Stat 100 Calculus and Matrix Algebra for Statistics. Differential and integral calculus. Infinite series. Matrix algebra. 3 u.
Stat 101 Elementary Statistics. Presentation of data; frequency distributions; measures of central tendency; measures of dispersion; index numbers; probability distributions; statistical inference; correlation and regression. Prereq: Math 11. 3 u.
Stat 102 Intermediaite Statistical Methods for Research. Intermediate concepts and statistical techniques for quantitative research and designed experiments.
Stat 114 Descriptive Statistics. Statistics; statistical measurement; statistical notations; collection, organization and presentation of data; measures of central tendency, location, dispersion, skewness, kurtosis; letter values, boxplots and stem-andleaf display; measures of association and relationship; rates, ratios, and proportions; construction of index numbers and indicators. Coreq: Math 17/equiv. 3 u.
Stat 115 Basic Statistical Methods. Computer assisted statistical analysis on the following: tests for means; tests for proportions; tests for independence; simple linear regression; analysis of variance; forecasting using classical techniques. Prereq: Stat 101/114/equiv. 3 u.
Stat 117 Mathematics for Statistics. Principles of logic; methods of proof; fields, sigma fields and sequences of sets; the real number system; sequences and series; combinatorial analysis. Prereq: Math 17/equiv. 3 u.
Stat 121 Probability Theory I. Elements of probability; random variables; discrete and continuous random variables; probability distributions; special distributions; mathematical expectations; functions of a randon variable. Prereq: Math 53, Stat 117/equiv; Coreq: Math 54. 3 u.
Stat 122 Probability Theory II. Joint, marginal, and conditional distributions; independence of random variables; distributions and expectations of functions of random variables; charactertization of F, t, and χ2 distributions, normal approximation to discrete distributions. Prereq: Stat 121. 3 u.
Stat 124 Introduction to Programming. Introduction to microcomputer and operating systems; principles of programming; programming using a high-level computer language (e.g., PASCAL). Prereq: Stat 101/114/equiv. 3 u.
Stat 125 Applications Software and Software Packages. Use of statistical software packages (e.g., SAS, SPSS) for database management and basic statistical analysis. Prereq: Stat 101/115/equiv, Stat 124/equiv. 3 u.
Stat 130 Introduction to Mathematical Statistics for Computer Science. Probability; random variables and distribution functions; special distributions; sampling distributions; maximum likelihood estimation; interval estimation; hypothesis testing; application of the central limit theorem to large sample inference; linear regression and correlation. Prereq: Math 55. 3 u.
Stat 131 Parametric Statistical Inference. Population and sample; statistics and sampling distributions; limit theorems; point and interval estimation; statistical hypothesis testing; inference based on the normal distribution and applications of z, t, χ2, and F distributions. Prereq: Math 55, Stat 122. 4 h. (3 lec, 1 lab). 4 u.
Stat 132 Nonparametric Statistical Inference. Levels of measurement; goodness-of-fit tests; sign and signed rank tests; distribution tests; association tests; tests for independence. Prereq: Stat 131, Stat 125. 3 u.
Stat 133 Bayesian Statistical Inference. Elements of Bayesian inference; assessment of prior likelihood and posterior distributions; Bayesian estimation and hypothesis testing; predictive distribution and asymptotics; Bayesian Hierarchical Models; introduction to Empirical Bayes; use of statistical software. Prereq: Stat 131, Stat 124. 3 u.
Stat 134 Introduction to Scientific Writing in Statistics. Principles and methods in scientific writing in statistical studies.
Stat 135 Matrix Theory for Statistics. Matrix operations; properties of matrices; special matrices; matrix calculus; determinants; eigenvalues and eigenvectors; linear systems; vector spaces; use of software; applications. Prereq: Math 53, Stat 125. 3 u.
Stat 136 Introduction to Regression Analysis. Linear regression model; model selection; regression diagnostics; use of dummy variables; remedial measures. Prereq: Stat 131, Stat 135.
Stat 138 Introduction to Sampling Designs. Probability and non-probability sampling techniques; complex surveys; variance estimation; treatment of missing data; applications to various contexts. Prereq: Stat 131, Stat 125. 3 u.
Stat 142 Introduction to Computational Statistics. Contemporary themes in computational statistics; survey of computationally-intensive methods in statistics; advanced data management; SQL programming; resampling methods; simulations; macro programming; modeling applications.
Stat 143 Survey Operations. Research process; techniques of data collection; principles of questionnaire design; data coding and encoding; data quality control; presentation of research findings. Prereq: SSa , Technical Writing course, Oral Communication Skills course. 3 u.
Stat 145 Introduction to Time Series Analysis and Forecasting. Classical methods; ARIMA models; Box-Jenkins method; unit root processes; intervention analysis; GARCH Models; regression with time series data; applications. Prereq: Stat 136. 3 u.
Stat 146 Introduction to Exploratory Data Analysis. Displaying and summarizing batches; re-expressing data; median polish; a A student has SS if s/he requires at most 18 major units to graduate robust and resistant measures; fitting resistant lines. Coreq: Stat 136. 3 u.
Stat 147 Introduction to Multivariate Analysis. Multivariate normal distribution; inference on mean vector and dispersion matrices; principal component analysis; factor analysis; cluster analysis; discriminant analysis; canonical correlation analysis; correspondence analysis and perceptual mapping; multivariate analysis of variance (MANOVA); applications. Prereq: Stat 136. 3 u.
Stat 148 Introduction to Experimental Designs. Principles of experimentation; completely randomized design; randomized complete block design; Latin-square design; factorial experiments; confounding; incomplete blocks design; cross-over design; analysis of covariance; nested and split-plot designs; random effects; response surface methodology (RSM); applications. Prereq: Stat 136. 3 u.
Stat 149 Introduction to Categorical Data Analysis. Categorical data; cross-classification tables; analysis using loglinear, logistic and logit models. Prereq: Stat 136. 3 u.
Stat 191 Special Topics in Biological and Medical Statistics. Prereq: COI. 3 u.
Stat 191.1 Introduction to Biostatistics. Descriptive and inferential statistics in the health sciences: clinical trials, epidemiologic studies: survival analysis. Prereq: Stat 125. Coreq: Stat 148. 3 u.
Stat 192 Special Topics in Business and Economic Statistics. Prereq: COI. 3 u.
Stat 192.1 Statistics in Market Research. Market research process; primary data collection; research design concepts; descriptive, inferential, and multivariate statistics in market research; communicating market research results; applications. Coreq: Stat 147. 3 u.
Stat 192.2 Advanced Linear Models. Instrumental variables: limited dependent variable models; panel data estimation. Prereq: Stat 136. 3 u.
Stat 193 Special Topics in Industrial and Physical Science Statistics. Prereq: COI. 3 u. 193.1 Introduction to Statistical Quality Control. Overview of quality control and improvement; identifying sources of variation; control charts; process capability analysis; acceptance sampling; reliability. Prereq: Stat 125, Stat 131. 3 u.
Stat 194 Special Topics in Social and Psychological Statistics. Prereq: COI. 3 u.
Stat 195 Introduction to Mathematical Statistics. Probability distributions, sampling distributions, parametric and nonparametric inference. 3 u.
Stat 196.1 Advanced Statistical Computing. Advanced data management and processing; Structured Query Language; modular codes; simulations; resampling methods. Prereq: Stat 136. 3 u. School of Statistics 555
Stat 197 Special Topics in Statistics. Prereq: COI. 3 u., may be taken thrice, topics to be indicated for record purposes.