 2.0STA-428 Non-Parametric Methods 2 + 0 2.0STA-428L Non-Parametric Methods (Lab) 0 + 2 1.0STA-400 Viva 0 + 0 2.0
Total 12 + 8 18.0
Detailed Syllabus
STA-101 PRINCIPLES OF STATISTICS (FOR MAT DEPT.) 3 Hours/week, 3 Credits
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.
Books Recommended:Hoel P G, Introductory Statistics, John Wiley, NYJohnston J. Econometric MethodsMostafa M G, Methods of Statistics, BangladeshWeatherburn C E, A first Course in Mathematical StatisticsWonnacott & Wonnacott, Introductory StatisticsYule and Kendal, An Introduction to the theory of Statistics
STA-102 STATISTICS FOR SOCIAL AND POLITICAL RESEARCH (FOR PSA DEPT.)2 Hours/Week, 2 Credits
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.
Books Recommended:Wonnacott & Wonnacott Introductory Statistics Mostafa M G, Methods of Statistics, BangladeshYule and Kendal, An Introduction the Theory of Statistics
STA-103 STATISTICS I (FOR BAN DEPT.)4 Hours/Week, 4 Credits
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.
3
Books Recommended:Croxton & Cowdon, Applied General Statistics, Prentice HallKlein L, A Text Book of Econometrics Mirer T, Economic Statistics and EconometricsMood & Grabill, Introduction of the Theory of StatisticsMostafa M G, Methods of StatisticsWalpole R W, Introduction to StatisticsWonnacott & Wonnacott, Intoductory Statistics, WileyYule & Kendal, An Introduction to the Theory of Statistics, Macmillan.
STA-104 INTRODUCTORY STATISTICS (FOR ECO DEPT.)Theory: 3 Hours/Week, 3 Credits
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.
Books Recommended:Mostafa M G, Methods of StatisticsIslam M N, An Introduction to Statistics and ProbabilityRoy M K, Fundamentals of Probability and Probability distributionsCroxton & Cowdon, Applied General Statistics, Prentice-HallMood & Grabill, Introduction to the Theory of StatisticsWalpole R W, Introduction to Statistics, Collier-MacmillanWonnacot & Wonnacot, Introductory Statistics, Wiley
STA-105 GENERAL STATISTICS (Course should be taught in applied nature) (FOR CEP DEPT.)3 Hours/Week, 3 Credits
Statistics : Definition, Nature & Scope. Organization of Data: Definition & classification of data, Tabulation, Frequency distribution, Graphic representations. Measures of Central Tendency: Mean , Median, Mode Geometric mean & Weighted average, Quantiles, Measures of Dispersion: Range, Standard deviation, Variance, Coefficient of variation, Skewness & Kurtosis. Probability: Definition, Statement & Interpretation of Laws of Probability, Bayes rule, Random variables, Mathematical Expectations, Probability distributions, Uses, Application & Properties of Binomial, Poisson & Normal distribution. Statistical Inference: Sampling & sampling distributions, Properties of t, F, λ2
distributions. Test of hypothesis concerning mean, variance, proportion, Test of independence, Contingency tables, Test of homogeneity, Confidence intervals for mean, variance, proportions, Sample size determination. Correlation & Regression: Definition , measure, interpretation & significance, Curve fitting by least squares method and related tests, Multiple linear regression. Analysis of Variance.
Books Recommended:Warren Chsae & Fred Bown, General Statistics (2nd Edition)Meyer A, Probability and Statistics, Addisio-Wesely, USA
STA-106 STATISTICS I (FOR ECO DEPT.)Theory: 3 Hours/Week, 3 Credits
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.
4
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.
Books Recommended:Mostafa M G, Methods of StatisticsIslam M N, An Introduction to Statistics and ProbabilityIslam M N, An Introduction to Sampling MethodsRoy M K, Fundamentals of Probability and Probability distributionsKlein L, A Test Book of EconometricsMirer T, Economic Statistics and EconometricsGupta and Kapoor, Fundamentals of Applied Statistics
STA-121 PROBABILITYTheory: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.Solving probability problems using Binomial, Poison, Normal distributions.Law of Large Numbers- Weak and Strong Law
Books Recommended:Meyer A, Probability and Statistics , Addison-Wesley, USAFeller W, Introduction to Probability Theory and its Applications, Vol-1, 3rd Ed, John Wiley, NYMood, Graybill &Boes, Introduction to Theory of Statistics, 3rd Ed, McGraw Hill, NYMosteller, Rourke &Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USAParzen E, Modern Probability Theory and its Applications, John Wiley, NY Ross S M, A First Course in Probability, Academic Press, NYRoss S M, Introduction to Probability Models, 3rd Ed, Academic Press, NYRoy MK. Fundamentals of Probability and Probability distributions.Islam, M.N., Introduction to Statistics and Probability, 3rd Edition
STA-122 PRINCIPLES OF STATISTICSTheory: 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. Study of binomial, poisson, negative binomial, geometric, hypergeometric, multinomial, uniform, normal, exponential, gamma and beta 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, EdinburghHoel P G, Introduction to Mathematical Statistics, 5th Ed, John Wiley, NYMoore P.G, Principles of Statistical Techniques, 3rd Ed, Cambridge University Press, LondonMostafa M G, Methods of Statistics, Bangladesh Wonnacott K H & Wonnacott R J, Introductory Statistics, 3rd Ed, John Wiley, NYWeatherburn C E, A First Course in Mathematical Statistics, Cambridge University Press, LondonYule G U & Kendal M G, An introduction to the Theory of Statistics, 14 th Ed, Charles-Griffin, LondonIslam, 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.
5
MAT 101A ALGEBRA2Hours/Week, 2 CreditsReview 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, Chebyshev and Jensen’s inequality.Determinant: 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 algebraic equations, Descartes rule of signs.
Books Recommended:Bemard & Child, AlgebraHall & Knight, Higher AlgebraRahman M.A, Algebra and TrigonometryShahidullah & Bhattacharjee, Algebra and Trigonometry
STA-123 THEORY OF STATISTICSTheory: 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 X and S2 , detailed study of 2
, 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 2 2 table, test for r c contingency table. Central limit theorem.
Books Recommended:Ali A, Theory of Statistics, Vol-II, BangladeshHoel P G, Introduction to Mathematical Statistics, 5th Ed, John Wiley, NYHogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, LondonKendall & Stuart, Advanced Theory of Statistics, 4th Ed, Charles-Griffin, LondonMood, Graybill & Boes, Introduction to the Theory of Statistics, 3rd Ed, McGraw Hill, NYMostafa M G, Methods of Statistics, BangladeshWonnacott K H & Wonnacott R J, Introductory Statistics, 3rd Ed, John Wiley, NYWeatherburn C E, A First Course in Mathematical Statistics, Cambridge University Press, LondonIslam, 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.
STA-201 PROBABILITY AND PROBABILITY DISTRIBUTIONS (FOR MAT DEPT.)3 Hours/Week, 3 Credits
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.
Books Recommended:Feller W, Introduction to Probability, Vol-1, 3rd Ed, John Wiley, NYHoel P G, Introduction to Mathematical Statistics, John Wiley, NYHogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London
6
Meyer A, Probability and statistics, Addison-Wesley, USAMood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NYMosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-wesley, USARoss S M, A first Course in Probability, Academic Press, NY
STA 201 BASIC STATISTICS (FOR ANP DEPT.)3 Hours/Week, 3 Credits
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.
Books Recommended: Books Recommended:Hoel P G, Introductory StatisticsMostafa M G, Methods of Statistics, BangladeshWonnacott & Wonnacott, Introductory Statistics
STA-202 BASIC STATISTICS AND PROBABILITY (FOR CSE DEPT.)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).
Books Recommended:Barlow R J, StatisticsChisholm J S R & Morris R M, Mathematical Methods in PhysicsHoel P G, Elementary Statistics, John Wiley, NYLoveday, Practical Statistics and ProbabilityMelnyk M, Principles of Applied StatisticsMostafa M G, Methods of statistics, BangladeshMosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USASpiegel M R, Theory and Problems of Statistics, McGraw Hill, NYTopping, Observation of Errors
STA-203 INFERENTIAL STATISTICS (FOR SOC DEPT.) (Course should be taught in applied nature)3 Hours/Week, 3 CreditsProbability 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.
Books Recommended:Croxton & Cowdon, Applied General Statistics, Prentice-HallKlein L, A Text Book of EconometricsMirer T, Economic Statistics and EconometricsMood & Graybill, Introduction to the Theory of StatisticsMostafa M G, Methods of StatisticsWalpole R W, Introduction to Statistic, Collier-MacmillanWonnacot P & Wonnacot R, Introductory Statistics, WileyYule & Kendal, An Introduction to the Theory of Statistic, Macmillan
7
STA-204 STATISTICS (FOR SCW DEPT.) Course should be taught in applied nature4 Hours/Week, 4 Credits
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.
Book recommended:Blalock H M, Social Statistics.Hagood, Statistics for SociologistsKendal & 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.
STA-205 STATISTICS FOR SOCIAL AND POLITICAL RESEARCH-II (FOR PSA DEPT.)3 Hours/Week, 3 Credits
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 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.
Books Recommended: Dwyer, Statistical Models for the social & Behavioural SciencesGoode W J & Panek H, Methods in Social ResearchSelltiz C, Research Methods in Social RelationsYoung P V, Scientific Social Surveys And ResearchMostafa, M.G, Methods of Statistics, Bangladesh
STA-206 STATISTICS ( FOR FORESTRY DEPT.)4 Hours/Week, 4 Credits
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, 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.
Books Recommended:Hoel P G, Introductory Statistics, John Wiley, NYJohnston J. Econometric MethodsMostafa M G, Methods of Statistics, BangladeshWeatherburn C E, A first Course in Mathematical StatisticsWonnacott & Wonnacott, Introductory StatisticsYule and Kendal, An Introduction to the theory of StatisticsHoel P G, Introduction to Mathematical Statistics, John Wiley,NYHogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, LondonMood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NY
8
Cochran W G, Sampling Techniques, 3rd Ed, John Wiley, NY
STA-207 STATISTICS II (FOR ECO DEPT.)Theory: 3 Hours/Week, 3 Credits
Sampling from normal population. Sampling distribution of various statistics, Detailed study of 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 estimationTest of significance in small and large samples. Comparison of means, proportions and variances. Test of homogeneity of means and variances.
Books Recommended:Ali A, Theory of Statistics, Vol-IIMostafa M G, Methods of StatisticsIslam M N, An Introduction to Statistics and ProbabilityRoy MK. Fundamentals of Probability and Probability distributions.Gupta and Kapoor, Fundamentals of Mathematical StatisticsMeyer A, Probability and Statistics , Addison-Wesley, USAMood, Graybill &Boes, Introduction to Theory of Statistics, 3rd Ed, McGraw Hill, NYRoss S M, A First Course in Probability, Academic Press, NYHogg and Tanis, Probability and Statistical Inference
STA-208 BASIC STATISTICS AND PROBABILITY (FOR PHY DEPT.)3 Hours/Week, 3 Credits
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.
Books Recommended:Barlow R J, StatisticsChisholm J S R & Morris R M, Mathematical Methods in PhysicsHoel P G, Elementary Statistics, John Wiley, NYLoveday, Practical Statistics and ProbabilityMelnyk M, Principles of Applied StatisticsMostafa M G, Methods in Statistics, BangladeshMosteller, Rourke & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USASpiegel M R, Theory and Problems of Statistics, McGraw Hill, NYTopping, Observation of Errors
STA- 209 STATISTICS (FOR CHE DEPT.)2 Hours/Week, 2 CreditsSummarization 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.
Books Recommended:Wonnacott & Wonnacott- Introductory Statistics, WileyMostafa M G, Methods of Statistics, BangladeshJhonston, J- Econometric MethodsG.D. Christian, Analytical Chemistry, John Wiley & Sons, 4th Ed.Vogel, Inorganic Quantitative Analysis, 4th Ed.
9
STA-211 BIOSTATISTICS (FOR BIOTEC DEPT)4Hours/Week, 4 Credits
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.
Books Recommended:Mostafa, M G- Methods of StatisticsSteel, R D G and Torry, J H- Principles and Procedures of StatisticsHogg, R and Graig, A- Introduction to Mathematical Statistics
STA-211L BIOSTATISTICS (Lab)2 Hours/Week, 1 Credit
Syllabus will be designed by course teacher.
STA-212 BIOSTATISTICS (For GEN DEPT)4Hours/Week, 4 Credits
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.
Books Recommended:Mostafa, M G- Methods of Statistics
10
Steel, R D G and Torry, J H- Principles and Procedures of StatisticsHogg, R and Graig, A- Introduction to Mathematical Statistics
STA-212L BIOSTATISTICS (Lab)2 Hours/Week, 1 Credit
Syllabus will be designed by course teacher.
STA-213 STATISTICS ( FOR FOOD & TEA TECHNOLOGY DEPT.)4 Hours/Week, 4 Credits
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, 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.
Books Recommended:Hoel P G, Introductory Statistics, John Wiley, NYJohnston J. Econometric MethodsMostafa M G, Methods of Statistics, BangladeshWeatherburn C E, A first Course in Mathematical StatisticsWonnacott & Wonnacott, Introductory StatisticsYule and Kendal, An Introduction to the theory of StatisticsHoel P G, Introduction to Mathematical Statistics, John Wiley,NYHogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, LondonMood, Graybill & Boes, Introduction to the Theory of Statistics, McGraw Hill, NYCochran W G, Sampling Techniques, 3rd Ed, John Wiley, NY
STA-221 SURVEY METHODSTheory: 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, NYIslam M.N., An Introduction to Sampling Methods, Book World, Dhaka.Desraj, Sampling TheoryKish L, Survey SamplingSukhatme 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.
STA-222 REGRESSION ANALYSIS -ITheory: 4 Hours/Week, 4 Credits
Bivariate quantitative data: Bivariate normal distribution, marginal distribution, conditional distribution.Regression and correlation: Method of least squares, regression line, correlation and regression coefficients, rank correlation and correlation ratio, regression curves from bivariate distributions.
11
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, 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, NYDraper N R & Smith H, Applied Linear Regression, 2nd Ed, John Wiley, NYGraybil F A An introduction to Linear Statistical Models, Mc Graw Hill, NYJohnston J, Econometric Methods, Mc Graw Hill, NYKoutsoyiannis A, Theory of Econometrics, Mac Milan, LondonMontogomery D C & Peck E, An Introduction to Linear Regression Analysis, John Wiley, NYSeber G A F, General Linear Regression Analysis , Wiley & Sons Ltd, NYWeisberg S, Applied Linear Regression, second edition John Wiley NY
STA-222L REGRESSION ANALYSIS –I (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.
STA-223 DESIGN AND ANALYSIS OF EXPERIMENTS-ITheory: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, WileyKempthrone, O., The Design and Analysis of Experiment, WileyDas, M.N. and Giri, N.C., Design and analysis of Experiments, Wiley Eastern, New DelhiSheffe, 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 YorkDavis, O.L., Design and Analysis of Industrial Experiments, Oliver & Boyd, Ltd. LondonBhuyan, K.C., Porikhanar Naksha and Vedanka BishlasionBhuyan, 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.
STA 301 STATISCTICS (FOR CEE DEPT.)4 Hrs./Week, 4 credits
12
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: 2 , t and F distributions. Test of Hypothesis: Test for population, mean, variance, correlation coefficient and regression coefficients.
Books Recommended:Spiegel M R, Theory and Problems of StatisticsHoel P G, Elementary StatisticsHogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, LondonMood, Graybil & Boes, Introduction to the Theory of Statistics, 3rd Ed, McGraw Hill, NYMostafa M G, Methods of StatisticsMilnyk M, Principles of Applied StatisticsBarlow R G, StatisticsLoveday, Practical Statistics and ProbabilityMosteller, Rourk & Thomas, Probability with Statistical Applications, 2nd Ed, Addison-Wesley, USAGoon A M & Gupta M N, Fundamentals of Statistics, Vol-I
STA-302 THEORY OF STATISTICS (FOR MAT DEPT.)3 Hours/Week, 3 Credits
Sampling from normal and nonnormal populations. Distribution of various statistics, distribution of linear functions of normal variates. Detailed study of 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.
Books Recommended:Hoel P G, Introduction to Mathematical StatisticsHogg and Craig, Introduction to Mathematical StatisticsMood, Graybill and Boes, Introduction to the Theory of StatisticsMostafa M G, Methods of Statistics, Bangladesh
STA-321 STATISTICAL INFERENCETheory: 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, LondonCox D R & Hinkley D V, Theoritical Statistics, Chapman and Hall, LondonGraybill F A, Introduction to Linear Statistical Models, McGraw Hill, NYHoel P G, Introduction to Mathematical Statistics, 4th Ed, Wiley, NYHogg R V and Chaig A T, Introduction to Mathematical Statistics, Macmillan, NYMood, Grabyl & Boes, Introduction to the Theory of Statistics, 3rd Ed, McGraw-Hill, NYKendall, M G & Stuart A, The Advance Theory of Statistics, Vol-2, 4th Ed, Charles-Grifin, LondonLindley, Statistical InferenceZacks S, Theory of Statistical Inference, John Wiley, NYHollander, M & Wolf, D.A.- Nonparamatric Statistical Methods
STA-321L STATISTICAL INFERENCE (Lab)Lab: 4 Hours/Week, 2 Credits
13
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.
STA-322 STATISTICAL COMPUTING-ITheory: 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 ProgrammingGorre and Stubs, Computers and Information System, McGraw Hill, NYKumar R, Programming with FORTRAN 77Meissner/Organick, FORTRAN 77Microsoft 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.
STA-323 REGRESSION ANALYSIS -IITheory: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.
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, LondonJohnston, J. : Econometric Methods, McGraw-Hill, New YorkJudge, 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 REGRESSION ANALYSIS -II (Lab)Lab:4Hours/week, 2 Credits
14
Fitting of multiple regression models, Tests of parameters of a multiple regression models. 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.
STA-324 STATISTICAL COMPUTING-IITheory: 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 ProgrammingSAS, Reference Manual: Language Guide for Personal Computers, Procedures Guide, STAT User’s GuideChowdhury A K, SAS HandoutPress W H et al, Numerical Recipes in Fortran – The Art of Scientific Computing, 2nd Ed, Cambridge University PressRipley D Brian, Stochastic Simulation, Wiley, NYRoss M Sheldon, Simulation, 2nd Ed, Academic Press, LondonRubinstein Y Reuven, Simulation and the Monte Carlo Method, Wiley, NYSPSS/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.
STA-325 DEMOGRAPHYTheory: 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.
15
Books Recommended: Barclay J, Techniques of Population Analysis (John Willey & Sons) NYSpiegelman, Introduction to DemographyCox D R, DemographyKpdekpo G, Demographic Analysis in AfricaChiang CL, The Life Table and its Application, John Wiley, NYBogue D, Principles of DemographyBartlett M S, Stochastic Population Model in Ecology and EpidemiologyShyrock, Siegel et al, Methods and Materials of DemographyPollard A H, Farhat Yusuf & Polard G N, Demography, Willey Eastern, IndiaGoon A M & Gupta M N, Fundamental of Applied StatisticsVol. IIKeyfitz N, Introduction to Mathematics of Population, Addison-WesleyLinger J W, A Handbook of Population Analysis, Part ABather R W, Mortality Table ConstructionPublications of B B S, M I S, Population Division Unit of Planning CommissionJournals - 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.
STA-326 LINEAR PROGRAMMINGTheory: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 ResearchVajda 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.
STA-421 ECONOMIC STATISTICSTheory: 4 Hours/Week, 4 Credits
Attributes of consumer behavior: Engel curves and lognormal demand curves. Maximization of utility, demand function, price, income and cross elasticities of demand. Preference theory of demand.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 andhomogeneity 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.
16
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, LondonAllen R G D, Microeconomic TheoryBridge J L, Applied Econometrics, North Holland, AmsterdamChatfield, Time Series Analysis Chiang, Fundamental Methods of Mathematical Economics, 3rd ED, McGraw Hill, NYCramer J S, Empirical EconometricsHenderson & Quandt, Microeconomic Theory-A Mathematical Approach, 2nd Ed, Mc Graw Hill, NYKendal M G, Time SeriesKoutsoyiannis A, Modern MicroeconomicsKlein L R, An Introduction to EconometricsLange O, An Introduction to EconometricsLeotief 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.
STA-423 APPLIED STATISTICSTheory : 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 ControlDuncan A J, Quality Control and Industrial StatisticsGrant, Statistical Quality ControlGuilford J P, Educational Statistics and Psychometric MethodsGuilford J P & Bejamin F, Fundamental Statistics in Psychology and Education, 6th EdWordsworth, Stephans & Godfrey, Modern Methods for Quality Control and ImprovementPublications 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.
STA-424 DESIGN AND ANALYSIS OF EXPERIMENTS-IITheory : 3 Hours/Week, 3 Credits
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.
17
Weighting design: Method of estimation. Use of incomplete blocks, construction and analysis of BIB designs, incomplete block design as weighting designs (Intra and inter-block analysis). Missing plot. Orthogonal latin squares. Youden squares. Lattice designs. Partially balanced incomplete block designs.
Factorial experiment: Sn factorial experiments and their analysis.Confounding, total, partial and simultaneous confounding in
two and three levels up to n factors, Fractional replicates and their construction. Asymmetric factorial experiments.
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, WileyKempthrone, O., The Design and Analysis of Experiment, WileyFederer, W.T., Experimental Design, Oxford & IBH publishing company, Pvt., Ltd.Gomez, K.A. & Gomez A.A., Statistical Procedures for Agricultural Research , 2nd EdYates, F., Design and Analysis of Factorial Experiments, Harpenden, Herts, EnglandDas, M.N. and Giri, N.C., Design and analysis of Experiments, Wiley Eastern, New DelhiSheffe, H., The Analysis of Variance, John Wiley & Sons, Inc., New York.Mann, H.B., Analysis and Design of Experiments, Dover publications, New YorkDavis, O.L., Design and Analysis of Industrial Experiments, Oliver & Boyd, Ltd. LondonBhuyan, K.C., Porikhanar Naksha and Vedanka BishlasionBhuyan, 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.
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.
18
STA-426 MULTIVARIATE METHODSTheory:2 Hours/Week, 2 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, NYGraybill, F.A.- An Introduction to Linear Statistical Models, Vol-1, 2nd Ed, Mc-Graw-Hill, NYManly B.F.J- Multivariate Statistical methods-a primer, Chapman and Hall, LondonJohnson R.A. and Wichern D.W.- Applied Multivariate Analysis, Prantice Hall, New Jersey
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 TestMatching: 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 dataCox, D. R. and Oakes, D: Analysis of Survival DataKalbfleisch, J.D. and Prentice R.L.: The Statistical Analysis of failure Time DataKleinbaum, D.G., Kupper, L.L. and Morgenstern, H. Epidemiologic Research: Principles and Quantitative Methods Rothman, K.J. and Greenland, S. :Modern EpidemiologyElandt-Jhonson, R.C. and Jhonson N.L.: Survival Models and Data AnalysisLee, E.T: Statistical Method for survival Data AnalysisPocock, William: Clinical Trials
STA-427L BIO-STATISTICS & EPIDIMIOLOGY (Lab)4 Hours/Week, 2 Credit
Syllabus will be designed by course Teacher
STA-428 NON-PARAMETRIC METHODS Theory: 2 Hours/Week, 2 Credits
Order Statistics: Joint Distribution of n order Statistics, Marginal Distributions of order Statistics Distribution of the Median and Range, properties of order Statistics.
19
Non-parametric Tests: Tests based on Runs, Tests of goodness of fit. Rank order Statistics. Other one sample and paired sample techniques. The sign test and signed rank test. The general two sample problem. Linear rank statistics and the general two-sample problem. Linear rank tests for the location problem, Linear rank tests for the scale problem. Tests of the equality of K independent samples. Measures for bivariate samples. Measures of association in multiple comparison.
Books recommended:Gibbons, J.D.-- Non parametric Statistical Inference Mc Graw Hill, N.YMaritz -- Distribution Free Statistical Methods, Chapman and Hall, LondonHollander, M and Wolfe, D.A-- Nonparametric Statistical Methods, Wiley, N.YBradley, J.V. -- Distribution free Statistical tests, Prentice Hall. N.YDavid, H.A.-- Order Statistics (2nd Ed) Wiley, N.YFraser, D.A.S-- Nonparametric Methods in Statistics, Wiley, N.YHogg R.V. & Craig, A.T. -- Introduction to Mathematical Statistics
STA-428L NON-PARAMETRIC METHODS (Lab)Theory: 2 Hours/Week, 1 Credits
Syllabus will be designed by course teacher.
.
20
