Statistics 110 and 201 - Fall 2017

Department of Statistics

University of California, Irvine

Welcome to the homepage for Statistics 110/201: Statistical Methods for Data Analysis I

Class Time

Lecture
Lab/Discussion
174 ICS
Lecture A (33790/37890) Mon, Wed 9:30 - 10:50am
Lecture B (37800/37895) Mon, Wed 12:30 - 1:50pm
103 Interim Classroom Facility (ICF)
A1: Fri 9:00 - 9:50; A2: Fri 10:00 - 10:50
B1: Fri 11:00 - 11:50; B2: Fri 12:00 - 12:50

How, when and where to find us:


Professor Jessica Utts Lecture A TA: Wendy RummerfieldLecture B TA: Brandon Berman
2212 Donald Bren Hall 2032 Donald Bren Hall2013 Donald Bren Hall
(949) 824-0649 no phoneno phone
jutts_at_uci.edu [Not clickable to avoid spam] wrummerf_at_uci.edu bermanb_at_uci
Mon, Wed 2:00 to 3:30 and by appointment Mon 11-12:30, Tues 3:30-5Mon 3:30-5, Fri 1-2:30
By Day of Week; See table above for location for each of us
Mon TuesWedThursFri
11:00-12:30, Rummerfield
2:00-3:30, Utts
3:30-5:00, Berman
3:30-5:00, Rummerfield2:00-3:30, UttsNone 1-2:30, Berman

Syllabus and other information

Information about getting an ICS Computing Account, and Installing and Using R and R Studio (Updated throughout the quarter)

Data Sets and Applets that will be used in the course (additional ones posted as needed)

Practice Exams and Exam Keys

Homework Solutions, posted after they are due

  • Assignment #1, Due Wed, Oct 11
  • Assignment #2, Due Wed, Oct 18
  • Assignment #3, Due Wed, Oct 25
  • Assignment #4, Due Mon, Oct 30
  • Assignment #5, Due Wed, Nov 15
  • Assignment #6, Due Wed, Nov 22
  • Assignment #7, Due Wed, Nov 29
  • Assignment #8, Due Wed, Dec 6

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    Daily Schedule

     
    Date Sections covered and skipped; other topics covered Material from class lectures and discussion (posted when covered)Assignment and Date Due
    Fri Sept 29 NO DISCUSSION SECTIONS TODAY
    Mon Oct 2 Introduction and start Chapter 0 Lecture 1 slides (as a pdf file, 6 to a page)
    Wed Oct 4 Finish Chapter 0; Sections 1.1, 1.2 Lecture 2 slides or Compact version Homework assignment #1, due Wed, Oct 11
    Fri Oct 6 Disc Introduction to R and R Studio Notes for Oct 6 discussion in html, and in pdf
    Mon Oct 9 Sections 1.3 to 1.5 Lecture 3 slides or Compact version
    Wed Oct 11 Review hypothesis testing, confidence intervals and distributions; Section 2.1Lecture 4 slides or Compact version
    R code and results for Highway sign-reading example
    Homework assignment #2, due Wed, Oct 18
    Fri Oct 13 Disc R for Regression (plots, linear models, etc) Notes for Oct 13 discussion in html, and in pdf
    Mon Oct 16 Sections 2.2 and 2.3 Lecture 5 slides or Compact version
    Skin cancer example
    Wed Oct 18 Confidence and prediction intervals, Section 2.4Lecture 6 slides or Compact version
    Highway sign example showing CI and PI commands and results
    Homework assignment #3, due Wed, Oct 25
    Fri Oct 20 Disc More R for Regression; Question and Answer Notes for Oct 20 discussion in html, and in pdf
    Mon Oct 23 Sections 3.1 and 3.2Lecture 7 slides or Compact version
    Wed Oct 25 Section 3.3 and Section 3.6 as applied to material in 3.3 Lecture 8 slides (in color) or Compact version (in black and white) Homework assignment #4, due Mon, Oct 30
    Fri Oct 27 Disc R for multiple regression; Midterm review Notes for Oct 27 discussion in html, and in pdf
    Review for Midterm
    Mon Oct 30 Section 3.5; More about ANOVA (not in book) No lecture slides today - on white board, and these 2 examples:
    Multicollinearity example and Example of why order matters
    Wed Nov 1 MIDTERM EXAM (covers through Fri, Oct 27) No homework this week
    Fri Nov 3 Disc More about R for multiple regression Notes for Nov 3 discussion in html, and in pdf
    Mon Nov 6 Section 3.4 and finish Section 3.6Lecture 11 slides or Compact version Homework assignment #5, due Wed, Nov 15 (covers 10/30 and 11/6 lectures)
    Wed Nov 8 Section 4.2 (Skip 4.1) Lecture 12 slides or Compact version
    Best Subsets Real Estate Example
    Fri Nov 10 Disc Veterans' Day Holiday - no class
    Mon Nov 13 Sections 1.5 and 4.3 Lecture on white board, then go over examples.
    Small example of case diagnostics
    Case diagnostics for the real estate example
    Case diagnostics in R
    Homework assignment #6, due Wed, Nov 22 (covers 11/8 and 11/13 lectures)
    Wed Nov 15 R for creating and comparing models; variable selection methods in R R code for Nov 15 lecture in html, and in pdf
    Fri Nov 17 Disc Case diagnostics in R; Regression hypotheses stated as models Notes for Nov 17 discussion in html, and in pdf
    Mon Nov 20 Start Chapter 5 Lecture on white board, then go over example.
    GPA and seat location example
    Wed Nov 22 Continue Chapter 5; Section 7.2 Lecture on white board, then go over example.
    Party Days and seat location example
    Homework assignment #7, due Wed, Nov 29
    Fri Nov 24 Thanksgiving Holiday - no class
    Mon Nov 27 Sections 4.4 and 7.5Lecture 15 slides or Compact version
    Wed Nov 29 Chapter 6 Lecture 16 slides or Compact version
    Two factor ANOVA Example
    Homework assignment #8, due Dec 6
    Fri Dec 1 Disc R for analysis of variance; comparing lm, anova and aov Notes for Dec 1 discussion in html, and in pdf
    Mon Dec 4 Other topics in analysis of variance (random effects, nested factors, repeated measures) Lecture 17 slides or Compact version
    Wed Dec 6 Analysis of covariance; Analysis of variance with more than two factors Lecture on white board
    Analysis of covariance example
    Fri Dec 8 Disc Review for final examANOVA scenarios for discussion and Answers (posted after class)
    Review for final exam
    Mon Dec 11 Lecture B Final Exam, 1:30 to 3:30pm
    Wed Dec 13 Lecture A Final Exam, 8:00 to 10:00am