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EDUwise: Engineering Knowledge & Learning @UCNQr6tmn-Py8Sf-938__IBQ@youtube.com

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54:59
Lek. 11 | Matematik - Wavelets (Part 1/2)
55:58
Lek. 12 | Matematik - Wavelets Og B Splines (Part 2/2)
01:17:32
Lek. 13 | Matematik - Specielle Funktioner (Part 1/1)
01:04:06
Lek. 11 | Matematik - Wavelets (Part 2/2)
37:32
Lek. 12 | Matematik - Wavelets Og B Splines (Part 1/2)
48:52
Lec 2 | Mathematics - Banach Spaces (Part 1/2)
54:04
Lek 21 | Matematik 1 - Riemann Integraler (Part 1/2)
44:18
Lek 22 | Matematik 1 - Plan Integraler (Part 1/2)
40:14
Lek 21 | Matematik 1 - Riemann Integraler (Part 2/2)
38:47
Lek 22 | Matematik 1 - Plan Integraler (Part 2/2)
04:38
13C day 5
06:03
13F Course summary day 8
02:24
13D Course summary day 6
06:24
13J Single slide overview
06:19
13HCourse summary day 10
05:00
13I Course summary day 12
06:42
13G Course summary day 9
05:58
13K Perspective
04:33
13E Course summary day 7
16:08
13A Course summary day 13
14:12
13B Course summary day 4
17:36
12F Chisquare test
08:24
12D Hypothesis test for one proportion
13:42
12H Analysis of proportions in R
15:03
12B Confidence interval for one proportion
09:11
12C Planning for precision of proportion
09:21
12E Two proportions
08:50
12G Analysis of contingency tables
16:02
12A Proportions intro
06:54
11C Two way ANOVA computations
17:29
11E Two way ANOVA posthoc
07:36
11B Two way ANOVA Model
04:34
11F Two way A NOVA model control
13:27
11D Two way ANOVA F test
24:45
11G Two way A NOVA case study
19:19
11 A Two way ANOVA Intro
15:12
10A Oneway ANOVA
18:58
10C Oneway ANOVA Computation
04:21
10G Oneway ANOVA Model control
05:54
10B Oneway ANOVA
08:49
10E Oneway ANOVA and two sample t test
10:08
10D Oneway ANOVA F test
17:06
10H Oneway ANOVA Acomplete example
14:06
10F Oneway ANOVA Post hoc
08:10
9E Curvilinearity with MLR
06:45
9F Confidence and prediction intervals
11:38
9C Model selection inMLR
14:57
9B MLR Multiple Linear Regression
21:41
9A Linea rregression warm up
15:52
9G Colinarity in MLR
09:57
9D Model validation Residual investigations
06:51
9H The overall MLR method
07:39
8F Confidence and prediction intervals
14:49
8E Hypothesis testing and confidence intervals
03:06
8G The Routput
07:10
8I Model control
10:14
8H Correlation and regression
12:22
8C Leasts quares method
09:56
8B The regression model
14:54
8D Statistics and linearregression