Statistics and Probability (STP)

STP 420 Introductory Applied Statistics. (3) F, S, SS
Introductory probability, descriptive statistics, sampling distributions, parameter estimation, tests of hypotheses, chi-square tests, regression analysis, analysis of variance, and nonparametric tests. Prerequisite: MAT 117 or equivalent. General Studies: N2.

STP 421 Probability. (3) F
Laws of probability, combinatorial analysis, random variables, probability distributions, expectations, moment generating functions, transformations of random variables, and central limit theorem. Prerequisites: MAT 300 and STP 420 or equivalents.

STP 425 Stochastic Processes. (3) S
Markov chains, stationary distributions, pure jump processes, 2d order processes, and other topics in stochastic processes. Prerequisites: MAT 342; STP 421.

STP 427 Mathematical Statistics. (3) S
Limiting distributions, interval estimation, point estimation, sufficient statistics, and tests of hypotheses. Prerequisite: STP 421.

STP 429 Experimental Statistics. (3) S
Statistical inference for controlled experimentation. Multiple regression, correlation, analysis of variance, multiple comparisons, and nonparametric procedures. Prerequisite: STP 420 or equivalent. General Studies: N3.

STP 525 Advanced Probability. (3) N
Measure-theoretic foundations of probability, distribution functions and characteristic functions, laws of large numbers and central limit theorems, conditional probabilities, martingales, and topics in stochastic processes. Prerequisites: MAT 571 and STP 421 or instructor approval.

STP 526 Theory of Statistical Linear Models. (3) F
Multinormal distribution, distribution of quadratic forms, full and nonfull rank models, generalized inverses, unbalanced data, variance components, and the large sample theory. Prerequisites: STP 427; knowledge of matrix algebra.

STP 527 Theory of Statistical Linear Models. (3) S
Continuation of STP 526. Prerequisite: STP 526 or instructor approval.

STP 530 Applied Regression Analysis. (3) F
Method of least squares, simple and multiple linear regression, polynomial regression, analysis of residuals, dummy variables, and model building. Prerequisite: STP 420 or equivalent.

STP 531 Applied Analysis of Variance. (3) S
Factorial designs, balanced and unbalanced data, fixed and random effects, randomized blocks, Latin squares, analysis of covariance, and multiple comparisons. Prerequisite: STP 420 or equivalent.

STP 532 Applied Nonparametric Statistics. (3) F
One sample test, tests of 2 or more related or independent samples, measures of correlation, and tests of trend and dependence. Prerequisite: STP 420 or equivalent.

STP 533 Applied Multivariate Analysis. (3) S
Discriminant analysis, principal components, factor analysis, cluster analysis, and canonical correlation. Prerequisite: STP 420 or equivalent.

STP 534 Applied Discrete Data Analysis. (3) N
Models for discrete and count data, measures of association, and log-linear and regression models for contingency tables. Prerequisite: STP 420 or equivalent.

STP 591 Seminar. (1–3) N
Topics may be selected from the following:
(a) Probability
(b) Statistics

Omnibus Graduate Courses: See omnibus graduate courses that may be offered.

1996–98 Graduate Catalog Table of Contents

Page Last Updated:
ASU Disclaimer

Visits to this page: page counter