Stat 101-Statistics I (3 CH)
Stat 101 is a compulsory course for statistics students. It is also offered for non-statistics students. The course mainly covers the Basic concepts, Population. Types of data, Sampling methods, Tables and graphs. Descriptive Statistics, Basic probability concepts, Random experiment. Sample space, Rules of probability. Counting techniques. Conditional probability. Independence, Discrete and continuous random variables. Sampling distributions, The Student-t distribution, F – distribution and Chi-Square distribution, Point estimation. Confidence intervals for a single population, Testing hypotheses for a single population. Statistical software like Minitab and Excel are used.
Stat 102- Statistics II (3 CH)
Stat 102 is a compulsory course for statistics students. It is also offered as a compulsory course for non-statistics students. The course mainly covers the following topics: Chi-Square Procedures, The Chi-square distribution. Chi-square goodness of fit test. Contingency tables. Association. Chi-square test for independence. The F-distribution. The completely randomized design. Multiple comparisons. The randomized block design. The two factor factorial design, Simple regression equation. Inference about the regression quantities. Nonparametric Statistics, The sign test and Wilcoxon signed rank test, the Wilcoxon rank sum test. The kruskall-Wallis test. The Friedman test. The Spearman correlation coefficient. Statistical software like Minitab and Excel are used.
Stat 151- Introduction to Applied Statistics (3 CH)
Stat 151 “Introduction to Applied statistics” is an elective three credit hours course devoted mainly for students in pharmacy and biomedical sciences. The course concentrates on the role of basic Statistics in solving real life real life problems. The topics include descriptive and some inferential Statistics. It is objective is to initiate and develop the use of the methods and skills required to deal with bio-data. There is no prerequisite for Stat 151 while it is important for the students to expect solving problems need critical thinking in selecting the best appropriate method and the results interpretation. We used a computer package –excel or Minitab- so I expect my student to have basic needs in the computer skills. Some basic knowledge in probability are presented in purpose of well understand of the statistical inference.
Stat 211- Introduction to Probability (3 CH)
Stat 211 is the first course in probability in probability theory offered for statistics students. It is a compulsory course for statistics students. It mainly covers the Random experiment. Sample spaces, Events. Axioms and rules of probability. Equally likely sample spaces. Counting techniques, Conditional probability. Random variables. Expected values. Moment generating function. Probability generating function, Probability distributions, uniform, Bernoulli, binomial, geometric, negative binomial, Poisson and hypergeometric. exponential, gamma, beta and normal. Discrete and continuous bivariate random variables. Joint, Marginal and conditional distributions.
Stat 221- Mathematical Statistics I (3CH)
This course is the first course of two courses in mathematical statistics. This course is a compulsory for the statistics major. The topics to be covered in this course are: the Multinomial and multivariate normal distributions. Functions of random variables. Transformation techniques. Sampling Distributions, the t, the 2, and the F distributions. The distribution of a single order statistic. The joint distribution of two order statistics. Distributions of functions of order statistics. Limit Theorems, Convergence in distribution, Convergence in Probability, Laws of large numbers. Limiting distributions. The Central limit theorem
Stat 231- Applied Regression analysis (3CH)
This course is a second year course in statistics which is offered for Statistics students. The course covers: Linear Regression; Residual Analysis; Autocorrelation; Multiple Regression; Parameter Estimation and Testing; Model Selection Procedures; Polynomial Regression; Indicator Variables; Multicollinearity; Outliers and Influential Observation. Statistical software like Minitab, SPSS and R are used.
Stat 241- Biostatistics(3 CH)
The course is an elective course for the statistics students. It includes the following topics: Methods of Sampling in Medical Studies; Summarizing and Presenting Medical Data; Demographic Statistics; Survival Analysis; Analysis of Cross Tabulation; Inference for Means; Parametric and Non-Parametric with applications to medical data; Multiple Linear, Logistic, Poisson and Cox regression applied to medical data; Sample Size Determination. Statistical software like Minitab and Excel are used.
Stat 242- Demography(3 CH)
Stat 242 is also an elective course for the statistics students. It covers the topics: Basic Concepts, Meaning of population, Demographic rates. Period rates. Person years. Growth rate. The concept of cohort. The crude death rate. Age-specific death rates. The Lexis diagram. Mortality rates. Single-failure indices. The standardized death rate. The standardized mortality ratio. Life Tables, Multiple Decrement Life Tables, Fertility and Reproduction, Modeling Age Patterns.
Stat 312- Stochastic Processes(3 CH)
This course is a third year and compulsory course for statistics students. It covers: elements of Stochastic Processes; Discrete Time Markov Chains; Random Walks; Branching Processes; Poisson Processes; Birth and Death Processes; Queuing Systems; Renewal Processes. Basic theory of martingales and Brownian motion. Applications to stochastic financial modeling.
Stat 322- Mathematical Statistics II (3 CH)
This course is a major course in the study plan for statistics students. It includes: Consistency, Sufficiency, the exponential family of distributions. Completeness of a family of distributions. Theory of Point Estimation, Criteria for judging point estimators. The mean squared error and the variance. Unbiasedness, Rao-Blackwell Theorem. Uniformly minimum variance unbiased estimation. Lower bounds of the variance of unbiased estimators. Information. Efficiency of an estimator. Maximum likelihood method. Moments method. Least squares method. Comparisons between the different methods. Interval estimation, Pivotal quantities. A General method for confidence intervals. Large sample confidence interval. Test of hypotheses, most powerful test. Neyman-Pearson lemma. Uniformly most powerful test. Uniformly most powerful unbiased test. Likelihood ratio test. Sequential tests. Large sample tests.
Stat 332- Experimental Design(3 CH)
The course is compulsory and covers the topics: Principles of Experimental Design; Completely Randomized designs; Randomized Complete Block designs; Latin Square designs; Incomplete Block Designs; Factorial Experiments; Split Plot; Analysis of Covariance. Statistical software like Minitab, SPSS and R are used.
Stat 333- Times Series(3 CH)
This course is compulsory and discusses the analysis of time series data and their use in prediction and forecasting. The course presents various methods including time series regression, smoothing techniques and the Box-Jenkins methodology. The emphasize is on the applied side of the subject utilizing statistical packages like R, SPSS and Minitab.
Stat 341- Actuarial Statistics I(3 CH)
It is the first course of two elective courses in actuarial statistics. Also it is an elective course covers the topics: Actuarial models, classifying and creating distributions. Frequency and severity with coverage models, deductibles, policy limits and coinsuranse. Aggregrate loss models, compoubd models, computing aggregate claims distributions, comparison beteen the various computing methods. Discrete and Continuous time ruin models.
Stat 343- Applied Survival Analysis(3 CH)This course is also an elective course which covers the topic: Censored data, types of censoring, examples of survival data analysis, the survival function, the hazard function, Nonparametric Methods, Life tables, the Product-Limit Estimator of the survival function, comparing two survival distributions (Mantel-Haenszel test), Parametric Survival Distributions and Inference, Goodness of Fit for Survival, Parametric Regression Models, Cox’s Proportional Hazards Model. Statistical software like Minitab, SPSS and R are used.
Stat 344- Quality control(3 CH)
An elective course covers: Analysis of Control Charts for Variables and Attributes; Histogram Analysis; Process Capability; Standard Acceptance Sampling Plans; Process Reliability. Statistical software like Minitab and SPSS are used.
Stat 361- Sampling Methods(3 CH)
It is a compulsory course for statistics students. Principles of sampling; questionnaire Design; Simple random sampling; Stratified and Cluster Sampling; Ratio and Regression estimation; Systematic Sampling; Multistage and Multiphase Sampling; Determination of the sample Size; Non-response and Non-sampling Errors Adjustment.
Stat 371- Statistical Packages(3 CH)
A compulsory course covers: Detailed use and full exploitation of Statistical Packages such as SPSS, MINITAB, R and SAS in working with Data; Topics include Data Entry, checking, manipulation and Analysis. Comparison between the different packages, their advantages and disadvantages. Weaknesses and strengths are discussed. Effective use of Statistical packages in solving real life problems. Advanced features of statistical packages.
Stat 372- Statistical Simulation(3 CH)
A compulsory course covers: Detailed use and full exploitation of Statistical Packages such as SPSS, MINITAB, R and SAS in working with Data; Topics include Data Entry, checking, manipulation and Analysis. Comparison between the different packages, their advantages and disadvantages. Weaknesses and strengths are discussed. Effective use of Statistical packages in solving real life problems. Advanced features of statistical packages.
Stat 372- Statistical Simulation(3 CH)
An elective course covers the topics: Generating of Discrete and Continuous Random Variables; Bootstrapping; Variance Reduction Techniques; Model Design and Simulation with Applications Including Queuing and other Applications; Verification and Validation of the Model. Using Statistical software like Minitab, SPSS and R.
Stat 381- Categorical Data Analysis(3 CH)
This course is elective third year course in statistics. It covers the following topics: contingency Tables; Measures of Association; Exact and Asymptotic methods for 2x2 and rxc Contingency Tables; Probit and Logistic Regression Models for Binary Data; Loglinear Models for Multiway Contingency Tables. Statistical software like Minitab, SPSS and R are used.
Stat 382- Non-parametric Statistics (3 CH)
This course an elective covers: Concepts of Non-Parametric Methods; Testing and Estimation for one, Two, and Several sample Problems; Independent and Paired; Location and Dispersion Problems; Goodness of Fit Tests; Tests for Trends and Association; Analysis of variance of Ranked Data; Pittman Efficiency of Non-Parametric Methods. Statistical software like Minitab, SPSS and R are used.
Stat 334- Generalized Linear Models (3 CH)
This course is an elective course. The topics to be covered are: Basic The Exponential family of distributions, Properties of distributions in the Exponential family, Generalized linear models, Examples, Inference in Generalized Linear Models, Model Adequacy and Diagnostics, The deviance statistic, The residuals, modifications of the residuals and model checks based on the residuals. Special Cases of Generalized Linear Models, Normal theory linear models, Binary logistic regression, Nominal and ordinal logistic regression, Poisson regression and Loglinear models. Statistical software like Minitab, SPSS and R are used.|
Stat 442- Actuarial Statistics II(3 CH)
This the second course of two elective courses in actuarial statistics. It covers the topics: Construction of Empirical Models, estimation for grouped and modified data, kernel density estimators. Parametric Statistical methods, estimation and confidence intervals in actuarial models. Model Selection, graphical methods, goodness of fit techniques. Credibility theory, Simulation of actuarial models, Case study examples.
Stat 445- Reliability and Life Testing(3 CH)
This course an elective course. Reliability Concepts; Component and System Reliability; Notions of Aging; Lifetime Distributions and Hazard Functions; Types of Censoring; Nonparametric Estimation of Reliability Function; Kaplan-Meier and Nelson Estimators; Parametric Inference Procedures for Exponential, Weibull and Extreme Value Distributions; Proportional Hazards Regression Model; Accelerated Life Testing; Stress-Strength Models. Statistical software like Minitab, SPSS and R are used.
Stat 481- Multivariate Analysis(3 CH)
This course is compulsory course in statistics. It covers the multivariate topics: Organization of Multivariate Data; Multivariate Distributions; Mahalanobis Distance; Hotelling's T2; Multivariate Analysis of Variance and Regression; Data Reduction Techniques; Discriminant and Classification Analysis; Canonical Correlation Analysis. Statistical software like Minitab, SPSS and R are used.
Stat 482- Bayesian Statistics(3 CH)
An elective course in Bayesian statistics. The topics of this course includes: Nature of Bayesian Statistics, Prior and posterior distributions. Noninformative priors. Jeffereys rule. Conjugate priors. Bayesian Inference, Quadratic loss function and Bayes estimators, Highest posterior density intervals, Bayesian tests of hypothesis. Bayesian methods in the normal and some other distributions. Approximate Bayesian Methods, Asymptotic approximations of the Bayes estimator, The Lindley and Tierney-Kadane methods, Markov chain Monte Carlo methods and the Gibbs sampler.
Stat 498- Special topics (3 CH)
An elective course. Studies topics in statistics that are not part of the regular offerings. Topics will be selected by statistics faculty members as appropriate. In each offering, a topic of the choice of the instructor will be studied in depth as a regular course.
Stat 499- Senior Project (3 CH)
It is a compulsory course for each Statistics students. A variety of skills learned throughout the curriculum are combined by expecting students to work through a variety of cases studies. Students are expected to collect data and analyze the data individually. Oral and written research reports suitable in format and content are required.