# STAT - Statistics

## STAT 150 Statistical Ideas

Introduction to the field of statistics, including sampling, experiments, measurement, descriptive statistics, probability, inference, correlation, regression and prediction. The emphasis will be on data and concepts rather than on calculations and mathematical theory. Not open to students who have completed a 200-level statistics course with a grade of C- or better. Background assumed: N.Y.S. Algebra II and Trigonometry (or Math B), or equivalent.

3

## STAT 200 Statistical Methods I

An introductory study of statistical methods with applications to business, economics, education, and the social sciences. Topics covered include: descriptive statistics and graphs, probability and probability distributions, estimation, confidence intervals, hypothesis testing and linear regression. The course focuses on when to use each of the different methods. Note: Credit for at most one of the following courses may be applied towards a student's requirements for graduation: BUAD 200, ECON 200, EDU 200, POLI 200, SOC 200, and STAT 200. Background assumed: N.Y.S. Algebra II and Trigonometry (or Math B), or equivalent.

3

## STAT 250 Statistics for Scientists

Introduction to statistical methods with special emphasis on uses in the natural sciences. Topics will include descriptive statistics, data collection, probability distributions, confidence intervals, hypothesis testing, regression, and analysis of variance. The course will include use of analytical labs and statistical computer packages. Background assumed: N.Y.S. Algebra II and Trigonometry (or Math B), or equivalent.

3

## STAT 260 Introduction to Data Science

An introduction to the art and science of transforming data into information. Working with data using R and RStudio; data collection, wrangling, modelling, and visualization; data "storytelling." Background assumed: N.Y.S. Algebra II or equivalent.

3

## 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 – 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

## STAT 400 Independent Study

Independent study of a selected list of readings approved by the faculty advisor. Departmental approval required.

1-3

## STAT 405 Statistics Seminar

This is a capstone course for the statistics minor. Students will complete a major statistics project. It will include designing an experiment, collecting the data, analyzing the data, and giving oral and written reports explaining the analysis and conclusions. Departmental permission is required.

1

## STAT 407 Special Topics

Selected readings, discussions, data analysis on a topic in statistics. Permission of department required.

1-2

## STAT 408 Special Topics

Selected readings, discussions, data analysis on a topic in statistics. Permission of department required.

3

### Prerequisites

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

## STAT 451 Time Series

Study of linear time series, moving averages and auto regressive models. Estimation, confidence intervals, forecasting and data analysis with time series models will be examined.

1

STAT 351

## STAT 460 Risk Management for Actuarial Science

Development of fundamental mathematical tools and language of quantitative risk management. Multivariate probability distributions including joint, conditional and marginal distributions, probabilities, moments, variance and covariance.

2

### Prerequisites

MATH 223 and STAT 350

STAT 355