# 300

## STAT 300 Statistical Methods II

Continuation of STAT 200. Review of the basics of estimation, confidence intervals and hypothesis testing. Simple and multiple regression, time series, analysis of variance and non-parametric methods. A statistical software package will be used extensively.

3

### Prerequisites

STAT 200 or BUAD 200 or ECON 200 or EDU 200 or POLI 200 or PSY 200 or SOC 200 or STAT 250 or STAT 350

## STAT 350 Probability and Statistics

Basics of probability; descriptive statistics; discrete and continuous distributions; confidence intervals and tests of hypotheses concerning means and proportions; simple linear regression; statistical software. MATH 210 is recommended, in addition to the prerequisites listed.

3

### Prerequisites

MATH 121 or MATH 123

## STAT 351 Regression and Analysis of Variance

Simple linear regression and multiple regression including inference, diagnostics and transformations. One-way and multi-way analysis of variance including inference, diagnostics and transformations. Use of professional statistical software.

3

### Prerequisites

(STAT 350 or STAT 250 or STAT 200 or BUAD 200 or ECON 200 or SOC 200 or POLI 200 or PSY 200)

## STAT 352 Categorical Data Analysis

Techniques for analyzing categorical response data â€" confidence intervals, tests of significance for a proportion, the difference of two proportions, contingency tables, regression, odds, odds ratios, logistic regression, logit models, loglinear models and diagnostics.

3

### Prerequisites

(STAT 350 or STAT 250 or STAT 200 or BUAD 200 or ECON 200 or SOC 200 or POLI 200 or PSY 200)

## STAT 354 Probability with Applications

A first course in probability with selected applications. Definition of probability and basic axioms; calculation of probabilities; mutually exclusive and independent events; conditional probability and Bayes Theorem; discrete random variables and distributions; continuous random variables and distributions; calculation of expected value, mode, median, percentiles, variance, standard deviation, and coefficient of variation; functions of random variables and transformations. Applications selected from Markov chains, random walks, queueing theory, and inventory theory

3

### Prerequisites

MATH 121 or MATH 123

## STAT 355 Mathematical Statistics

Multivariate distributions, functions of random variables, sampling distributions and central limit theory, theory of estimation, the method of moment and maximum likelihood, and hypothesis testing.

3

### Prerequisites

MATH 223 and STAT 354

## STAT 360 Topics in Data Science

A continuation of STAT 260: statistical foundations of data science; bootstrap methods; supervised learning; unsupervised learning; simulation; interactive data graphics; working with spatial data and text; working with large data sets.

3

STAT 260