STAT411/5112  Methods of Data Analysis I  Spring 2018
When you can measure what you are speaking about and express it in numbers you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of an unsatisfactory kind  Kelvin (18241907)
 Syllabus, Al's email, Office Phone: 9945145, Office: Barnard (EPS) 304, Office Hours and Schedule.
 Allison's office hours on 4/17 (Tuesday) and 4/19 (Thursday) are from 9a11a in Wilson 2232.
 R resources:
 home page, download R, download RStudio (a nice R interface)
 help: web pages An Intro to R, SimpleR, printable pdfs: An Intro to R, SimpleR
 Writing a statistical report for Data Analysis problems; Summary of Statistical Findings examples; Scope of Inference Writing examples
 Other useful links:
 Taking STAT412/512 next semester: survey; Questions? contact: Mark Greenwood
 Stat Course Catalog
 Final exam schedule for Spring 2018
 Search classes
 Exams:
 5/3 6PM, Final Exam. Formula sheet provided. Practice exam and solutions. Review sheet. See course schedule below for UPDATED Finals week Office Hours.
 3/2 Midterm Exam 1. Formula sheet provided. SOLUTIONS. Practice exam and solutions.
 STAT511 Project
 Homeworks:
 DUE 4/23 HW12: activity from Chapter 11 MLR notes, more details to be provided in class on 4/20, SOLUTIONS: pdf
 DUE 4/18 HW11, outline of SOLUTIONS: pdf
 DUE 4/11 HW10, SOLUTIONS: pdf or Rmd
 DUE 4/4 HW9, SOLUTIONS: pdf or Rmd
 DUE 3/26 HW8, SOLUTIONS: pdf or Rmd
 DUE 2/26 HW7, SOLUTIONS: pdf or Rmd
 DUE 2/21 HW6, chronic wound data, SOLUTIONS: pdf or Rmd
 DUE 2/12 HW5, SOLUTIONS: pdf or Rmd
 DUE 2/5 HW4, SOLUTIONS
 DUE 1/29 HW3, grading scheme
 DUE 1/22 HW 2, pregnancy and pot use article, SOLUTIONS
 DUE 1/17 HW 1, turn in answers to questions #18 from Lab 1: copy and paste the questions into a new document, then enter your R code and output under each question.
 Labs:
 4/25 Lab 15, open format, come with any questions you have
 4/18 Lab 14, §11 Case influence statistics
 4/11 Lab 13, working on HW11
 4/4 Lab 12, working on HW10
 3/28 Lab 11, working on HW9
 3/21 Lab 10, working on HW8
 3/7 Lab 9, SLR, claims data. Partial SOLUTIONs: pdf and Rmd.
 2/27 Lab 8, working with objects in R: pdf or Rmd
 2/20 Lab 7, working on HW7
 2/14 VALENTINES DAY LAB 6, working on HW6, chronic wound data
 2/7 Lab 5: A closer look at ANOVA table, F distribution, permutation and randomization ANOVA (PERMANOVA), notes
 1/31 Lab 4: checking for normality and the BoxCox transform of 1sample data, SOLUTIONS
 1/24 Lab 3, using RMarkdown: example: Rmd, doc, html
 1/17 Lab 2, working on HW2.
 1/10 Lab 1.pdf: the Rmarkdown file that generated Lab1.pdf; getting started with R; Download R; download RStudio; dairy data as: text, csv
 Extra problems:
 Chapter 11: p. 338 (answers on p. 343): #13, 58.
 Chapter 10: p. 297 (answers on p. 309): #38.
 Chapter 9: p. 261 (answers on p. 269): #1, 2, 411.
 Chapter 8: p. 227 (answers on p. 235): #114.
 Chapter 7: p. 198 (answers on p. 206): #311.
 Chapter 6: p. 170 (answers on p. 175): #1, 4, 611.
 Chapter 5: p. 141 (answers on p. 147): #14, 610, 12.
 Chapter 3: p. 77 (answers on p. 84): #110, 14, 16, 17, 19.
 Chapter 2: p.51 (answers on p.56): #110, 11b.
 Chapter 1: p.22 (answers on p.26): #111, 15.
 Course Schedule
 5/3 12pm  1pm Office Hours in Barnard304; 6pm  8pm Final Exam in JABS407
 5/2 Office Hours CANCELLED (going to sample in Yellowstone)
 5/1 12pm  1pm Office Hours in Barnard304
 4/27 Review
 4/25 §12 An example
 4/23 §12 Variable selection using AIC and BIC and allsubsets regression, Chapter 12 notes

 4/20 §11 Refining the model. Chapter 11 MLR notes: pdf and Rmd, evaluation data
 4/18 NO CLASS  but in lab: §11 Case influence statistics. Chapter 11 SLR notes
 4/16 §10.210.4 CIs for mean response, PI for future response, extra sum of squares F test

 4/13 §10.210.4 Linear combinations of coefficients
 4/11 §10.110.2 How R finds the least squares solution; tests and CIs for individual coefficients, Chapter 10 notes
 4/9 §9.49.6 Fitting an MLR model with factors with more than 2 levels; beware of overfitting

 4/6 §9.49.6 Fitting the basic MLR Model IV with two predictors and an interaction; fitting an MLR model with any number of predictors and factors
 4/4 §9.49.6 Fitting the basic MLR Model III with two predictors without an interaction
 4/2 §9.49.6 Graphical tools for assessing Models III and IV

 3/30 SPRING FRIDAY  NO CLASS
 3/28 §9.19.3 Fitting the basic MLR Model II with one predictor and one factor with an interaction, Chapter 9 notes
 3/26 §9.19.3 Fitting the basic MLR Model I with one predictor and one factor with no interaction

 3/23 §8.5, Extra sum of squares test for model selection, Chapter 8.5 notes
 3/21 §7.5, 8.28.3 Correlation, Robustness of SLR to deviations from assumptions, Chapter 8.28.3 notes.
 3/19 §7.4Tests and CIs for mean response, PIs for a future response and mean response, PIs for a future response

 3/12  3/16 SPRING BREAK!

 3/9 Inclass group work for extra credit
 3/7 §7.4, 8.3, 8.6 Checking regression assumptions, tests of regression parameters, Chapter 7 notes
 3/5 §6.2 Intro to SLR, ROutput: pdf, Rmd

 3/2 Midterm exam
 2/28 Review
 2/26 §6.3 Bonferronis

 2/23 §6.364 Planned vs unplanned tests and CIs, simultaneous family of tests and CIs, Tukeys multiple comparisons after ANOVA
 2/21 §6.2 Testing linear combinations after ANOVA, Chapter 6 notes
 2/19 PRESIDENT'S DAY  NO CLASS

 2/16 §5.6 Random effects ANOVA applied to the skull data with a cluster effect for Epoch
 2/14 §5.6 KruskalWallis (nonparametric ANOVA), random effects ANOVA
 2/12 §5.2 Followup ttest for a planned comparison

 2/9 §5.3, 5.5 ANOVA model, checking ANOVA model assumptions with residuals, notes
 2/7 NO CLASS  but in Lab: A closer look at ANOVA table, F distribution, permutation and randomization ANOVA (PERMANOVA), notes
 2/5 §5.25.3 The basics of ANOVA; ANOVA as a comparison of reduced and full models, Chapter 5 notes, skull data, diagANOVA.r

 2/2 §3.4 3.5 Box Cox transform of 2 sample data, biofilm data, ROutput
 1/31 §3.23.3 Robustness to nonnormality and nonindependence, Resistance to outliers, Chapter 3 notes, timber data
 1/29 §2.3 Twosample z and ttests: unpooled, pooled, paired, ROutput

 1/26 §2.3 t confidence intervals, two sample tests, ROutput
 1/24 §2.2 onesample ztest and ttest, z confidence intervals, ROutput: pdf or Rmd, Chapter 2 notes
 1/22 §1.4, 2.2 permutation test for observational studies, a simulation model for
random sampling, Central Limit Theorem
 1/19 §1.3 Randomization test for experiments, ROutput.
 1/17 §1.2 Study design, sampling plans, Scope of Inference
 1/15 NO CLASS: MARTIN LUTHER KING DAY!