Brief COURSE
DESCRIPTIONS
Course Description:
Course Number: STAT 101
Course Name: Statistics I
Credit Hours: 3 (2+2)
Pre-requisite: None
Semester Offered: Fall
Course Content: 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.
Course Number: STAT 102
Course Name: Statistics II
Credit Hours: 3 (2+2)
Pre-requisite: STAT 101
Semester Offered: Spring
Course Content: 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.
Course Number: STAT 211
Course Name: Introduction to Probability
Credit Hours: 3 (2+2)
Pre-requisite: MATH 102 and STAT 101
Semester Offered: Fall
Course Content : 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.
Course Number: STAT 221
Course Name: Mathematical Statistics I
Credit Hours: 3 (2+2)
Pre-requisite: STAT 211 and MATH 251
Semester Offered: Spring
Course Content: The Multinomial and multivariate normal distributions. Functions of
2
random variables. Transformation techniques. Sampling Distributions, the t, the  , 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.
Course Number: STAT 231
Course Name: Applied Regression Analysis
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102 and STAT 211
Semester Offered: Spring
Course Content:
Simple 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.
Course Number: STAT 241
Course Name: Biostatistics
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102 or STAT 151
Semester Offered: Fall
Course Content : 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.
Course Number: STAT 242
Course Name: Demography
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102
Semester Offered: Spring
Course Contents: Basic Concepts, Meaning of population, Demographic rates. Period
rates. Person years. Growth rate. The concept of cohort. The crude death rate. Agespecific 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
Course Number: STAT 312
Course Name: Stochastic Processes
Credit Hours: 3 (2+2)
Pre-requisite: STAT 211 and MATH 251
Semester Offered: Fall
Course Content : 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.
.
Course Number: STAT 322
Course Name: Mathematical Statistics II
Credit Hours: 3 (2+2)
Pre-requisite: STAT 221
Semester Offered: Fall
Course Content: 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.
Course Number: STAT 332
Course Name: Designs of Experiments
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102 and STAT 211
Semester Offered: Fall
Course Content : 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.
Course Number: STAT 333
Course Name: Time Series
Credit Hours: 3 (2+2)
Pre-requisite: STAT 231
Semester Offered: Spring
Course Content: This course 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.
Course Number: STAT 341
Course Name: Actuarial Statistics I
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102 and STAT 211
Semester Offered: Spring
Course
contents:
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.
Course Number: STAT 343
Course Name: Applied Survival Analysis
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102
Semester Offered: Fall
Course contents: 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.
Course Number: STAT 344
Course Name: Quality Control
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102 and STAT 211
Semester Offered: Spring
Course Content: 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.
Course Number: STAT 361
Course Name: Sampling Methods
Credit Hours: 3 (2+2)
Pre-requisite: STAT 102 and STAT 211
Semester Offered: Spring
Course Content:
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; Nonresponse and Non-sampling Errors Adjustment.
Course Number: STAT 371
Course Name: Statistical Packages
Credit Hours: 3 (2+2)
Pre-requisite: STAT 231
Semester Offered: Fall
Course Content: 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. Weeknesses and strengths are discussed. Effective
use of Statistical packages in solving real life problems. Advanced features of statistical
packages.
Course Number: STAT 372
Course Name: Statistical Simulation
Credit Hours: 3 (2+2)
Pre-requisite: STAT 211
Semester Offered: Fall
Course Content: 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.
Course Number: STAT 381
Course Name: Categorical Data Analysis
Credit Hours: 3 (2+2)
Pre-requisite: STAT 231
Semester Offered: Spring
Course Content : 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.
Course Number: STAT 382
Course Name: Non-Parametric Methods
Credit Hours: 3 (2+2)
Pre-requisite: STAT 221
Semester Offered: Fall
Course Content: Basic 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.
Course Number: STAT 434
Course Name: Generalized Linear Models
Credit Hours: 3 (2+2)
Pre-requisite: STAT 322
Semester Offered: Fall
Course Contents: 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.
Course Number: STAT 442
Course Name: Actuarial Statistics II
Credit Hours: 3 (2+2)
Pre-requisite: STAT 341
Semester Offered: Fall
Course Content: 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.
Course Number: STAT 445
Course Name: Reliability and Life Testing
Credit Hours: 3 (2+2)
Pre-requisite: STAT 322
Semester Offered: Spring
Course Content: 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.
Course Number: STAT 464
Course Name: Environmental Statistics
Credit Hours: 3 (2+2)
Pre-requisite: STAT 312 & STAT 361
Semester Offered: Spring
Course Content: Stochastic processes in the Environment. Fitting probability models
to Environmental data. Tail Exponential Method. Poisson Processes and its application.
Negative binomial model (Contagion and True Models). Capture-Recapture Method,
Distance Sampling, Composite sampling, Introduction of Rank Set sampling methods,
adaptive cluster sampling and adaptive allocation methods.
Course Number: STAT 481
Course Name: Multivariate Analysis
Credit Hours: 3 (2+2)
Pre-requisite: STAT 322 and Math 231
Semester Offered: Fall
Course Content:
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.
Course Number: STAT 482
Course Name: Bayesian Statistics
Credit Hours: 3 (2+2)
Pre-requisite: STAT 322
Semester Offered: Fall
Course contents: 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.
Course Number: STAT 498
Course Name: Special Topics
Credit Hours: 3
Pre-requisite: Departmental Approval
Semester Offered: Fall
Course Content: 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.
Course Number: STAT 499
Course Name: Graduation Project
Credit Hours: 3
Pre-requisite: Departmental Approval
Semester Offered: Spring
Course Content: 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.