ILRST 3080

ILRST 3080

Course information provided by the Courses of Study 2021-2022.

This course provides an introduction to probability and parametric inference. Topics include: random variables, standard distributions, the law of large numbers, the central limit theorem, likelihood-based estimation, sampling distributions and hypothesis testing, as well as an introduction to Bayesian methods. Some assignments may involve computation using the R programming language.

When Offered Fall, Spring.

Prerequisites/Corequisites Prerequisite: STSCI 2150 or STSCI 2200/BTRY 3010 or equivalent, MATH 2130 or equivalent.

Outcomes
  • Students will be able to manipulate random variables and their distributions using differential and integral calculus.
  • Students will be able to derive properties of standard probability.
  • Students will be able to derive maximum likelihood estimators for standard probability distributions and discuss their properties.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: BTRY 3080STSCI 3080

  • 4 Credits Stdnt Opt

  • 12287 ILRST 3080   LEC 001

    • MW Malott Hall 253
    • Jan 24 - May 10, 2022
    • El Alaoui, A

  • Instruction Mode: In Person

  • 12288 ILRST 3080   DIS 201

    • T Ives Hall 219
    • Jan 24 - May 10, 2022
    • El Alaoui, A

  • Instruction Mode: In Person

  • 12289 ILRST 3080   DIS 202

    • R Ives Hall 219
    • Jan 24 - May 10, 2022
    • El Alaoui, A

  • Instruction Mode: In Person