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MATH 205 (Fall 2022): Statistical methods

• General information:
  • Instructor: Vu Dinh
  • Lectures: MWF 3:35pm-4:25pm, Gore Hall Room 304.
  • Labs:
    • Section 050L: Mon 2:30pm - 3:20pm, Gore Hall Room 222
    • Section 051L: Wed 2:30pm - 3:20pm, Gore Hall Room 222
  • Office hours: Tuesday 3:00pm - 4:30pm, Friday 1:30pm - 3:00pm, or by appointments.

• Syllabus
  • There will be an in-class midterm exam during the week of October 24-28. The exam consists of two parts: a written exam during the Oct 28 lecture, and the computational exam during the lab sessions of that week.
  • Detailed syllabus

• Topics and reference
  • Lectures: Probability and Statistics for Computer Science. David Forsyth (2018).
    The text is available online from the UD library.
  
  
  • Labs: simpleR – Using R for Introductory Statistics. John Verzani (2002).
    Link
  
  
  • Topics: The aim is to cover Chapters 1-9 of the text.
    Topics include descriptive statistics, graphical displays, sampling, variation, normal distribution, estimation, hypothesis testing, one-way analysis of variance, simple linear regression and goodness of fit.

• Lectures
  • Lecture 1 (Wed, 08/31)
    
  • Lecture 2 (Fri, 09/02).
    
  • Lecture 3 (Wed, 09/07).
    
  • Lecture 4 (Fri, 09/09).
    
  • Lecture 5 (Mon, 09/12).
    
  • Lecture 6 (Wed, 09/14).
    
  • Lecture 7 (Fri, 09/16).
    
  • Lecture 8 (Mon, 09/19).
    
  • Lecture 9 (Wed, 09/21).
    
  • Lecture 10 (Fri, 09/23).
    
  • Lecture 11 (Mon, 09/26).
    
  • Lecture 12 (Wed, 09/28).
    
  • Lecture 13 (Fri, 09/30).
    
  • Lecture 14 (Mon, 10/03).
    
  • Lecture 15 (Wed, 10/05).
    
  • Lecture 16 (Fri, 10/07).
    
  • Lecture 17 (Mon, 10/10).
    
  • Lecture 18 (Wed, 10/12).
    
  • Lecture 19 (Fri, 10/14).
    
  • Lecture 20 (Mon, 10/17).
    
  • Lecture 21 (Wed, 10/19).
    
  • Lecture 22 (Fri, 10/21).
    
  • Lecture 23 (Mon, 10/24).
    
  • Practice midterm (Wed, 10/26).
    Solution to Problem 3
    
  • Lecture 24 (Mon, 10/31).
    
  • Lecture 25 (Wed, 11/02).
    
  • Lecture 26 (Fri, 11/04).
    
  • Lecture 27 (Mon, 11/07).
    
  • Lecture 28 (Wed, 11/09).
    
  • Notes on confidence intervals.
    
  • Lecture 29 (Fri, 11/11).
    
  • Lecture 30 (Mon, 11/14).
    
  • Lecture 31 (Wed, 11/16).
    
  • Lecture 32 (Fri, 11/18).
    
  • Lecture 33 (Mon, 11/28).
    
  • Lecture 34 (Wed, 11/30).
    
  • Lecture 35 (Fri, 12/02).
    
  • Lecture 36 + Review (Mon, 12/05).
    
  • Practice exam
    Solution to the practice
    

• Lab instructions
  • Lab 1
    
  • Lab 2
    
  • Lab 3
    
  • Lab 4
    
  • Lab 5
    Notes: Compute the inverse of the distribution functions (2 examples)
    
  • Lab 6
    
  • Lab 7
    
  • Lab 8
    
  • Lab 9
    
  • Lab 10
    

• R scripts
  • Lab 1
    
  • Lab 2
    
  • Lab 3
    
  • Lab 4
    
  • Lab 5
    
  • Lab 6
    
  • Lab 7
    
  • Lab 8
    
  • Lab 9
    
  • Lab 10
    

• Homework assignments
  • Homework 1 (due 09/23)
    
  • Homework 2 (due 10/07)
    
  • Homework 3 (due 10/21)
    
  • Homework 4 (due 11/11)
    
  • Homework 5 (due 12/02)
    

• Exam-Simulations
  • Monday session
    
  • Wednesday session
    

• Misc
  • z-table