STAT 401 – Experimental Methods
Instructor of Record in Spring 2021 and Fall 2021
Random variables; probability density functions; estimation; statistical tests, t-tests; correlation; simple linear regression, and central limit theorem. Students in STAT 401 are primarily 3rd, 4th, and 5th year undergraduate students studying engineering or meteorology. Most students have never taken a statistics course before or have taken only an introductory statistics course. The textbook is Probability and Statistics with R for Engineers and Scientists by Michael Akritas. Students apply statistical and probability concepts in R in weekly lab sessions guided by the instructor and teaching assistant.
Sample course materials:
- Syllabus
- Example lecture slides: Conditional Probability and Independent Events
- Example lab: Lab 1 (preceded by a lab 0)
STAT 318 (MATH 318) – Elementary Probability
Instructor of Record in Fall 2019, Spring 2020, and Fall 2020
Combinatorial analysis, axioms of probability, conditional probability and independence, discrete and continuous random variables, expectation, and limit theorems. Students are mostly 2nd, 3rd, and 4th year undergraduate students studying computer science or applied data science. Most have not taken a statistics class before or have taken introductory statistics. The textbook is Probability and Statistical Inference by Robert Hogg, Elliot Tanis, and Dale Zimmerman.
Sample course materials:
- Syllabus
- Example lecture slides: Continuous Random Variables
STAT 200 – Elementary Statistics
Instructor of Record in Summer 2020 and Summer 2021; Lab Instructor in Fall 2018.
Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation. STAT 200 is a standard first course in statistics. Student who have successfully completed this course will understand basic concepts of probability and statistical inference, including common graphical and numerical data summaries; notions of sampling from a population of interest, including the sampling distribution of a statistic; construction and interpretation of confidence intervals, test statistics, and p-values; and connections between probabilistic concepts like the normal distribution and statistical inference. They will recognize various types of data, appropriate statistical methods to analyze them, and assumptions that underlie these methods, They will also gain extensive experience in the use of Minitab Express statistical software to analyze data and interpret the output of this software.
Sample course materials:
STAT 466 – Survey Sampling
Introduction to design and analysis of sample surveys, including questionnaire design, data collection, sampling methods, and ratio and regression estimation. STAT 466 Survey Sampling (3)This course covers classical sampling design and analysis methods useful for research and management in many fields. Topics include design of questionnaires; methods of data collection, sample-survey designs including simple random sampling, stratified sampling, cluster sampling, and systematic sampling ratio, regression, and difference estimation; two-stage cluster sampling; population size estimation; methods for dealing with nonresponse; and possibly other topics at the discretion of the instructor. Statistical software will be used to apply many of the techniques covered by this course.