STAT - Statistics and Probability

STAT100 Elementary Statistics and Probability (3 Credits)

Simplest tests of statistical hypotheses; applications to before-and-after and matched pair studies. Events, probability, combinations, independence. Binomial probabilities, confidence limits. Random variables, expected values, median, variance. Tests based on ranks. Law of large numbers, normal approximation. Estimates of mean and variance.

Prerequisite: MATH110, MATH112, MATH113, or MATH115; or permission of CMNS-Mathematics department; or must have math eligibility of STAT100 or higher and math eligibility is based on the Math Placement Exam or the successful completion of Math 003 with appropriate eligibility.

Restriction: Must not have completed MATH111; or must not have completed any STAT course with a prerequisite of MATH141. Cross-listed with: DATA100.

Credit Only Granted for: DATA100 or STAT100.

STAT110 Applications of R for Data Science (1 Credit)

Intended to prepare students for subsequent courses requiring computation with R, providing powerful and easy to use tools for statistical data analysis. Covers basics of R and R Studio including file handling, data simulation, graphical displays, vector and function operations, probability distributions, and inferential techniques for data analysis.

Prerequisite: DATA100, STAT100, or MATH135; or any 400-level STAT course. Cross-listed with: DATA110.

Credit Only Granted for: STAT110 or DATA110.

STAT386 Experiential Learning (3-6 Credits)

Prerequisite: Must have learning proposal approved by the CMNS-Mathematics Department.

STAT400 Applied Probability and Statistics I (3 Credits)

Random variables, standard distributions, moments, law of large numbers and central limit theorem. Sampling methods, estimation of parameters, testing of hypotheses.

Prerequisite: 1 course with a minimum grade of C- from (MATH131, MATH141); or students who have taken courses with comparable content may contact the department. Cross-listed with: DATA400.

Credit Only Granted for: DATA400, ENEE324, or STAT400.

Additional Information: Not acceptable toward graduate degrees in MATH/STAT/AMSC.

STAT401 Applied Probability and Statistics II (3 Credits)

Point estimation - unbiased and consistent estimators. Interval estimation. Minimum variance and maximum likelihood estimators. Testing of hypotheses. Regression, correlation and analysis of variance. Sampling distributions. Elements of non-parametric methods.

Prerequisite: 1 course with a minimum grade of C- from (STAT400, STAT410).

Additional Information: Not acceptable toward graduate degrees in MATH/STAT/AMSC.

STAT410 Introduction to Probability Theory (3 Credits)

Probability and its properties. Random variables and distribution functions in one and several dimensions. Moments. Characteristic functions. Limit theorems.

Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH461, MATH341); and 1 course with a minimum grade of C- from (MATH340, MATH241). Cross-listed with: SURV410.

Credit Only Granted for: STAT410 or SURV410.

STAT420 Theory and Methods of Statistics (3 Credits)

Point estimation, sufficiency, completeness, Cramer-Rao inequality, maximum likelihood. Confidence intervals for parameters of normal distribution. Hypothesis testing, most powerful tests, likelihood ratio tests. Chi-square tests, analysis of variance, regression, correlation. Nonparametric methods.

Prerequisite: 1 course with a minimum grade of C- from (SURV410, STAT410). Cross-listed with: SURV420.

Credit Only Granted for: STAT420 or SURV420.

STAT422 Probability Models (3 Credits)

Random variables, Joint Distributions, Hierarchical Models, Random Samples, Algorithms for generating samples, Markov Chains, Poisson Processes, Stochastic Processes, Simulations.

Prerequisite: STAT400 or STAT410.

Credit Only Granted for: STAT498J or STAT422.

Formerly: STAT498J.

STAT426 Introduction to Data Science and Machine Learning (3 Credits)

An introductory course to the recent developments in the fields of data science and machine learning. Emphasis will be given to mathematical and statistical understanding of commonly used methods and processes.

Prerequisite: Minimum grade of C- in MATH241 or MATH340; and minimum grade of C- in MATH240, MATH461 or MATH341; and minimum grade of C- in STAT400 or STAT410; students who have taken courses with content comparable to STAT400/410 may request permission of the instructor.

Credit Only Granted for: STAT426 or CMSC320.

STAT430 Introduction to Statistical Computing with SAS (3 Credits)

Descriptive and inferential statistics. SAS software: numerical and graphical data summaries; merging, sorting and splitting data sets. Least squares, regression, graphics and informal diagnostics, interpreting results. Categorical data, lifetime data, time series. Applications to engineering, life science, business and social science.

Prerequisite: 1 course with a minimum grade of C- from (STAT400, STAT410); and must have completed or be concurrently enrolled in STAT401 or STAT420; students who do not meet the STAT401 or STAT420 requirement but who have taken a statistics course may contact the math department to confirm eligibility.

STAT440 Sampling Theory (3 Credits)

Simple random sampling. Sampling for proportions. Estimation of sample size. Sampling with varying probabilities. Sampling: stratified, systematic, cluster, double, sequential, incomplete.

Prerequisite: 1 course with a minimum grade of C- from (STAT401, STAT420).

Credit Only Granted for: STAT440 or SURV440.

STAT464 Introduction to Biostatistics (3 Credits)

Probabilistic models. Sampling. Some applications of probability in genetics. Experimental designs. Estimation of effects of treatments. Comparative experiments. Fisher-Irwin test. Wilcoxon tests for paired comparisons.

Prerequisite: Must have completed one semester of calculus.

Restriction: Junior standing or higher.

Credit Only Granted for: BIOE372 or STAT464.

Additional Information: Not acceptable toward degrees in MATH/STAT.

STAT470 Actuarial Mathematics (3 Credits)

Major mathematical ideas involved in calculation of life insurance premiums, including compound interest and present valuation of future income streams; probability distribution and expected values derived from life tables; the interpolation of probability distributions from values estimated at one-year multiples; the 'Law of Large Numbers' describing the regular probabilistic behavior of large populations of independent individuals; and the detailed calculation of expected present values arising in insurance problems.

Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH461, MATH341); and 1 course with a minimum grade of C- from (MATH340, MATH241).

Recommended: STAT400.

STAT498 Selected Topics in Statistics (1-6 Credits)

Topics of special interest to advanced undergraduate students will be offered occasionally under the general guidance of the MATH/STAT major committee. Students register for reading in statistics under this number.

Restriction: Permission of CMNS-Mathematics department.

Repeatable to: 16 credits.