TMA4255 Applied Statistics, spring 2011

Lectures

Lectures: Tuesday 12.15-14.00 in F3
Thursday 8.15-10.00 in F3

NB: new room on Thursdays - exept for April 7 which will be in EL3.

Detailed plan with handouts

(for tentative overview scroll down)
1up="one slide pr page", 2up="two slides pr page", 4up="four slides pr page".
NBNB: the reading list is based on the WMMY book. The slides are used in the lectures and can not replace READING the literature on the reading list.

Date Part Chapter Topic Handouts Data Additional activity/notes
26 14.04.11 1-7 Summing up, exams, questions? 1up 2up 4up
25 12.04.11 add 4.3 Approximation of E and Var, Summing up, questions? 1up 2up 4up
24 07.04.11 7 16 Nonparametric statistics 1up 2up 4up
23 05.04.11 6-7 10.17, 16 Contingency tables, Nonparametric statistics shoshoni.MTW Nonparametric methods
22 31.03.11 6 10.14-10.16 Contingency tables 1up 2up 4up
21 29.03.11 5- 6 17.5, 10.14 SPC, Goodness of fit tests 1up 2up 4up Test of association
20 24.03.11 5 17.4 Statistical process control 1up 2up 4upfeilbrikker.MTW sjukefravere.MTW Control charts with data
19 22.03.11 4-5 13.13, 17.1-17.4 Random effects ANOVA, Statistical process control 1up 2up 4up metalltjukkleik.MTW
18 17.03.11 4 14.1-14.3 Two factor ANOVA 1up 2up 4up eysenck.MTW
17 15.03.11 4 13.8-13.10 Randomized block designs 1up 2up 4up
16 10.03.11 4 13.4, 13.6 Equal variances? Multiple comparisons. 1up 2up 4up redcellfolate.MTW
15 08.03.11 4 13.1-13.3 One factor analysis of variance 1up 2up 4up aggregates.MTW Proof thm 13.2(pdf) ANOVA (pdf)
E 03.03.11 3 No lecture Supervision of project, Place: The office of Håkon Toftaker
E 01.03.11 3 No lecture Supervision of project, Place: F3
14 24.02.11 3 BHH Ch 12 Fractional factorial designs 1up 2up 4up
13 22.02.11 3 BHH Ch 12 Fractional factorial designs 1up 2up 4up BHHreactor16.MTW BHHreactor32.MTW Box, Hunter and Hunter Chapter 12 (pdf)
12 17.02.11 3 Note p 13-16 Blocking 1up 2up 4up Homework: enter data from Figure 2 in Note into MINITAB and reproduce the analyses on pages 9 and 11 in the Note. 2in4example.MTW limabeans.MTW pilotdata8blokk.MTW DOE in MINITAB and Seed to Plant compulsory project example (pdf)
11 15.02.11 3 Note p 4-12 Effects, 2in3, full 2ink factorial, estimating variance1up 2up 4up
10 10.02.11 2-3 Note p 1-3 Finish stepwise routines for MLR (slides 19-24) from lecture 9. Then factorial experiments (pages 1-3) in the note1up 2up 4up Note: Factorial experiments at two levels
9 08.02.11 2 12.6, 12.7, 12.9, 12.11, 12.13 Orthogonality and multicollinearity, testing subsets of parameters, model selection.1up 2up 4up acidrain.MTW (MINITAB) and acidrain.txt (R) Note: Transformations
8 03.02.11 2 12.4-12.6, 12.10 ANOVA, Model check using residuals, Prediction. 1up 2up 4upswissTMA4255.r R analyses of swiss data and wrongmodelMLR.r, R analyses with wrong model
7 01.02.11 2 11.6, 12.1-12.4 Prediction in simple linear regression (slides 9-16 from lecture 6), The multiple linear regression model - including matrix notation, least squares estimators 1up 2up 4upswiss.MTW (MINITAB) and available in R as swiss
6 27.01.11 2 11.5-11.8 Simple linear regression: sum of squares, inference, prediction1up 2up 4upaswan.MTW (MINITAB) and aswan.txt (R) Printout from MINITAB from the wood quality example (I'll bring copies on paper for you to write on at the lecture)
5 25.01.11 2 11.1-11.4 Start with manual calculation on the blackboard for the Fusion-time example (using slides from last time). Then, simple linear regression.1up 2up 4upstiffdens.MTW (MINITAB) and stiffdens.txt (R) Linear regression
4 20.01.11 1 8.8, 9.4, 9.8, 9.9, 9.13, 10.8, 10.13 One and two sample t-test, two sample F-test 1up 2up 4upfusiontime.MTW (MINITAB) and fusiontime.txt (R) Comparing means
3 18.01.11 1 8.7, 9.4, 10.7 Hypothesis testing, t-distribution, t-test, confidence interval 1up 2up 4up LDLds.MTW (MINITAB) and LDLds.txt (R) Hypothesis testing and p-values
2 13.01.11 1 6.2-6.3, 8.3-8.6 Normal distribution, normal plot, distribution mean and S2 1up 2up 4up Quantiles in the normal distribution
1 11.01.11 1 8.1-8.3 Introduction, LDL example, sampling, X and f(x) 1up 2up 4up Presenting data Population and sample

Tentative lecture plan

Weeek Chapter Topic Exercise
2-3 8-10 Introduction. One and two sample inference based on normal data 1+2
4-5-6 11-12 Linear regression 3+4+5
6-7-8 Design of experiments 6+7
9 Compulsory individual project
10-11-12 13-14 Analysis of variance 8+9
12 17 Statistical process control 10
13 10 Statistical analysis of contingency tables 11
14 16 Nonparametric statistics 11
15 Summing up and concluding remarks
2011-04-13, Mette Langaas