Download statistics undergraduate courses

STATISTICS UNDERGRADUATE COURSES
STAT 201
Introduction to Statistics
(2-2-3)
Descriptive statistics: measures of location, dispersion, and skewness. Probability. Random
variables. Normal and Binomial probability distributions. Sampling distribution of the mean.
Estimation. Testing hypotheses. Regression and correlation. Applications using statistical
packages.
Note: Not to be taken for credit with Stat 319 or ISE 205
Prerequisite: MATH 102
STAT 211
Statistics for Business I
(3-0-3)
Data description: Frequency table, histogram, measures of central tendency, scatter diagram
and correlation. Probability theory; sampling; probability distributions; point and confidence
interval estimation; application for managerial decision. A statistical package will be used.
Note: Not open for credit to Statistics or Mathematics Majors, Not to be taken for credit with
ISE 205, STAT 201 and STAT 319.
Prerequisite: MATH 131, MATH 132
STAT 212
Statistics for Business II
(3-0-3)
Hypothesis testing for means and variances; index numbers and time series; simple linear
progression and correlation analysis; multiple regression analysis; the chi-squared and F
distributions and their applications. A statistical package will be used.
Note: Not open for credit to Statistics or Mathematics Majors, Not to be taken for credit with
ISE 205, STAT 201 and STAT 319.
Prerequisite: STAT 211
STAT 213
Statistical Methods for Actuaries
(2-2-3)
Descriptive Statistics: Frequency table; histogram, measure of central tendency and
variability, scatter diagram and correlation. Probability theory; sampling techniques;
probability distributions; estimation; hypothesis testing for means and variances; index
number and introductory time series analyses; simple linear regression and correlation
analysis; multiple regression analysis; the chi-squared and F distributions and their
applications; application for financial decisions; application using statistical packages.
Note: Not to be taken for credit with STAT 201, STAT 211, STAT 212, or STAT 319.
Prerequisite: MATH 102
STAT 301
Introduction to Probability Theory
(3-0-3)
Basic classical models of probability. Set functions. Axiomatic definition of probability.
Conditional probability and Bayes’ theorem. Random variables and their types. Distributions,
moments, and moment generating functions. Special discrete and continuous distributions.
Random vectors and their distributions. Marginal and conditional distributions. Independent
random variables. Functions of random variables. Sums of independent random variables.
Weak law of large numbers and the central limit theorem.
Prerequisite: MATH 201, STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 302
Statistical Inference
(3-0-3)
Random sampling and the sampling distributions: t, chi-square, and F. Order Statistics.
Methods of estimation: maximum likelihood and moments. Properties of a good estimator:
unbiasedness, consistency, efficiency, sufficiency, and approximate normality. Testing of
simple hypotheses, the Neyman-Pearson lemma. Testing composite hypotheses, uniformly
most powerful and likelihood ratio tests. Bayesian Statistics.
Prerequisite: STAT 301
STAT 310
Regression Analysis
(3-0-3)
Simple linear regression: The least squares method, parameter estimation, confidence
intervals, tests of hypotheses and model adequacy checking. Multiple linear regression,
including estimation of parameters, confidence intervals, tests of hypotheses and prediction.
Model adequacy checking and multicollinearity. Polynomial regression. Variable selection
and model building.
Prerequisite: STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 319
Probability and Statistics for Engineers and Scientist
(2-3-3)
Presentation and interpretation of data, elementary probability concepts, random variables and
probability distributions, binomial, Poisson, exponential, Weibull, normal and lognormal
random variables. Estimation, tests of hypotheses for the one sample problem. Simple and
multiple linear regression, application to engineering problems. The lab session will be
devoted to problem solving using statistics software.
Note: Not open for credit to Statistics or Mathematics Majors, Cannot be taken for credit with
ISE 205 or STAT 201.
Prerequisite: MATH 102
STAT 320
Statistical Quality Control
(3-0-3)
How control charts work. Control chart methods for attributes and variables. Process-control
chart techniques. Process-capability analysis. Acceptance-sampling by attributes and
variables.
Note: Not to be taken for credit with ISE 320
Prerequisite: STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 325
Non Parametric Statistical Methods
(3-0-3)
One sample problem, the sign, and Wilcoxon signed rank tests. Two-Sample problem,
Wilcoxon rank sum and Mann-Whitney tests. Kruskal-Wallis test for one-way layout.
Friedman test for randomized block design. Run test for randomness. Goodness of fit tests.
Prerequisite: STAT 201 or Consent of the Instructor
STAT 342
Applied Statistics
(3-0-3)
Review for descriptive statistics, estimation, and testing hypotheses. Simple linear regression.
One way analysis of variance. Multiple regression. Randomized block designs. Factorial
experiments. Random and mixed effect models.
Note: Not to be taken for credit with STAT 310 and/or STAT 430
Prerequisite: STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 355
Demographic Methods
(3-0-3)
Scope of demography. Vital events. Demographic survey. History of world population and
distribution. Demographic transition. Fertility and its measures. Mortality and its measures.
Direct and indirect standardization. The life table. Construction of a life table. Stationary
population. Stable population. Migration. Theories of migration. Consequences of migration.
Population estimates and projections.
Prerequisite: STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 361
Operational Research I
(3-0-3)
Problem solving and decision making. Linear programming: formulation, the graphical
method, the simplex method, sensitivity analysis, and duality. Transportation and assignment
problem. Integer programming. Project scheduling PERT/CPM.
Note: Not to be taken for credit with ISE 303
Prerequisite: STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 365
Data Collection and Sampling Methods
(3-0-3)
Concept of data collection. Sample surveys, finite and infinite populations, execution and
analysis of samples. Basic sampling designs: simple, stratified, systematic, cluster, two-stage
cluster. Methods of estimation of population means, proportions, totals, sizes, variances,
standard errors, ratio, and regression.
Prerequisite: STAT 201 or consent of the Instructor
STAT 375
Categorial Data Analysis
(3-0-3)
2x2 contingency tables, two-way contingency tables, three-way and higher dimensional
contingency tables. Loglinear models for contingency tables. Logistic regression. Building
and applying loglinear models.
Prerequisite: STAT 201 or STAT 212 or STAT 213 or STAT 319
STAT 399
Summer Training
(0-0-2)
Students are required to spend one summer working in industry prior to the term in which
they expect to graduate. Students are required to submit a report and make a presentation on
their summer training experience and the knowledge gained.
Prerequisite: ENGL 214, Junior Standing, Approval of the Department
STAT 415
Stochastic Processes
(3-0-3)
Basic classes of Stochastic processes. Poisson and renewal processes with applications in
simple queuing systems. Discrete and continuous time Markov chains. Birth-Death and Yule
processes. Branching models of population growth and physical processes.
Prerequisite: STAT 301
STAT 416
Stochastic Processes for Actuaries
(3-0-3)
Basic classes of Stochastic processes. Poisson (regular, compound, compound surplus, and
non-homogenous) and renewal processes with applications in simple queuing systems and
actuarial science. Discrete and continuous time Markov chains. Birth-Death and Yule
processes. Branching models of population growth processes. Actuarial risk models;
simulation. Arithmetic and geometric Brownian motions, and applications of these processes
such as in computation of resident fees for continuing care retirement communities, and
pricing of financial instruments.
Note: Not to be taken for credit with STAT 415
Prerequisite: STAT 301
STAT 430
Experimental Design
(3-0-3)
Importance of statistical design of experiments. Single-factor and multifactor analysis of
variance. Factorial designs. Randomized blocks. Nested designs. Latin squares. Confounding
and 2-level fractional factorials. Analysis of covariance.
Prerequisite: STAT 302
STAT 435
Linear Models
(3-0-3)
Review of multiple regression. The general linear model. Quadratic forms. Gauss- Markov
theorem. Multivariate normal distribution. Computational aspects. Full rank models. Models
not of full rank. Computer applications.
Prerequisite: STAT 310
STAT 440
Multivariate Analysis
(3-0-3)
Introduction to multivariate analysis. Multivariate normal distribution theory. Distribution of
the sum of product matrix. Inference about the parameters of the multivariate normal
distribution. Comparison of means. Linear models. Principal components. Factor analysis.
Classification and discrimination techniques.
Prerequisite: STAT 310
STAT 460
Time Series
(3-0-3)
Examples of simple time series. Stationary time series and autocorrelation. Autoregressive
moving average processes. Modeling and forecasting with ARMA processes. Maximum
likelihood and least squares estimator. Nonstationary time series.
Prerequisite: STAT 310
STAT 461
Operational Research II
(3-0-3)
Inventory models. Waiting line models. Decision Analysis. Multicriteria decision problem.
Markov process. Dynamic programming. Calculus-based Procedures.
Note: Not to be taken for credit with ISE 421
Prerequisite: STAT 301, STAT 361
STAT 470
Senior Project in Statistics
(1-3-2)
This course is designed to draw upon various components of the undergraduate curriculum.
The project could be in the area of data analysis, sampling survey, experimental design,
regression analysis, multivariate data analysis, time series and etc. A report is essential for
course completion.
Prerequisite: Senior Standing
STAT 475
Statistical Models for Life time Data
(3-0-3)
Life tables, graph and related procedures. Single samples: complete or Type II censored data
and Type I censored data for Exponential, Weibull, Gamma and other distributions.
Parametric regression for Exponential, Weibull and Gamma distributions. Distributions- free
methods for proportional hazard and related regression models.
Prerequisite: STAT 302, STAT 310
STAT 499
Topics in Statistics
(3-0-3)
Variable contents. Open for senior students interested in studying an advanced topic in
statistics with a departmental faculty member.
Prerequisite:
Senior standing, Permission of the Department Chairman upon
Recommendation of the Instructor.