STAT–STATISTICS

1998-99 Catalog*Statistics Department*

STAT 130 Introduction to Statistical Reasoning (3) GEB B.2.

Survey of statistical ideas and philosophy. Emphasis on concepts rather than in-depth coverage of statistical methods. Topics include sampling, experimentation, data exploration, chance phenomena, and methods of statistical inference. Credit not allowed for students with previous Statistics course. 3 lectures. Prerequisite: Intermediate algebra, appropriate score on ELM.

STAT 200 Special Problems for Undergraduates (1–2)

Individual investigation, research, studies, or surveys of selected problems. Total credit limited to 4 units, with a maximum of 2 units per quarter. Prerequisite: Consent of department head.

STAT 211 Elementary Probability and Statistics (3) GEB B.2.

Classification of statistical data. Calculation and uses of various averages, measures of variability, elementary probability. Binomial and normal distributions. Random sampling, confidence intervals. Introduction to hypothesis testing. 3 lectures. Not open to students with credit in STAT 210. Prerequisite: Intermediate algebra, appropriate score on ELM.

STAT 212 Statistical Methods (3) GEB B.2.

Tests of hypotheses, and confidence intervals on common parameters. Linear regression and correlation, multiple regression. Analysis of variance and enumerative data. Nonparametric methods. 3 lectures. Prerequisite: One class in introductory statistics other than STAT 217/STAT 218/STAT 221.

STAT 217 Applied Statistics for the Liberal Arts (4) GEB B.2.

Sampling and experimentation, descriptive statistics, confidence intervals, two-sample hypothesis tests for means and proportions, Chi-square tests, linear and multiple regression, analysis of variance. Not open to students with credit in STAT 218 or STAT 221 or STAT 251. 4 lectures. Prerequisite: Intermediate algebra, appropriate score on ELM.

STAT 218 Applied Statistics for the Life Sciences (4) GEB B.2.

Descriptive statistics, confidence intervals, parametric and nonparametric one- and two-sample tests. Applications of statistics to the life sciences. Use of a statistical computer package. Not open to students with credit in STAT 217 or STAT 221 or STAT 251. 4 lectures. Prerequisite: Intermediate algebra, appropriate score on ELM.

STAT 221 Introduction to Probability and Statistics (5) GEB B.2.

Data classification, descriptive statistics, elementary probability. Binomial and normal distributions. Random sampling, confidence intervals and hypothesis testing on common parameters. Introduction to regression and correlation, analysis of variance, contingency table analysis. 5 lectures. Prerequisite: Intermediate algebra, appropriate score on ELM. Not open to students with credit in STAT 217 or STAT 218.

STAT 251 Statistical Inference for Management I (4) GEB B.2.

Descriptive statistics. Probability distributions. Point and interval estimation of common population parameters. Hypothesis tests of population means, proportions, and variances. Chi-square analysis. Nonparametric tests. Survey sampling. 4 lectures. Prerequisite: MATH 124.

STAT 252 Statistical Inference for Management II (4) GEB B.2.

Regression, correlation, multiple regression, time series, and forecasting. Single factor analysis of variance. Statistical quality control. Experience with statistical computer packages in analyzing data sets. Use of computers assumed throughout course. 4 lectures. Prerequisite: STAT 251 and CSC 119 or one course in computer programming.

STAT 312 Statistical Methods for Engineers (3) GEB B.2.

Survey of statistical methods. Descriptive statistics. Graphical methods. Discrete and continuous random variables. One and two sample confidence intervals and hypothesis tests. Single factor analysis of variance. Chi-square tests. Use of computer for solving statistical problems. 3 lectures. Prerequisite: MATH 142.

STAT 313 Applied Experimental Design and Regression Models (4) GEB B.2.

Analysis of variance and regression analysis for students not majoring in statistics or mathematics. Includes one-way classification, randomized blocks, Latin squares, factorial designs, multiple regression, diagnostics, and model comparison. 4 lectures. Prerequisite: STAT 212, STAT 217, STAT 218, or STAT 221.

STAT 321 Probability and Statistics for Engineers and Scientists (4) GEB B.2.

Tabular and graphical methods for data summary, numerical summary measures, probability concepts and properties, discrete and continuous probability distributions, expected values, statistics and their sampling distributions, point estimation, confidence intervals for a mean and proportion. Use of MINITAB computer package. 4 lectures. Prerequisite: MATH 142.

STAT 322 Statistical Analysis for Engineers and Scientists (4) GEB B.2.

Confidence intervals, hypothesis testing, one and two-factor analysis of variance, simple linear regression, nonlinear and multiple regression, chi-square tests, introduction to statistical quality control. 4 lectures. Prerequisite: STAT 321.

STAT 323 Design and Analysis of Experiments I (4) GEB B.2.

Principles, construction and analysis of experimental designs. Includes completely randomized, randomized complete block, Latin squares, Graeco Latin squares, factorial, and nested designs. Fixed and random effects, expected mean squares, multiple comparisons, and analysis of covariance. 4 lectures. Prerequisite: STAT 322.

STAT 324 Applied Regression Analysis (4) GEB B.2.

Simple linear regression and associated special topics, multiple linear regression, indicator variables, influence diagnostics, assumption analysis, selection of "best subset", nonstandard regression models, logistic regression, nonlinear regression models. 4 lectures. Prerequisite: STAT 252 or STAT 313 or STAT 322.

STAT 330 Statistical Uses of Computers (4)

Techniques available to the statistician for efficient use of computers to perform statistical computations and to analyze large amounts of data. Use of SAS throughout the course. Includes data preparation, report writing, and basic statistical methods. 3 lectures, 1 activity. Prerequisite: STAT 212 or STAT 313 or STAT 252 or STAT 322.

STAT 400 Special Problems for Advanced Undergraduates (1–2)

Individual investigation, research, studies or surveys of selected problems. Total credit limited to 4 units, with a maximum of 2 units per quarter. Prerequisite: Consent of department head.

STAT 412 Applied Probability Models (3)

Discrete and continuous Markov chains. Poisson processes and generalizations, birth and death processes. Applications of renewal theory. Queuing models, branching processes, Markovian decision processes. 3 lectures. Prerequisite: STAT 321 and MATH 242, or consent of instructor.

STAT 416 Statistical Analysis of Time Series (3)

Descriptive smoothing methods, regression models for time series data, forecasting via exponential smoothing, methods for seasonal data, ARIMA models and Box-Jenkins methods, frequency domain analysis, filtering. 3 lectures. Prerequisite: STAT 252 or STAT 322.

STAT 418 Analysis of Cross-Classified Data (3)

Discrete multivariate statistics, including analysis of cross-classified data, log-linear models for multidimensional contingency tables, goodness of fit statistics, measures of association, model selection, and hypothesis testing. 3 lectures. Prerequisite: Two courses in statistics and MATH 206 or consent of instructor.

STAT 419 Applied Multivariate Statistics (3)

Continuous multivariate statistics. Multivariate linear model, principal components and factor analysis, discriminant analysis, clustering, and canonical correlation. 3 lectures. Prerequisite: Two courses in statistics and MATH 206 or consent of instructor.

STAT 421 Sampling Techniques (3)

Planning, execution, and analysis of sampling from finite populations. Sampling designs and estimation procedures. Nonsampling errors. Questionnaire analysis. Case studies. 3 lectures. Prerequisite: STAT 212, STAT 252, or STAT 322.

STAT 423 Design and Analysis of Experiments II (3)

Continuation of STAT 323. 2^{k} factorial designs, 3^{k} factorial designs, balanced and partially balanced incomplete block designs, nested designs, split-lit designs, response surface methodology, confounding, repeated measures, and other design approaches. 3 lectures. Prerequisite: STAT 323.

STAT 425 Probability Theory (4)

Basic probability theory, combinatorial methods, stochastic independence, conditional and marginal probability, probability models for random phenomena, random variables, probability distributions, distributions of functions of random variables, mathematical expectation, covariance and correlation, conditional expectation. 4 lectures. Prerequisite: STAT 321, MATH 241.

STAT 426 Estimation and Sampling Theory (4)

Properties of statistics obtained from samples. Sample mean properties, convergence in probability, law of large numbers, and central limit theorem. Selected probability distributions. Theory of estimation. Sampling distribution of estimators. Introduction to hypothesis testing. 4 lectures. Prerequisite: STAT 425.

STAT 427 Mathematical Statistics (4)

The theory of hypothesis testing and its applications. Nonparametric methods. Linear statistical models including linear regression, and analysis of variance. The general linear model, full-rank models, constrained models, and tests of linear hypotheses. 4 lectures. Prerequisite: STAT 426.

STAT 430 Statistical Computing (3)

Design and use of statistical software in programming, statistical applications, efficiency and numerical accuracy of algorithms, object oriented statistical languages, random number generation, simulation, resampling, bootstrapping, linked and dynamic graphics, smoothing algorithms. 3 lectures. Prerequisite: STAT 322 and STAT 330.

STAT 461, 462 Senior Project (2) (2)

Selection and completion of a project under faculty supervision. Projects typical of problems which graduates must solve in their fields of employment. Project results are presented in a formal report. Minimum 120 hours total time.

STAT 463 Undergraduate Seminar (2) (CR/NC)

Reports and discussions by students through seminar methods, based on topics of interest to persons preparing for a career in statistics. Offered only on a Credit/No Credit basis. 2 seminars. Prerequisite: Junior standing.

STAT 470 Selected Advanced Topics (1–3)

Directed group study of selected topics for advanced students. Open to undergraduate and graduate students. *Class Schedule* will list topic selected. Total credit limited to 6 units. 1–3 lectures. Prerequisite: Consent of instructor.

STAT 485 Cooperative Education Experience (6) (CR/NC)

Part-time work experience in business, industry, government, and other areas of student career interest. Positions are paid and usually require relocation and registration in course for two consecutive quarters. Formal report and evaluation by work supervisor required. Total credit limited to 16 units. Credit/No Credit grading only. Prerequisite: Sophomore standing and consent of instructor.

STAT 495 Cooperative Education Experience (12) (CR/NC)

Full-time work experience in business, industry, government, and other areas of student career interest. Positions are paid and usually require relocation and registration in course for two consecutive quarters. Formal report and evaluation by work supervisor required. Total credit limited to 16 units. Credit/No Credit grading only. Prerequisite: Sophomore standing and consent of instructor.

STAT 512 Statistical Methods (4)

Statistical methods in research for graduate students not majoring in mathematical sciences. Probability distributions, confidence intervals, hypothesis testing, contingency tables, linear regression and correlation, multiple regression, analysis of variance. Use of computer packages. 4 seminars. Prerequisite: Graduate standing and intermediate algebra or equivalent.

STAT 513 Applied Experimental Design and Regression Models (4)

Applications of statistics for graduate students not majoring in mathematics. Analysis of variance including the one-way classification, randomized blocks, Latin squares, and factorial designs. Introduction to multiple regression and to analysis of covariance. Use of computer software in the solution of statistical problems. 4 lectures. Not open to students with credit in STAT 313. Prerequisite: STAT 512 or STAT 212 or STAT 218 or equivalent.

STAT 542 Statistical Methods for Engineers (3)

Survey of statistical methods for graduate students in engineering. Descriptive statistics. Graphical methods. Discrete and continuous random variable. One- and two-sample confidence intervals and hypothesis tests. Single factor analysis of variance. Chi-square tests. Use of computer for solving statistical problems. 3 lectures. Prerequisite: MATH 142, graduate standing.