STA 120:
Statistics with Applications (4) FWSpSu
Collection and summarization of data; measures of central tendency and dispersion;
probability; binomial and normal distributions, confidence intervals and
hypothesis testing. Not open to mathematics or engineering majors. 4 lecture/problems.
Prerequisites: Minimum placement score on ELM appropriate MDT or C or better
in MAT 012 within two quarters. |
STA 200:
Special Problems for Lower Division Students (1-2)
Individual or group investigation, research, studies
or surveys of selected problems. Total credit limited to 4 units, with a
maximum of 2 units per quarter. |
STA
210: Statistical Computing (4)
Use of computer packages, inferences about means
of two populations, dependent and independent samples, small and large samples,
inferences about proportions and variances, correlation and regression.
4 lecture/problems. Prerequisite: C or better in STA 120 or consent of instructor.
|
STA
220: Discrete Probability Models (4)
Set-theoretic approach to probability in finite
sample spaces. Conditional probability, independence, binomial, hypergeometric
and related distributions. 4 lecture/problems. Prerequisite: C or better
in MAT 105, or consent of instructor. |
STA
241 (formerly STA 330): Applied Probability Theory (4) FWSpSu
Central limit theorem, maximum likelihood estimation. Point and interval
estimation and hypothesis testing. Small and large sample inferences. Contingency
table analysis and Chi- square tests. 4 lecture/problems. Prerequisite:
C or better in STA 330, STA 315, ECE 315, or consent of instructor. |
STA
309: Statistical Methods in Engineering and the Physical Sciences (3) FWSpSu
The uses of statistics in testing, inspection and production, measures of
central tendency and dispersion, probability, binomial and normal distributions,
sampling theory, hypothesis testing and estimation, comparison of two populations.
Not open to students required to take STA 315 or ECE 315. Not open to math
majors for upper division math elective credit. 3 lecture/problems. Prerequisite:
C or better in MAT 214 or MAT 131 or consent of instructor. |
STA
310: Sampling Survey Methods (4) Sp (odd years)
Simple random sampling, stratified, cluster, systematic, multistage,
multiphase and probability sampling methods, source of errors, sample size
estimation. Not open to math majors for upper division math elective credit.
4 lecture/problems. Prerequisite: C or better in STA 120 or equivalent or
consent of instructor. |
STA
326: Statistical Methods for Computer Scientists (4) FWSpSu
Rules of Probability. Discrete and continuous distributions including the
multinomial distribution. Sampling distributions. Point and interval estimation.
Hypothesis testing. Large and small sample inferences for means, proportions,
and variances. Introduction to queueing theory and regression. 4 lecture/problems.
Prerequisites: C or better in MAT 214 or consent of instructor. Not open
to students required to take STA 330. |
STA
341 (formerly STA 331): Applied Statistics (4) FWSp
Central limit theorem, maximum likelihood estimation. Point and interval
estimation and hypothesis testing. Small and large sample inferences. Contingency
table analysis and Chi- square tests. 4 lecture/problems. Prerequisite:
C or better in STA 330, STA 315, ECE 315, or consent of instructor. |
STA
400: Special Problems for Upper Division Students (1-2)
Individual or group investigation, research, studies or surveys of
selected problems. Total credit limited to 4 units, with a maximum of 2
units per quarter. |
STA
420: Nonparametric Statistics (4)
Common nonparametric tests such as permutation tests, sign tests,
Wilcoxon test, chi- square test, and rank correlation tests. Null distributions
and their approximations. 4 lecture/problems. Prerequisite: C or better
in STA 210 or STA 331, or consent of instructor. |
STA
425: Applied Survival Analysis (4)
4 lecture/problems.
Prerequisite: C or better in STA xxx or STA xxx or consent of instructor.
|
STA
430: Introduction to Random Processes (4)
General types of stochastic processes. Random walks, Poisson processes,
counting processes, Markov chains, and topics from other areas such as Markov
jump processes, Birth-death processes, Gaussian processes. 4 lecture/problems.
Prerequisite: C or better in STA 315 or STA 330 or consent of instructor.
|
STA
432: Applied Regression Analysis (4)
Matrix approach to regression models, least square estimation, correlation,
multiple regression, transformation of variables, analysis of residuals,
multicollinearity and auto- correlation. Use of computer packages for applied
problems. 4 lecture/problems. Prerequisites: C or better in STA 331 and
MAT 208 or consent of instructor. |
STA
435: Analysis of Variance and Design of Experiments (4)
ANOVA techniques, computer solutions, randomized groups and blocks designs,
interactions, analysis of covariance. Latin square, split-plot, simple and
confounded factorial designs; treatment of missing data, incomplete block
designs. 4 lecture/problems. Prerequisite: C or better in STA 331 or STA
441 or consent of instructor. |
STA
440: Mathematical Statistics I (4)
Discrete and continuous probability distributions; moments, moment generating
functions, special distributions, distributions of functions of random variables.
4 lecture/problems. Prerequisite: C or better in MAT 215, or consent of
instructor. |
STA
441: Mathematical Statistics II (4)
Asymptotic distributions; central limit theorem; point and interval estimation;
completeness and sufficient statistics; Neyman-Pearson theory of testing
hypotheses. 4 lecture/problems. Prerequisite: C or better in STA 440, or
consent of instructor. |
STA
499/499A/499L: Special Topics for Upper Division Students (1-4)
Group study of a selected topic, the title to be specified in advance. Total
credit limited to 8 units with a maximum of 4 units per quarter. Prerequisite:
consent of instructor. Lecture/Activity/Lab. |