SB1a Applied Statistics I

NEWS (Week 2 of HT16)

We have a computer practical this week on Wednesday 3:30-5 in the new home for
Statistics on St Giles. The IT teaching Lab is next door to the main
lecture theatre on the LGF.

I am hoping everyone can make the 3:30-5 slot so we wont need the
2-3:30 session. The new lab is big enough to fit us all in. If you 
cant make 3:30-5 I will run a lab 2-3:30. Please let me know.

The 3rd assessed practical will be available at the Lab and online from
2pm Wednesday this week. It is due Monday week 7 this term.

Assessed practicals (handout material)

First assessed practical: Normal linear models and R with RnotesForElectrodesAnalysis.R and Resistance and Swim data.

Second assessed practical: Fitting GLM's and R with RnotesForDeathPenaltyAnalysis.R and justice.txt and Study1Data.csv and Study2Data.csv data.

Third assessed practical: Fitting Heirarchical Models and R (here is the bare R-code) with Antechinus.txt data.

Assessed practicals (background and non-assessed)

The location for the HT16 Lab in week 2 has changed to the new home for Statistics on St Giles. See NEWS above.

SB1a practical lab sessions weeks MT 3,5 and 7 and HT week 2, Wednesdays 2-3:30pm and 3:30-5pm in 1SPR.
You should attend one session in each of these weeks. Here are your respective lab times.

SB1 assessed practical hand-in times: 12 noon on Monday week 8 MT15, Monday week 2 HT16,
Monday week 7 HT16, Monday, week 2 TT16 (questions go out at the time of the previous practical lab).
These four assessed practicals make up 34% of your USM for SB1.

The practicals assume familiarity with certain R-methods. This is something you can learn in the practical
teaching sessions. R is free high quality software for statistical computing, available for download here.

Here is a link to some tips written by Dr Matechou on writing reports.

Here are some links to background R material: very basic R-exercises and solutions; a link to the
CRAN R tutorial An Introduction to R.

First (non-assessed) practical: Normal linear models and R with RnotesForTreesDataAnalysis.R
and RnotesForFrogsDataAnalysis.R

An example practical report with RnotesForRatsDataAnalysis.R

Lecture material

Week 1: overheads for briefing, L1&2 and R-code

Week 2: overheads for L3&4 and R-code for L3 and R-code for L4.

Week 3: overheads for L5&6 and R-code for L5 and R-code for L6.

Week 4: overheads for L7&8 and R-code for L8 (pages 12,13 added Tuesday 3/11/15).

Week 5: overheads for L9&10 and R-code for L's 10-11.

Week 6: overheads for L11&12 and R-code for L's 11-12 and L's 12-13.

Week 7: overheads for L13&14 and R-code for L14 and L14-15.

Week 8: overheads for L15&16 and R-code for L16.

Problem sheets

Week 3 classes - Problem Sheet 1 due 5pm Friday week 2 at SPR1.

Week 4 classes - Problem Sheet 2 due 5pm Friday week 3 at SPR1.

Week 5 classes - Problem Sheet 3 due 5pm Friday week 4 at SPR1.

Week 6 classes - Problem Sheet 4 due 5pm Friday week 5 at SPR1.

Week 7 classes - Problem Sheet 5 due 5pm Friday week 6 at SPR1.

Week 8 classes - Problem Sheet 6 due 5pm Friday week 7 at SPR1. The aids.csv data are here.

Your class times have been posted. Please let me know if there is a clash. Available classes are Mondays 11-12 and 12-1,
and Wednesdays at 10. Hand in your work to the appropriate SB1a tray in SPR1 by 5pm on Fridays.

Lecture material from last year (MT14)

Lecture notes
Lecture Notes - some extra detail on the material presented in lectures. The material on GLM's is "less polished".

Data files
Data files. The ohp.txt data has been slightly randomised.

Material from 2013

Dr Eleni Matechou's lecture notes from last year.

Reading material

Recommended

A.C. Davison "Statistical Models", Cambridge

J.J. Faraway "Linear Models with R", Chapman and Hall

J.J. Faraway "Extending the Linear Model with R", Chapman and Hall

Other very helpful texts and more advanced reading

A. Gelman and J. Hall "Data analysis using regression and multilevel/hierarchical models", Cambridge University Press

F.L. Ramsey and D.W. Schafer "The Statistical Sleuth", Duxbury press

A.J. Dobson and A.G. Barnett "An Introduction to Generalized Linear Models", 3rd Edition, Chapman and Hall

W.N. Venables and B.D. Ripley "Modern Applied Statistics with S", 4th Edition, Springer

A. Agresti "An Introduction to Categorical Data Analysis", 2nd Edition, Wiley Series in Probability and Statistics

J.C. Pinheiro and Bates "Mixed-effects models in S and S-PLUS", Springer

T. Snijders and J. Bosker "Multilevel analysis", 2nd edition, Sage

nicholls@stats.ox.ac.uk