statistical courses description - kaukau.edu.sa/files/13012/files/28644_english description...

Statistical Courses Description

Course No. Course Title Theory Practice Credit Prerequisite(s)

STAT 110 General Statistics 3 - 3 -

Objectives

- To give the students an understanding of statistics. - To learn some commonly used statistical techniques. - To apply these techniques in describing and analyzing data. - To use statistics to solve different kind of problems. - To recognize sound/good statistical studies. - To gain an appreciation for analytical skills.

Course Description

- What is Statistics? - Collecting data, graphical presentation and tabulation. - Measures of central tendency: mean, median and mode. - Measures of dispersion: range, and standard deviation. - Relative Dispersion and Skewness. - Elementary probability: random experiment, sample space, event, and computation

of probability. Rules of addition and multiplication, conditional probability and independence.

- Random variables, probability distributions, variance and expected value - Some probability distributions (Binomial, Poisson, and Normal).

- Sampling and sampling distribution: Sampling distribution of Sample Mean (in case of large samples), central limit theorem and sampling distribution of proportion.

- Estimation of population mean and proportion. - Tests of statistical hypotheses: testing of mean, differences between two means,

proportion, differences between two proportions in large samples. - Simple linear regression and Correlation: Pearson's correlation coefficient and

Spearman's rank correlation coefficient.

Textbook:

Bluman, "Elementary Statistics a Step by Step Approach", 6th Edition (2006)

Subsidiary:

Larson & Farber, "Elementary Statistics: Picturing the World", 3rd Edition (2006)


Stat 203 Statistics in Practice 1 2 2 Stat 110

Objectives

The course provides clear and understandable explanations of statistics concepts through the use of continuing case studies and an emphasis on live improvement. The cases and examples show real applications of statistics relevant to today's science students. The course motivate students by showing persuasively how the use of statistical techniques in support of live decision-making helps to improve live processes. Subject areas covered include medicine and pharmaceutics; industry, finance and commerce; public services; the earth and environmental sciences, and so on. A variety of computer centered examples and exercises, and a robust, technology-based ancillary package are designed to help students master this subject.

Course Description

- Application of statistics in other fields. - Estimation and statistical tests of two samples. - Significance for proportions and difference between two proportions. - Chi-square tests: goodness of fit tests, test for independence and homogeneity

in contingency tables. - Fisher’s test and McNemar Test. - Measures of association: nominal and ordinal data. - Communicating and Documenting results of Analyses. - Using one of Statistical packages to solve the problems.

Main text books:

Ott, Larson, Mendenhall; Statistics a toll for the social sciences. 5th edition.

Subsidiary books:

Moore; The basic Practice of Statistics. 2nd edition.


Stat 205 Statistical

Mathematics 3 - 3 Math 110

Objectives

1. To refresh the mathematical knowledge of the student for studying Statistics.

2. To enhance the mathematical background of the student.

Course Description:

1. Quick revision (oriented-to-probability) on: counting techniques including

permutations and combinations, matrices, sets, integrals stressing on double and

triple integrals, expansions of functions, maxima and minima of functions, partial

fractions, and progressions.

2. Difference and differential equations applied to solve difference-differential

equations related to branching processes: birth-and-death processes, and epidemic

processes.

3. Laplace's transforms applied to solve: difference, ordinary differential, partial

differential differential-difference, integral, integro-differential equations.

4. Special functions: gamma, beta, … functions applied to statistical distribution theory.

5. Expansions of functions oriented to calculating probabilities from probability and

moments from moment generating functions.

6. Constrained maxima and minima using Lagrange's multipliers .

7. The principle of mathematical induction.

Main text books:

Cramer, H., "Mathematical Methods of Statistics", 13th Ed. (1999)

Subsidiary books:

1425


Stat 211 Probability Theory I 3 2 4 Stat110,

Math202

Objectives

Studying probability and probability distributions with its characteristics in case of

one variable.

Course Description:

- Random experiment, Sample space, Events, Axioms of probability. - Conditional probability and independence, Bayes theorem. - Discrete and continuous Random variables, probability function and probability

density function, distribution function and its characteristics. - Mathematical expectation, central and non-central moments of order r,

measures of skew ness and kurtosis. - Moment generating function and probability generating function. - One variable discrete probability distributions (Uniform, Bernoulli, Binomial,

Poisson, Geometric, Hypergeometric and Negative Binomial). - Gamma function, Beta function. - One variable continuous probability distributions (Uniform, Normal, Gamma,

Exponential, Chi-Square and Beta). - Derivation of moments, moment generating function, probability generating

function (whenever relevant) for the above distributions.

Main text books :

G.M. El-Sayyad: Theory of probability, 1990, جده– دار اآلفاق

Bain & Engelhardt, Introduction to Probability and Mathematical Statistics, Duxbury Press

Subsidiary books :

- Blake, I.F. : An Introduction to Applied Probability, John Wiely, 1989.


Stat 241 Statistical packages

and Research Methods 1 2 2

Stat110, CS

100

Objectives

The goal of this course is to provide the students with skills of handling and

analyzing the statistical data in different research areas through developing certain

fundamental Knowledge and skills of Statistical research stages, assumptions,

methodologies and decision making. This will be done by application on statistical packages.

Course Description:

- Theoretical concepts including: Statistical research stages, assumptions, population, types of random sampling and sample size, types of questions, types of variables, measurement levels and coding.

- Handling statistical data by using a statistical program such as SAS, Minitab, or SPSS. This includes to show students entering data, different files, saving files, opening files, invoking the program and its uses in descriptive statistics, graphical representation, different probability distributions, sampling techniques, generating random and patterned numbers, confidence intervals, testing hypotheses, correlation, regression, ANOVA and chi-square tests.

Main text books :

Designing and conducting survey research, A comprehensive guide. Louis M. Rea and

Richard A. Parker. Jessey-Bass publisher. Second Edition.

Subsidiary books :

الطبعة األولى، . أساليب البحث العلمي والتحليل اإلحصائي(.2005)عبد الحميد البلداوي . د

. دار الشروق


Stat 261 Operations Research I 3 - 3 Stat 110

Objectives

Introducing to the science of operations research and its importance and some of the main

problems.

Course Description:

- Introduction: History and development of O.R., Definition of O.R., Various stages of an O.R. study.

- Linear programming: Formulation of LP problems, The graphical method, Simplex method, The two-phase method, The dual simplex method, The dual problem and its relation with the primal problem.

- The transportation problem: LP formulation, methods of finding initial feasible solution, Testing of optimality and finding the optimal solution.

- The assignment problem: LP formulation, The Hungarian method of solution, The unbalanced AP.

- Inventory models: some deterministic and stochastic models. - Network analysis: Drawing networks, PERT and CPM methods.

Main text books :

Hamdy A. Taha, Operations Research, Macmillan Publishing Co. (1997). Barry Render ,Ralph M. Stair, Michael E. Hanna, "Quantitative Analysis for Management", Pearson Subsidiary books :

Churchman, C.W., Ackoff and E.L. Arnoff, Introduction to Operations Research, John Wiley,

(1992).


Stat 302 Statistical Methods 2 2 3 Stat 211

Objectives

To make the student aware of the statistical methods which are used in estimation and

testing of significance.

Course Description:

- Calculation of moments and coefficients of skewness and kurtosis. - Revision of: Normal, x2, t and F distributions and their relations. - Sampling distribution from normal population, sampling distribution of means,

differences between two means, variance and ratio of two variances (and their uses in estimation and testing of significance).

- Central limit theorem and law of large numbers, estimation and test of significance for proportions and difference between two proportions.

- Analysis of Variance. - Tukey, Scheffe, Bonferroni Multiple comparison Procedure - ANOVA diagnostics and Remedial Measures. - Non Parametric Alternatives - Using Minitab packages.

Main text books:

Walpole, Introduction to Statistics, Collier McMillan, (1992).

Subsidiary books:

Mendenhall, W. Warcherly D.D. and R.L. Scheaffer, Mathmatical Statistics with Applications, PWS-kent 1989. Neter; Applied Linear Statistical Models, 5th Edition


Stat 312 Theory of Probability

II 3 - 3

Stat211,

Math203

Objectives

Studding probability distributions of more than one random variable and finding the

probability distributions of functions and sums of random variables.

Course Description:

- Bivariate probability distribution: Discrete and continuous, joint, marginal, and conditional distributions, Calculation of moments, independency, Covariance, and Coefficient of correlation.

- Probability generating function and moment generating function. Trinomial and bivariate normal distributions.

- Generalization of the above concepts to multivariate random variables. - Probability distributions of functions of random variables using distribution

function, moment generating function and transformation methods. - Derivation of Chi-square, t and F distributions. - Probability distributions of sum of independent random variables and their

properties: the expected value, variance and covariance.

Main text books :

G.M. El-Sayyad: Theory of probability, 1990, Dar-Hafez

Subsidary books :

Blake, I.F. : An Introduction to Applied Probability, John Wiely, 1989.


Stat 321 Inference Statistics I 3 - 3 Stat 312

Objectives

Studying the theoretical bases for the estimation methods.

Course Description:

- Review of the concepts of joint distributions and the distribution of sums of random variables.

- Definition of: parameter space, statistic, information and sufficiency. - Properties of estimators, unbiased ness, consistency and efficiency, lower bound

of the variance of unbiased estimators, Rao-Cramer inequality. - Methods of estimation: maximum likelihood, moments, least-squares. - Interval estimation, pivotal quantity, confidence interval and expectation of its

length, large sample confidence interval. - Bayesian point estimates, Bayesian interval estimation.

Main text books :

G.M. El-Sayyad: "Statistical Inference, 1994, Dar-Hafez

Subsidiary books :

Mood, A. M., F.A. Graybill and D.C. Boss, Introduction to the Theory of Statistics, McGraw. Hill, (1989).


Stat 333 Statistical Quality

Control 3 - 3 Stat 302

Objectives

To make the student aware of the statistical control which has two main aspects: Process

control and acceptance sampling.

Course Description:

- Definition and principles of SPC. - Control charts: theoretical CC and empirical CC to detect lack of control of

process, CC for variables: X-charts, R-charts (number of defects). - Acceptance sampling: sampling plan, operating characteristic curve, single-

sample plans, double and sequential sampling plans.

Main text books :

Grant, E.I. and R.S. Leaver Worth, Statistical Quality Control, McGraw Hill, New York, (1992).

Subsidiary books :

Feigenbaum, A.V., Total Quality control, McGraw Hill, 1988. Statistical Methods in Quality control, D.J. Cowden, Prentice-Hall, 1987.


Stat 334 Demography 3 - 3 Stat 302

Objectives

To present the statistical methods and probability models used in the study of population

and the treatment of demographic data.

Course Description:

- Definition of : Population, Demography, Census, Vital statistics, ratios and rates. - The distribution of population according to sex and age, and the Population

Pyramid. - Annual rate of population growth: Linear, Geometric and exponential forms. - Measurement rates of: Mortality, Migration, Fertility. - Life tables: Definition, Basic life table functions, Construction of life table. - Mathematical models related to demographic analysis, Population projections.

Main text books :

Cox, P. R. "Demography" 1987, Cambridge Univ. press, (1990).

Subsidiary books :

Hinde, A (1998), Demographic Methods, Arnold.


Stat 335 Biostatistics 3 - 3 Stat302

Objectives

The aim of this course is to teach student applications of statistical methodology in public

health, medicine, and other biomedical sciences.

Course Description:

This course contains: descriptive statistics, some of probability distributions, sampling

distributions, estimation and testing parameters, regression and analysis of variance, chi-

square distribution and analysis of frequencies, nonparametric and distribution-free

statistics, vital statistics.

Main text books :

Daniel, W(1995). Biostatistics: A Foundation for Analysis in the Health Sciences, USA.

Subsidiary books :

Runyon, R. Fundamental of Statistics in the Biological Medical and Health Sciences, USA.


Stat 336 Reliability Theory 3 - 3 Stat302

Objectives

The aim of this course is to teach student statistical methods used in industrial applications,

lifetime data analysis and reliability systems.

Course Description:

This course contains: Reliability Concepts and Reliability Data, Failure Models, Reliability of

Systems, Life Data Analysis, Accelerated Life Testing, Standby systems.

Main text books :

Hoyland, A. And Rausand, M. (2004). System Reliability Theory: Models And Statistical Methods,2nd Edition, J. Wiley, New York. Subsidiary books :

William Q. Meeker And Luis A. Escobar (1998). Statistical Methods for Reliability Data , J. Wiley, New York.

http://www.wiley.com/





Stat 337 Statistical Finance 3 - 3 Stat 302

Objectives

To make the students aware of the statistical principles involved in the analysis of financial

problems and investments.

Course Description:

- Statistical techniques used to price and hedge derivative securities in modern finance.

- Modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes.

- Applications of derivatives in practice, cash flow analysis, profitability analysis, and operating activities analysis.

- Main text books :

- Hull, Options, Futures, and Other Derivatives. 6th edition.

Subsidiary books :

Promislow, Fundamentals of Actuarial Mathematics, Wiley.


Stat 351 Sampling Theory 3 - 3 Stat 321

Objectives

To provide the theoretical bases of some probability sampling methods together with

practical examples. It is useful in planning and market research studies.

Course Description:

- Definition : population, parameters, complete enumeration, samples, statistics, sampling units and frames.

- Kind of sampling, sampling design, design of questionnaire, data collection and sources of error.

- Different types of sampling schemes: simple random, stratified random, systematic random, estimation of parameters, variances of estimation of parameters, variances of estimates, estimate of variances, Bound on error, choice of sample size.

- Use of supplementary information: Ratios, Regression and Difference Estimates.

Main text books :

Sampath, S. "Sampling Theory and Methods", Department of Statistics, Loyola College,

Chennai, India Second Edition (2005).

. جده - اآلفاق دار1993 ، جالل مصطفى .د ، الصياد جالل .د : االحصائية المعاينة طرق -

Subsidiary books :

Cochran, W.G. "Sampling Techniques", 1987, John Wiley.


Stat 362 Operations Research

II 3 - 3 Stat261

Objectives

This subject aims to give the student an idea of the theory of linear programming, which has

been studied previously in the subject stat 261 without proofs. In addition, the subject

studies some advanced topics in the area of operations research.

Course Description:

1. Sensitivity analysis: Changes in the objective function - Addition of a new variable - Changes in the right side constraints - Addition of a new constraint. Parametric linear programming.

2. Theorems of linear programming. This chapter covers several theorems such as the week duality theorem - the duality theorem - the complementary slackness theorem.

3. Integer programming. Cutting plane algorithm - Branch and bound technique. 0-1 integer programming.

4. Bounded variables technique.

Main text books :

Operations Research, An Introduction, Taha, H.A., Prentice Hall; 8th ed. (2006).

Subsidiary books :

Operations Research, Applications and algorithms, Winston, W.L., PWS - Kent Publishing Co.,

Boston, (1992).


Stat 390 Summer Training - - 2 Department

Approval

Objectives

The student will be directed to a company or establishment for training on real statistical

problems.

Main text books :

Derr J., "Statistical Consulting: A Guide to Effective Communication", Duxbury Press; 1st ed.


Stat 403 Regression Analysis 3 - 3 Stat 302,

Math241

Objectives

Studying the statistical methods used in regression analysis.

Course Description:

- Simple linear regression: The method of least squares and its assumptions, Gauss-Markov theorem, statistical inference about regression coefficients, methods of measuring model adequacy, prediction.

- Multiple linear regression, estimation of the model, using matrices in regression, polynomial regression, partial F test, prediction.

- Residual analysis, testing of the assumptions of least squares method. - Selection of predictor Variables and building regression models. - Non linear regression. - Applications using computer.

Main text books:

Neter; Applied Linear Statistical Models, 5th Edition.

Subsidiary books:

Montgomry, D.C. and A.P. Elizabith, Introduction Linear Regression Analysis, John Wiley and

Sons 1982.


Stat 405 Design and Analysis

of Experiments 3 - 3 Stat 403

Objectives

To make the students aware of the statistical principles involved in the planning of

experiments and subsequent analysis of data. Experiments in agriculture, medicine and

industry rely heavily on these methods.

Course Description:

- Basic principles: randomization, replication and local control. - Three basic designs: completely randomized, randomized block and Latin

square, randomization of treatments, model description, least square estimates of parameters and their properties, break up of squares to their relevant components, calculation of their expected values, preparation of ANOVA tables.

- Multiple comparisons: LSD, Duncan and Schaffer's method. - Estimation of missing values and approximate analysis. - Simple factorial experiments (rxc): main effects, interactions, relevant models

and estimation of parameters. - Analysis of simple factorial experiments such as 23 and 32. - Blocking and Confounding in the 2k - Experiments with Random Factors - Nested and Split-Plot Designs

Main text books:

Montgomery, D.G. "Design and Analysis of Experiments" 1993, John Wiley.

Subsidiary books:

Oehlert, Afirst Course in Design and Analysis of Experiments. Peter, W.M. John "Statistical Design and Analysis of Experiments" 1991, the MacMillan

Comp. New York.


Stat 406 Categorical Data

Analysis 3 - 3 Stat 302

Objectives

This course aim to study the different techniques used to analyze qualitative data

which are used in Economic, Social and Medical fields.

Course Description:

- Discussing the qualitative data. - Study the properties of the Multinomial distribution - Study of the Chi-square tests (Goodness of fit, Homogeneity, Independence). - Yates Modifications. - Fisher Exact test ( Binary and General case). - Significance of rank correlations (Spearman rho and Kendall tau). - Attitudes in Contingency tables (2 X c and r X c). - McNimar, Cochran Q and Kendall W tests. - Method of discrimination using Bayes theorem. - Logistic regression models.

Main text books :

A. E. Maxwell, "Analyzing Qualitative Data" (1971), Redwood Press Limited, Trowbridge & London. Stephen E. Fienberg, "The Analysis of Cross-Classified Categorical Data" (1978), Cambridge, Massachusetts & London.

Subsidiary books :

Conover, "Introduction to Nonparametric Statistics" (1999), 3rd Ed.


Stat 407 Nonlinear Regression 3 - 3 Stat 403

Objectives

The main purpose of this course is giving Students an idea about the nonlinear models which

have a wide applications in real data.

Course Description:

- Introduction to regression models : Linear and nonlinear regression models, Geometrical representation of

nonlinear regression models.

- Yield-Density Models: Examination of nonlinearity in the yield-density models, choice of yield-density

models

- Sigmoidal growth models: Stability of parameter estimations to varying assumptions about the error, Examination of nonlinearity in Sigmoidal growth models, Searching for better parameterizations of the growth models.

Main text books :

Introduction to Regression Modeling, by Bovas Abraham , Johannes Ledolter, Duxbury Applied, 2005.

Subsidiary books :

Nonlinear regression modeling: A unified practical approach : David A. Ratkowsky, New York, 1983.

http://www.amazon.com/exec/obidos/search-handle-url?%5Fencoding=UTF8&search-type=ss&index=books&field-author=Johannes%20Ledolter


Stat 413 Stochastic Processes 3 - 3 Stat

312,Math241

Objectives

Studying random processes that depend on time in its development such as population

growth and infection and nuclear spread.

Course Description:

- probability generating function and its characteristic and use - random walk and spread processes as its limit - Markov chain - Stationary distribution - Classifying chains - Poisson processes

Main text books :

Taylor, H. & Karlin, S. (1998). An Introduction to Stochastic Modeling, Academic Press. Bailey, "The elements of Stochastic Processes".

Subsidiary books :

Hoel, "Stochastic Processes". A First Course in Stochastic Processes. Karlin, S and Taylor, H. Academic Press (1975).


Stat 422 Inference Statistics II 3 - 3 Stat 321

Objectives

Studying the theoretical bases for the methods used in testing statistical hypothesis.

Course Description:

- Basic definitions: simple and composite hypothesis, types of error, power and power functions.

- Nyman and Pearson Lemma with applications. - Uniformly most powerful test and its construction with applications. - Likelihood ratio test. - Sequential tests: sequential probability ratio test. - Bays method for hypothesis testing.

Main text books :

G.M. El-Sayyad: "Statistical Inference 1994" دار المريخ

Subsidiary books :

Mood, A. M., F.A. Graybill and D.C. Boss, Introduction to the Theory of Statistics, McGraw.

Hill, (1989).


Stat 424 Decision Theory 3 - 3 Stat 422

Objectives

This course aims at giving the students an idea about some of the method. Applied in

decision making .

Course Description:

- No data decision criterion.

- Decision under partial information .

- Loose tables .

- Using Prior and Posterior Probabilities to compute expected losses.

- Decision tree.

- Loss and Risk Functions.

- Minimax and Bayes decision Functions.

- Parameter space, Prior and Posterior distributions and Bayes estimate .

- Game theory.

Main text books :

- Bernard W. Lindgren, " Statistical theory " 1993 Chapman & Hall/CRC,

Subsidiary books :

Gilbert Gordon and I. Pressman, " Quantitative Decision – Makin for Business ", Prentice

Hall Inter., Inc. ,London (1990).

Barry Render and Ralph M. Stair, Jr., " Quantitative analysis Management " , Allyn and

Bacon, (1990).


Stat 425 Order Statistics 3 - 3 Stat 312

Objectives

To make the students aware of the order statistics principles .

Course Description

- Definition of order statistics-the joint distribution of the first n- th order statistics-

the marginal distributions of the i-th order statistics.

- The joint distribution of the i-th and j-th order statistics – the cumulative distribution

functions of order statistics-the probability density functions of the range and the

median –the moments of the order statistics –order statistics from some specific

distributions.

Main text books:

Barry, C. Arnold, N. Balakrishnan, and H.N.Nagaraja "A First Course in Order Statistics" Wiley

(1992).

Subsidiary books:

Herbert David, and H.N. Nagaraja " Order Statistics" Wiley (2003).


Stat 427 Bayesian Statistics 3 - 3 Stat 312

Objectives

To make the students aware of the order statistics principles .

Course Description:

- Introduction the prior distribution - The posterior distribution-Conjugate and non-

informative priors.-Joint prior and posterior distributions.

- Bayesian point estimation- Bayesian confidence intervals- Bayesian testing

hypotheses.

Main text books:

Michael, J and Rosenthal J, "Probability & Statistics" (2003), W.H. Freeman.

Subsidiary books:

William M. M. Bostad, " Introduction to Baysian Statistics", Wiley.


Stat 436 Medical Statistics 3 - 3 Stat 335

Objectives

To introduce new statistical techniques which are used commonly in Medical

Applications.

Course Description:

- Basic concepts and designs: controlled and uncontrolled clinical trials; historical

controls; randomization; protocol deviations.

- Size of trials.

- Multiplicity and meta-analysis: interim analyses; multi-centre trials; combining

trials.

- Cross-over trials.

- Binary response data: logistic regression modeling; McNemar’s test, relative risks,

odds ratios.

- Survival Data Analysis

- Basic concepts: survivor function; hazard function; censoring.

- Single sample methods: lifetables; Kaplan-Meier survival curve; parametric models.

- Two sample methods: log-rank test; parametric comparisons.

- Regression models: inclusion of covariates; Cox’s proportional hazards model;

competing risks.

Main text books:

Altman, D.G. (1991) Practical Statistics for Medical Research, Chapman & Hall.

Subsidiary books:

Matthews, J.N.S. (2000). An Introduction to Randomized Controlled Clinical Trials, Arnold.


Stat 438 Actuarial Statistical

Models 3 - 3 Stat 357

Objectives

To make the students aware of the statistical principles involved in the insurance and risks.

Course Description:

- Statistical techniques used in insurance - Life table and life insurance - Survival distributions and failure times - Risk theory - Applications of statistics in insurance. -

Main text books:

Promislow, Fundamentals of Actuarial Mathematics.

Subsidiary books:

Dowd, An introduction to market risk measurement.


Stat 442 Programming &

Simulation 2 2 3 Stat 403

Objectives

This course requires that you have some knowledge of statistical methods of estimation and

hypothesis testing from a previous statistics class (STAT 302, STAT 403). This is not really an

advanced programming class but merely an introduction to a very useful statistical package

and uses it to perform some simulation tasks. The objectives of this course are to use the

simulation technique as a tool to explain and verify most of the theorems that were studied

by students during their theory and method courses.

Course Description:

- Introduction to statistical programming. - Introduction to data analysis. - Introduction to data manipulation. - Introduction to simulation. - Simulating one sample with different distributions. - Simulating more than one sample with different distributions. - Simulating the relationships among some of the distributions. - Simulating the Central Limit Theorem. - Simulating T-Test for two samples with and without satisfying the assumptions. - Simulating One-Way ANOVA model with and without satisfying the model

assumptions. - Simulating Simple Linear Regression model with and without satisfying the model

assumptions.

Main text books : (book can be chosen among these books according to statistical program

that will be used)

1. Xitao Fan, Akos Felsovalyi, Stephen A. Sivo, and Sean C. Keenan (2007). SAS for Monte

Carlo Studies: A Guide for Quantitative Researchers, SAS Institute Inc., Cary M, NC, USA.

2. Rebecca J. Elliott (2007). Learning SAS in the Computer Lab, SAS Institute Inc., Cary M, NC,

USA.

3. Applied Statistics and the SAS Programming Language

4. Martinez, W. and Martinez, A. (2002). Computational Statistics Handbook with MATLAB,

Chapman & Hall.

5. Verzani, J. "Using R for Introductory Statistics", Chapman & Hall/CRC; 1st ed.


Stat 450 Data Mining 3 - 3 Stat 403

Objectives

The main purpose is training the students to deal with huge data and their

applications in the real life.

Course Description:

- DIMENSION REDUCTION METHODS: Principal Components Analysis, Factor Analysis

- REGRESSION MODELING: Simple Linear Regression, Least-Squares Estimates, Coefficient of Determination , Standard Error of the Estimate , Correlation Coefficient , ANOVA Table , Regression Model , Inference in Regression ,Verifying the Regression Assumptions.

- MULTIPLE REGRESSION AND MODEL BUILDING: Multiple Regression Model, Inference in Multiple Regression, Regression with Categorical Predictors.

- LOGISTIC REGRESSION: Maximum Likelihood Estimation, Interpreting Logistic Regression Output, Multiple Logistic Regression.

- NAIVE BAYES ESTIMATION AND BAYESIAN NETWORKS: Bayesian Approach, Maximum a Posteriori Classification, Naive Bayes Classification, Bayesian Belief Networks.

- GENETIC ALGORITHMS.

Main text books :

Daniel T. Larose (2007). Data Mining methods and models, Wiley.

Subsidiary books :


Stat 451 Econometrics 3 - 3 Stat 403

Objectives

The main objective is to introduce Econometrics, through explaining the importance

of statistical methods in the field of economic studies and the problems that face economic

researchers.

Course Description:

- Data types in Econometric Theory.

- Overview of Econometric Models.

- BLUE Estimation for Multiple Linear Regression Model.

- Autocorrelation Problem.

- Heteroscedacity Problem.

- Multicollinearity of Explaining Variables Problem.

- Errors in Variables.

- Introduction to Simultaneous Systems.

Main text books :

Maddala, G. (2001), Introduction to Econometrics 3rd Ed., Wiley.

Subsidiary books :

Gujarati, D. N. "Essentials of Econometrics", McGraw-Hill (1998)


Stat 453 Nonparametric

Methods 3 - 3 Stat 302

Objectives

To introduce a collection of non-parametric tests which applicable on data from general

populations.

Course Description:

- Order statistics and their probability distributions. - Distribution of the median, limiting distribution. - Point and interval estimation for median using order statistics. - Sign, signed rank (Wilcoxon) tests for one sample and paired data. - Kolmogrov-Smirnov test for one and two samples. - Mann-Whitney-Wilcoxon test for two samples. - Spearman's rank correlation, Kendall's tau and tests of association based on

them. - Kreskas - Walls test and Friedman test.

Main text books :

Conover, W. "Practical Nonparametric Statistics", 3rd,John Wiley & Sons, (1992).

Subsidary books :

Randles R.H. and D.A. Wolfe, "Introduction to the theory of Non-parametric, 1992, John

Wiley and Sons.


Stat 454 Time Series Analysis 3 - 3 Stat 403

Objectives

To make a scientific study of series changing over time. This is very useful in business, industry, economics, and management where forecasts are needed. Course Description: - Definition of time series. - The aims of time series analysis. - The components of time series. - Additive and multiplicative models. - Auto-covariance, Auto correlation function, stationary, white noise. - Box and Jenkins method. - Random walk model. - Autoregressive process. - Moving average process. Integrated moving average. - Mixed ARIMA models. - The sample autocorrelation function. - Exponential smoothing of time. - Fitting of linear and exponential models. - Use of computers. Main text books : - Chatfield, C., "The Analysis of Time Series" 1993, Chapman and Hall. Subsidiary books : - Fuller, W., "Introduction to Statistical Time Series:, 1990, John Wiley.


Stat 455 Multivariate Analysis 3 - 3 Stat 404

Objectives

To study different statistical methods used on analyzing multivariate variables.

Course Description:

Inference about the mean of multivariate normal distribution, means comparison, principle

analysis, factor analysis, canonical correlation analysis, cluster analysis, classification and

discriminant analysis.

Main text books :

1998

Subsidiary books :

Applied Multivariate Statistical Analysis by Richard A. Johnson, Dean W. Wichern (2002)


Stat 456 Spatial Statistics 3 - 3 Stat 403

Objectives

- Covering the three types of spatial data: point pattern, geo-statistical, and lattice.

- Presenting the application of statistical and computational methods for description, modeling, and analysis for each type of these data.

- learning how to statistically analyze and interpret spatial data.

Course Description:

- Introduction to Spatial Data. - Visualizing Spatial Data. - Analyzing Geo-statistical Data. - Analyzing Lattice Data. - Analyzing Spatial Point Patterns.

Main text books :

Schabenberger, O. and Gotway, C.A. (2005), Statistical Methods for Spatial Data, Chapman and Hall.

Subsidiary books :

Cressie, N. (1993), Statistics for Spatial Data, rev. ed., Wiley.


Stat 463 Queuing Theory 3 - 3 Stat 312

Objectives

This course aims to gain the ability of studying and analyzing real life service systems. This

leads to increase and optimize the performance of these systems.

Course Description:

0. Background: differential and difference equations, Laplace transforms, probability

generating functions, moment generating functions.

1. Introduction: Description of queuing problem, characteristics of queuing processes,

notations, measures of effectiveness, common areas of applications, deterministic

queuing models, Poisson process and the exponential distribution, Markovian

property of the exponential distribution, stochastic processes and Markov chains.

2. Simple Markovian birth-death queuing models: birth-death processes, steady- state

solution for the M|M|1 model, queues with parallel channels M|M|c , queues with

parallel channels and truncation M|M|c|k , Erlang’s formula M|M|c|c, queues with

unlimited service M|M|∞, finite source queues, state-dependent service, queues

with impatience, transient behavior, busy period analysis for M|M|1 and M|M|c.

3. Advanced Markovian models: Bulk input M [x] |M|1, bulk service M|M [y] |1,

Eralangian models M|Ek|1, El|Ek|c, priority queue disciplines.

4. Models with general arrival or service patterns: Single server queues with Poisson

input and general service M|G|1), multi-server queues with Poisson input and

general service, general input and exponential service G|M|c.

Main text books:

Taha, H.A. Operations Research: An Introduction. Macmillan Publishing Co., New York, 1997.

Subsidiary books:

Gross D., Harris C.M. Fundamentals of Queuing Theory. 4th edition, John Wiley, 2008.


Stat 480 Special Topics 2 - 2 Department

Approval

Objectives The purpose of this course is to teach the students new topics arising in Statistical field, not

covered in the courses presented by the department.

Course Description:

The topics is suggested by the instructor and approved by the department council.

Main text books: as needed

Subsidiary books: as needed


Stat 491 Research Project 3 - 3 Department

Approval

Objectives To train student on doing research and presenting it. A problem will be assigned to student

to solve it via collecting data related to the topic then summarizing and analyzing the

collected data then present these in a form of thesis that will be discussed with the student

in a seminar.

Main text books :

Choosing a reference depend on the research topic and student can look at the subsidiary

books on ways of how to write a thesis.

Subsidiary books :

1968

Day, R. (1989). How to Write and Publish a Scientific Paper. ISI Press.

statistical courses description - kaukau.edu.sa/files/13012/files/28644_english description...

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