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List of Courses
* All credit hours are based on the current term, this may vary for previous terms.
| STAT101 - Statistics in the Modern World |
(3 credit hours) |
The course aims to explore and learn about popular real-world topics using statistics as a tool. It discusses statistical application in population growth, economic developments, income distribution and environmental changes. Key statistical tools will be introduced through their applications in real world issues.
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| STAT105 - Statistics For Business(1) |
(3 credit hours) |
This course aims at training students to handle statistical exploratory, descriptive, and estimation tools in business applications. It covers samples and populations, descriptive statistics, tabular and graphical presentation, random sampling, probability, independence, Binomial distribution, Normal distribution, sampling distributions and statistical estimation.
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| Prerequisite: |
- MATU1312 or MATU1332 or INTU1302
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| STAT1202D - Statistics In Ed. & Psychology |
(3 credit hours) |
This course aims at introducing the basic methods for collecting and analyzing data pertaining to studies in education and psychology. It includes basic concepts, data classification, sample and population, frequency distributions, graphics, measures of location and dispersion and normal distributions, correlation, applications in education and psychology.
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| STAT125 - Statistics For Business(2) |
(3 credit hours) |
This course aims at training students to use statistical methods for making decisions in Business and Economics. This course includes hypothesis testing for one and two means and for one and two proportions, nonparametric tests, single factor analysis of variance, chi-square test for goodness?of?fit, chi-square test for independence, contingency tables, simple and multiple regression and time series analysis.
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| Prerequisite: |
- STAT105
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| STAT130 - Statistics for Business |
(3 credit hours) |
This course aims at introducing students to the fundamental concepts of statistics and training them to apply the basic methods and techniques of statistical analysis in business and economics problems. It covers basic concepts, sources and methods of data collection, tabular and graphical presentation of data, descriptive statistics, introduction to probability and probability distributions, sampling distributions, statistical estimation, hypotheses testing, analysis of variance, chi-square test of independence, and correlation and regression analysis.
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| Prerequisite: |
- MATU1312 or MATU1425 or MATU1435
- ENGU1304 or ENGU1305
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| STAT180 - PsychologIcal Statistics 1 |
(3 credit hours) |
This course aims at introducing the basic concepts and elementary applications of statistics that are widely utilized by psychologists. It covers data description, central tendency measures, variability indicators, and degrees of peakedness and asymmetry of data distributions. In addition, the normal distribution, standard scores, correlation and their applications in psychology and as well as hypothesis testing will be studied in this course. Statistical packages will be used throughout the course to work out psychological applications.
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| STAT210 - Probability and Statistics |
(3 credit hours) |
This course aims at introducing the basic concepts of statistics and probability that are widely utilized in IT applications. It covers such topics as events and sample space, probability, conditional probability, random variables, cumulative distribution functions and probability density functions, moments of random variables, common distribution functions, elementary introduction to statistics with emphasis on applications and model formulation, descriptive statistics, sampling and sampling distributions, inference, t tests, one-way analysis of variance, correlation and regression, and chi-square tests.
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| Prerequisite: |
- MATH110
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| STAT215 - Social Statistics (1) |
(3 credit hours) |
This course aims at providing students with statistical methods for modeling and analyzing social data. It includes data collection, tabulation and graphical presentation, statistical measures, cross-tabulation analysis, and principles of survey data analysis using statistical packages. It emphasizes the use of the computer package (SPSS) to analyze real social data.
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| STAT2152 - Social Statistics (1) |
(3 credit hours) |
This course aims at providing students with statistical methods for modeling and analyzing social data. It includes data collection, tabulation and graphical presentation, statistical measures, cross-tabulation analysis, and principles of survey data analysis using statistical packages. It emphasizes the use of the computer package (SPSS) to analyze real social data.
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| STAT220 - Engineering Statistics |
(2 credit hours) |
This course covers concepts of probability theory and statistical applications in engineering systems. It includes engineering applications of probability theory, sampling theory, random samples, random variables, probability models, basic statistics, confidence intervals, hypothesis testing, inference, simple linear regression.
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| Prerequisite: |
- MATH1110
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| STAT230 - Principles Of Probability |
(3 credit hours) |
This course is an introduction to the principles and laws of probability. It aims at giving the student a thorough understanding of the concepts of probability, conditional probability, random variables and probability distributions, moment generating function, bivariate and marginal distribution functions, conditional distributions and expectations. Although the primary focus of the course is on a mathematical development of the subject, it also includes a variety of illustrative examples and exercises that are oriented towards applications in the social and physical sciences.
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| Prerequisite: |
- MATH115 or MATH110
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Fall Spring |
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| STAT235 - Statistics for Biology |
(3 credit hours) |
This is an introductory statistics course for students in biological and agricultural sciences who have no formal background in statistics. It covers the basic statistical methods for describing and analyzing data arising in the life sciences. The emphasis is on the intuitive understanding of concepts rather than the underlying mathematical developments. Applications and data analysis are based on the statistical package Minitab.
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| Prerequisite: |
- MATH105
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Fall Spring |
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| STAT236 - Statistical Packages |
(3 credit hours) |
This course aims at acquainting students with commonly used statistical packages and enhancing their data analysis skills. It includes an introduction to Minitab, SPSS, SAS, missing values, data manipulatioon, tabulation, descriptive statistics, hypothesis testing, ANOVA and regression.
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| Prerequisite: |
- STAT125
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Spring |
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| STAT242 - Non-Parametric Statistics |
(3 credit hours) |
This course develops student’s understanding of the methodology and the theory underlying a number of statistical techniques applicable in solving real-life inference problems under minimal assumptions about the underlying distribution of the data. It covers the following topics: order statistics, distribution free tests, single and multi-sample rank statistics, Pittman's efficiency and rank correlations.
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| Prerequisite: |
- STAT125 or STAT130
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Fall Spring |
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| STAT245 - Prob. and Stat for Education |
(3 credit hours) |
The course aims at introducing students to the basic concepts and methods of probability and statistics with applications in the education field. It includes sample spaces and events; counting techniques; probability; conditional probability; random variables; cumulative distribution function and probability density function; moments of random variables; sampling and sampling distributions, inference about means and proportions, correlation and simple regression.
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- MATH110
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Fall Spring |
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| STAT280 - Psychological Statistics 2 |
(3 credit hours) |
This course aims at introducing the basic concepts of statistical inference and their applications in psychology. It covers sampling distributions, point and interval estimation, statistical hypothesis testing, correlation, regression and prediction, analysis of variance and factorial ANOVA. Statistical packages will be used throughout the course to work out psychological applications.
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| Prerequisite: |
- STAT180
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| STAT320 - Applied Random Processes |
(3 credit hours) |
The main topics of this course include an introduction to stochastic processes as models of time-dependent random phenomena, Markov chains, Fourier Transforms, Queuing Theory.
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| Prerequisite: |
- ITBP203 or STAT210
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| STAT331 - Design Of Experiments |
(3 credit hours) |
This course aims at training students to select the appropriate design for an experiment and analyze its results using statistical packages. It includes completely randomized designs, ANOVA, multiple comparisons, residual analysis, factorial experiments, analysis of covariance, randomized block designs and Latin squares.
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- STAT125 or STAT130
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Fall |
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| STAT338 - Regression Analysis |
(3 credit hours) |
This course aims at introducing students to the methods of regression analysis and training them to fit regression models to data. This course includes simple and multiple linear regression, dummy variable regression, model selection, diagnostics for residuals, multi-collinearity detection, transformations, lack-of-fit tests, partial and sequential F-tests.
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| Prerequisite: |
- STAT125 or STAT130
- STAT230
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Spring |
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| STAT340 - Mathematical Statistics |
(3 credit hours) |
This course aims at introducing the basic concepts of estimation and hypothesis testing. It includes point estimation, properties of estimators, method of moments, method of maximum likelihood, method of least squares, interval estimation, most powerful tests and likelihood ratio tests. It also covers some common confidence intervals and tests for means, variances and proportions.
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- STAT230
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Fall Spring |
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| STAT369 - Demographic Analysis |
(3 credit hours) |
This course aims at introducing techniques of demographic analysis and enhancing the students' data analysis skills with the use of computer packages. It includes vital statistics, rates and proportions, mortality, fertility and migration, life tables, population projections, and estimation.
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| Prerequisite: |
- STAT125 or STAT215 or STAT2152
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Fall |
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| STAT422 - Sampling Techniques |
(3 credit hours) |
The course develops an understanding of survey research methodologies and data collection methods from scientific and practical perspectives. It emphasizes training students on alternative sample designs used to produce statistical inferences to solve real-life problems. In addition to discussing survey methods and design, it covers: simple, stratified, systematic and cluster sampling, ratio and regression estimates, errors in sample surveys and case studies.
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- STAT230
- STAT125 or STAT130
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Spring |
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| STAT433 - Time Series Analysis |
(3 credit hours) |
This course aims at training students to select the appropriate time series model, estimate the parameters and make forecasts. It includes time series regression, classical decomposition, exponential smoothing, autocorrelation and partial autocorrelation functions, stationary and homogeneous time series, autoregressive, moving average, ARMA and ARIMA models and seasonal models, Box-Jenkins methodology and business applications.
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| Prerequisite: |
- STAT338
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Fall |
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| STAT461 - Applied Multivariate Analysis |
(3 credit hours) |
This course introduces students to the methodology and applications of multivariate statistical analysis. It covers multivariate analysis of variance and regression, canonical correlations, principal components, factor analysis, discrimination, classification and cluster analysis. The emphasis is on computer implementation and applications to the various sciences rather than the theoretical aspects of the topics.
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| Prerequisite: |
- STAT338
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Fall Spring |
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| STAT462 - Categorical Data Analysis |
(3 credit hours) |
This course is an introduction to topics in categorical data analysis. It is an applied course emphasizing the modeling and the analysis of categorical data using the statistical package SPSS. Both descriptive and inferential methods are discussed. The covered topics include measures of association, tests of goodness-of-fit, tests of independence, exact tests, logit and probit models and discriminant analysis.
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| Prerequisite: |
- STAT338
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| STAT469 - Statistical Quality Control |
(3 credit hours) |
This course aims at introducing the basic process control and acceptance sampling techniques. It covers the objectives of statistical quality control, control charts for variables, control charts for attributes, acceptance sampling, single, double and multiple sampling, and the OC curve.
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| Prerequisite: |
- STAT340
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| STAT472 - Statistical Computing |
(3 credit hours) |
The course introduces students to common computational techniques needed in statistics. It covers, in particular, data manipulation and cleaning techniques, sampling, simulation, resampling, maximum likelihood estimation and elementary Bayesian analysis. These techniques will be demonstrated using prominent statistical packages.
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| Prerequisite: |
- STAT340
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Spring |
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| STAT480 - Seminar in Applied Stat. (E) |
(3 credit hours) |
This course uses the case teaching technique. During the course students will work in groups to solve various cases / capstone experiences / projects. Students are also expected to write reports and give oral presentations for each project. Each group will be assigned a project that requires the use of international, national and /or official statistical databases.
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- STAT331
- STAT338
- STAT422
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Fall Spring |
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| STAT503 - Applied Statistics |
(2 credit hours) |
This course is dedicated to graduate students from Faculty of Science. It aims at introducing the students to the basic statistical procedures commonly used in the analysis of scientific and environmental problems. These statistical applications complement and reinforce scientific and environmental concepts and methods, particularly in practical, development and assessment models, and interpretation of data and results. It includes numerical and graphical description of data, techniques for significance evaluation and relationships.
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Fall Spring |
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| STAT607 - Decision Techniques& Data Anal |
(3 credit hours) |
The course provides a structured approach for describing, analyzing, and finalizing decisions involving uncertainty. It introduces various decision analysis techniques and principles of designing decision support systems for carrying out sensitivity analysis. It also presents key statistical techniques used in modeling and analyzing business data and providing empirical evidence for action recommendation.
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Spring |
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| STAT609 - Decision Techs.& Data Analysis |
(3 credit hours) |
The course provides a structured approach for describing, analyzing, and finalizing decisions involving uncertainty. It introduces various decision analysis techniques and principles of designing decision support systems for carrying out sensitivity analysis. It also presents key probability and statistical techniques used in modeling and analyzing business data and providing empirical evidence for action recommendation. Topics include decision analysis techniques, descriptive and inferential statistics, one-way and two-way analysis of variance, modeling using regression analysis, times series regression, exponential smoothing and forecasting.
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| STAT612 - Experimental Design& Analysis |
(3 credit hours) |
Steps in planning experiments; principles of experimental design; application of some designs in product development systems and evaluation factorial design; linear programming, CRD, RCD, LS, regression and correlation: and inspection of mean differences.
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Fall Spring |
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| STAT621 - Multivariate Systems& Modeling |
(3 credit hours) |
Mathematical models for evaluating resource management strategies. Stochastic and deterministic simulation for optimization. System control structures. Team modeling approach.
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| STAT640 - Stat.& Quantitative Analysis |
(3 credit hours) |
This course prepares MBA students to design and conduct research to address and solve business challenges. It provides an empirical basis for the analysis and action recommendations for the solution of business problems or for the achievement of business objectives. MBA students will learn to frame, plan, and conduct research projects as well as developing and fine-tuning forecasting models. Students will apply key statistical techniques used in modeling and analyzing research findings and business data.
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| STAT659 - Applied Statistics |
(2 credit hours) |
This is a graduate course at the Master level covering the principles of risk and uncertainty applied to hydraulic, environmental and other water-related problems. It includes such topics as statistical measures and graphs, parametric and non-parametric statistical inference, analysis of variance, multiple regression and correlation.
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| STAT661 - Geo-Statistics |
(2 credit hours) |
Computer-based methods in geographical analysis. Focuses on bivariate and multivariate regression, discrimination analysis, factor analysis, and analysis of spatial and temporal data.
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| STAT701 - Applied Petroleum Statistics |
(2 credit hours) |
Computer-based statistical methods in petroleum sciences and engineering. Focuses on estimation of parameters, comparisons of treatments, multivariate techniques such as multivariate regression, discrimination analysis and Statistical analysis of field and petroleum engineering data.
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| STAT703 - Stat.&Quality Assur. for CE |
(3 credit hours) |
Sampling distributions, Inferences concerning means and variances, Curve fitting, Analysis of variance, Factorial experimentation, Experimental design for quality improvement, Quality control, Control Charts for measurements and attributes, acceptance sampling, Quality assurance for construction, Quality systems and requirements for CE, Project quality management, Developing a quality system.
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| STAT715 - Design/Analysis of Experiments |
(3 credit hours) |
This course focuses on design of experiments, optimum selection of input for experiments, and the analysis of results. Full factorial as well as fractional factorial designs, response surface designs, complete randomized designs, ANOVA, multiple regression, normal probability plot, importance of analyzing interactions, signal to noise ratios, confidence intervals, and variance reduction analysis are covered in this course. Statistical analysis software such as SPSS and Minitab will be used.
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| Prerequisite: |
- or STAT701 or STAT659 or STAT607 or STAT701 or STAT659
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