Undergraduate Courses

The department offers a statistics major and a joint statistics/mathematics major in cooperation with the mathematics department. The joint statistics/mathematics major provides a stronger preparation for graduate study in statistics. Students who are most interested in applying statistics in industry, government, or in applied areas of graduate study should take the statistics major. The department encourages interdisciplinary study, and students should consult with departmental advisers to plan their program.

Major Requirements

Statistics

A total of 46 credits is required: 18 credits in mathematics, 25 credits in statistics, and 3 credits in computer science, as follows:
(No courses with grade D can be counted toward the major.)

1. Computer Science 01:198:110 or 111

2. Mathematics 01:640:151-152; 250; 251, and additional three credits in mathematics electives

(252 or a course at the 300 level or above, but not 477 or 481)

3. Statistics 01:960:381*; 382*; 384*; 390*; 463; 486; 490

4. Two courses chosen from 01:960:467; 476; 483;

Statistics/Mathematics

A total of 56 credits is required: 28 credits in mathematics, 25 credits in statistics, and 3 credits in computer science, as follows:
(No courses with grade D can be counted toward the major.)

1. Computer Science 01:198:110 or 111

2. Mathematics 01:640:151;152; 250; 251; 252; 311; 478 and additional three credits in mathematics electives (300 level or above, but not 477 or 481)

3. Statistics 01:960:381*; 382*; 384*; 390*; 463; 486; 490

4. Two courses chosen from 01:960:467; 476; 483

* Mathematics 01:640:477 and 481 may be taken instead of Statistics 01:960:381, 382. Credit will not be given for both 01:640:477 and 01:960:381, nor for both 01:640:481 and 01:960:382.

Sequence of Courses for Nonmajors

The sequence of courses in the study of statistics is related to a student's primary field of specialization. Students seeking credit for courses other than those for which their class and major qualify them must have the prior approval of the statistics undergraduate director and the dean of instruction, Faculty of Arts and Sciences.

Field of Interest Introductory Courses Subsequent Courses
Political Science, Psychology, Sociology and Humanities 211*, 212 390, 463, 467, 476, 486, 490
Mathematics 381, 382 390, 384, 463, 467, 476, 486, 490
Physics, Engineering, Chemistry, CompSci 379, 384 463, 476, 483, 486, 490
Biology, Agriculture, Pharmacy 401*, 490 390, 463, 467, 476, 486
Business 285* 463, 476, 486, 490
Environmental Science 211*, 212 463, 467, 486, 490
Economics 201* or 211*, 212 463, 467, 486, 490

*Credit will not be given for more than one of 201, 211, 285, 401. Note also that the recommended follow-up course for 960:211 is 960:212, or 384.

Minor Requirements

A minor in statistics consists of 960:390 and six additional courses in the Department of Statistics of which at least one must be at the 400 level. Neither 01:960:401 nor 01:960:484 may be used to fulfill this 400-level requirement.

Level II Statistics

The Level II Statistics prerequisites for some courses may be fulfilled by 960:212 or 960:384 or 960:401 or 960:484 or the equivalent. Credit will not be given for more than one Level II Statistics course.

Courses

01:960:201. Basic Statistics for Economics (4)
Prerequisite: 01:640:115 or permission of department. Credit not given for more than one of the following: 01:960:201, 211, 321 and 01:220:201.
Introduction to statistical inference, including descriptive statistics, probability, sampling, estimation, hypothesis testing, and simple regression analysis. Instruction in the use of computer packages.

01:960:211-212. Statistics I, II (3,3)
Prerequisite: 01:640:115 or permission of department. See Level II Statistics restrictions. Credit not given for more than one of 01:960:201, 211, 285, and 401; nor for more than one of 01:960:212, 380, 384, 401, and 484.
Principles and methods of statistics, including probability distributions, sampling, estimation, hypothesis testing, regression and correlation analysis, curve-fitting, nonparametric methods, and analysis of variance (ANOVA)

01:960:285. Introductory Statistics for Business (3)
Prerequisites: 01:640:115 or equivalent. Credit not given for more than one of 01:960:201, 211, 285, and 401.
Topics include descriptive statistics, probability theory, random variables, sampling distributions, estimation, hypothesis testing, and one- and two-sample t-tests.

01:960:337. Managerial Statistics (3)
Prerequisite: 01:960:211 or 321, or equivalent.
Modern data analysis and applied statistical decision theory in such fields as market research, business forecasting, and operations research. Analysis of time series and index numbers.

01:960:379. Basic Probability Theory (3)
Prerequisite: One term of calculus.
Descriptive statistics; elementary probability theory; probability distributions; the binomial, Poisson, exponential and normal distributions; basic sampling theory; applications of probability theory.

01:960:381Theory of Probability (3)
Prerequisite: O1:640:251. Credit not given for both 01:960:381 and 01:640:477.
Probability distributions; the binomial, geometric, exponential, Poisson, and normal distributions; moment generating functions; sampling distributions; applications of probability theory.

01:960:382Theory of Statistics (3)
Prerequisite: 01:960:381 or equivalent. Credit not given for both 01:960:382 and 01:640:481.
Statistical inference methods, point and interval estimation, maximum likelihood estimates, information inequality, hypothesis testing, Neyman-Pearson lemma, linear models.

01:960:384 Intermediate Statistical Analysis (3) (Formerly 960:380)
Prerequisite: one of the following courses: 960:201, 211, 285, 379, 381 or permission of department. Credit not given for more than one of 01:960:212, 384, 401 or 484.
Application of statistical techniques to the analysis of data; tests of significance, correlation and regression analysis, confidence intervals, analysis of variance and some design of experiments, analysis of cross-classified data, chi-square tests. The course requires the use of basic statistics computer package SAS.

*960:384 is numbered 960:380 previously. Credit is not given for both 960:380 and 384.

01:960:385. Statistics for Social Work (E2)
Registration limited to students in the Graduate School of Social Work. Graded as satisfactory or unsatisfactory.
Descriptive statistics; methods of classifying and summarizing data; estimation and prediction; correlation and regression analysis; principles of hypothesis testing.

01:960:390. Introductory Computing for Statistics (1)
Five-week course; 3 hrs. lecture and lab.
Prerequisite: Level II Statistics.
Introduction to the use of statistics computer packages with main focus on SAS. Includes: generating random samples, estimation, testing hypotheses. ANOVA

01:960:391,392. Honors Seminars in Probability/Statistics (3,3)
Prerequisite: Caclulus I, or permission of the department.
Co-requisite: Calculus II.
Lectures and discussions of real life examples or case studies on statistics and probability theory, and their ramifications. Topics may vary term by term. Extensive data analysis required.

01:960:401. Basic Statistics for Research (3)
Prerequisite: 01:640:115 or equivalent. Credit not given for more than one of 01:960:201, 211, 285, and 401; nor for more than one of 01:960:212, 384, 401, and 484.
As applied in fields other than statistics; treats research projects dependent on the use of observed data from planned experiments. Includes inference methods in estimation and hypothesis testing, and general linear models.

01:960:463. Regression Methods (3)
Prerequisite: Level II Statistics.
Multiple and nonlinear correlation and regression techniques for analysis of events in time and space: analysis of variance and covariance (ANOVA), related multivariate techniques, response surface approaches.

01:960:467. Applied Multivariate Analysis (3)
Prerequisite: Level II Statistics or permission of department.
Introduction to the methodology of multivariate analysis. Multiple linear regression, discriminant analysis, profile analysis, canonical correlation, principal components, and factor analysis.

01:960:476. Introduction to Sampling (3)
Prerequisite: 01:960:379 or 381 or equivalent or permission of department.
Principles of sampling application for economic procurement or assessment of data. Current techniques for area sampling, sampling of accounts, large-scale surveys, stratification, cluster sampling, systematic sampling, two-stage sampling, and construction estimates.

01:960:483. Statistical Quality Control (3)
Prerequisite: Level II Statistics.
Statistical measures; histogram analysis; construction and analysis of control charts for variables and attributes; analysis of capability indices; acceptauce sampling plans; statistical aspects of tolerance; analysis of means.

01:960:484. Basic Applied Statistics (3)
Prerequisite: One of the following coures: 960:201, 211, 285, 379, 381, 401 or an equivalent course in basic probability theory. See credit restrictions for Level II Statistics.
Estimation, hypothesis testing, chi-square methods, correlation and regression analysis, basis of design of experiments.

01:960:486. Computing and Graphics in Applied Statistics (3)
Prerequisite: Level II Statistics.
Use of various computer-based techniques, including graphical, to understand and interpret data. Exposure to basic analysis of categorical, time-series and multivariate data in the applied areas such as biostatistics, quality control and others.

01:960:490. Introduction to Experimental Design (3)
Prerequisite: Level II Statistics.
Principles of designs. Nature and analysis of various designs; randomized blocks, Latin squares, factorial designs. Applications to specific problems.

01:960:491. Reliability-Quality Control (3)
Prerequisites: 01:640:251 and Level II Statistics.
A survey of current theory and practice in this field.

01:960:495. Independent Studies in Statistics (3)
Prerequisite: Permission of department.