STAT 3850 - Foundation of Statistics -- Spring 2025

Instructor Info

  • Name: Vahan Huroyan
  • Webpage: http://vahan.huroyan.com
  • Office: Ritter 113
  • Office Hours: Tuesday & Wednesday 3:00–4:00pm or by appointment

Course Info

  • Course Syllabus: [here]
  • Location: Ritter Hall 334
  • Lecture Time: Tuesday & Thursday 12:45–2:00pm
  • Textbook: Probability, Statistics, and Data: A Fresh Approach Using R by Speegle and Clair

Important Dates

  • Midterm 1: February 27
  • Midterm 2: April 10
  • Final Exam: May 8

Lecture Schedule

  • Lecture 1, Jan 14: Probability basics (Section 2.1)
  • Lecture 2, Jan 16: R basics (Chapter 1)
  • Lecture 3, Jan 21: Simulations (Section 2.2)
  • Lecture 4, Jan 23: Conditional Probability, Independence (Section 2.3)
  • Lecture 5, Jan 28: Counting arguments (Section 2.4)
  • Lecture 6, Jan 30: Discrete Random Variables, Probability mass function (Section 3.1)
  • Lecture 7, Feb 4: Expected Value, Binomial Random Variable (Sections 3.2, 3.3)
  • Lecture 8, Feb 6: Binomial and Geometric random variables (Section 3.3)
  • Lecture 9, Feb 11: Functions of random variables, Variance, Standard Deviation (Sections 3.4, 3.5)
  • Lecture 10, Feb 13: Independent Random Variables, Poisson (Sections 3.5, 3.6)
  • Lecture 11, Feb 18: Continuous random variables, PDF (Section 4.1)
  • Lecture 12, Feb 20: Expected value, Variance, Standard deviation (Sections 4.2, 4.3)
  • Lecture 13, Feb 25: Review
  • Lecture 14, Feb 27: Midterm 1
  • Lecture 15, Mar 4: Normal Random Variable (Section 4.4)
  • Lecture 16, Mar 6: Uniform, Exponential Random Variable (Section 4.5)
  • Lecture 17, Mar 18: Estimating Probabilities, Discrete Distributions (Sections 5.1, 5.2)
  • Lecture 18, Mar 20: Estimating Continuous Distributions, CLT (Sections 5.3, 5.4)
  • Lecture 19, Mar 25: Sampling Distributions, Chi-squared, t-distribution (Section 5.5)
  • Lecture 20, Mar 27: Data Frames, dplyr verbs (Sections 6.1, 6.2)
  • Lecture 21, Apr 1: dplyr pipelines (Sections 6.3, 6.4)
  • Lecture 22, Apr 3: Character strings, Structure of data (Sections 6.5, 6.6)
  • Lecture 23, Apr 8: Review, ggplot fundamentals (Section 7.1)
  • Lecture 24, Apr 10: Midterm 2
  • Lecture 25, Apr 15: Visualizing single variable (Section 7.2)
  • Lecture 26, Apr 22: Confidence intervals for the mean (Section 8.2)
  • Lecture 27, Apr 24: Hypothesis tests of the mean (Section 8.3)
  • Lecture 28, Apr 29: One-sided CI, Two-sample tests (Sections 8.4, 8.6)
  • Lecture 29, May 1: Simulation, Type II errors, power (Sections 8.5, 8.7)