| 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 4up | feilbrikker.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 variance | 1up 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 note | 1up 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 4up | swissTMA4255.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 4up | swiss.MTW (MINITAB) and available in R as swiss | | |
6 | 27.01.11 | 2 | 11.5-11.8 | Simple linear regression: sum of squares, inference, prediction | 1up 2up 4up | aswan.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 4up | stiffdens.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 4up | fusiontime.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 | |