UNDERGRADUATE COURSES IN STATISTICS

STAT 201 – ELEMENTARY STATISTICAL INFERENCE [Fall, Spring]
STAT 211
– PRINCIPLES OF STATISTICS I [Fall, Spring, Summer]
STAT 212
– PRINCIPLES OF STATISTICS II [Fall, Spring]
STAT 301
– INTRODUCTION TO BIOMETRY [Fall, Spring]
STAT 302
– STATISTICAL METHODS [Fall, Spring, Summer]
STAT 303
– STATISTICAL METHODS [Fall, Spring, Summer]
STAT 307
– SAMPLE SURVEY TECHNIQUES [Spring]
STAT 407
– PRINCIPLES OF SAMPLE SURVEYS [Fall]
STAT 408
– INTRODUCTION TO LINEAR MODELS [Spring]
STAT 414
– MATHEMATICAL STATISTICS I [Fall]
STAT 485
– DIRECTED STUDIES [Fall, Spring, Summer]

201. Elementary Statistical Inference. (3-0). Credit 3. Data collection, tabulation, and presentation. Elementary description of the tools of statistical inference; probability, sampling, and hypothesis testing. Applications of statistical techniques to practical problems. May not be taken for credit after or concurrently any other course in statistics or INFO 303 has been taken.

211. Principles of Statistics I. (3-0).  Credit 3.  Introduction to probability and probability distributions. Sampling and descriptive measures. Inference and hypothesis testing. Linear regression, analysis of variance. Prerequisite: MATH 152 or 172.

212. Principles of Statistics II. (3-0). Credit 3.  Design of experiments, model building, multiple regression, nonparametric techniques, contingency tables, and short introductions to response surfaces, decision theory and time series data. Prerequisite: STAT 211.

301. Introduction to Biometry. (3-0). Credit 3.  Intended for students in animal sciences. Introduces fundamental concepts of biometry including measures of location and variation, probability, tests of significance, regression, correlation, and analysis of variance which are used in advanced courses and are being widely applied to animal-oriented industry. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.

302. Statistical Methods. (3-0). Credit 3.  Intended for undergraduate students in the biological sciences and agriculture (except agricultural economics). Introduction to concepts of random sampling and statistical inference; estimation and testing hypotheses of means and variances; analysis of variance; regression analysis; contingency tables. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.

303. Statistical Methods. (3-0). Credit 3. Intended for undergraduate students in the social sciences. Introduction to concepts of random sampling and statistical inference, estimation and testing hypotheses of means and variances, analysis of variance, regression analysis, contingency tables. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.

307. Sample Survey Techniques. (3-0). Credit 3. Concepts of population and sample; the organization of a sample survey; questionnaire design. Basic survey designs and computation of

estimates and variances. Prerequisites: STAT 301, 302, 303, or INFO 303.

407. Principles of Sample Surveys. (3-0). Credit 3.  Principles of sample surveys and survey design; techniques for variance reduction; simple, stratified and multi-stage sampling; ratio and regression estimates; post-stratification; equal and unequal probability sample. Prerequisite: STAT 212.

408. Introduction to Linear Models. (3-0). Credit 3. Introduction to the formulation of linear models and the estimation of the parameters of such models, with primary emphasis on least squares. Application to multiple regression and curve fitting. Prerequisites: MATH 304; STAT 212.

414. Mathematical Statistics. (3-0). Credit 3.  Introduction to the mathematical theory of statistics, including random variables and their distributions, expectation and variance, point estimation, confidence intervals and hypothesis testing. Prerequisite: MATH 221, 251 or 253.

485. Problems. Credit 1 to 6. Special problems in statistics not covered by another course in the curriculum. Work may be in either theory or methodology. Prerequisite: Approval of instructor.