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Lectures from 02402 Introduction to Statistics in Auditorium 42 (F17)

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Lecture 13L: Exam info

A little discussion.

Date: 05/05/2017 16:21 - Duration: 00:13:42 - Views: 1

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Lecture 13K: Perspective.

Other statistics courses

Date: 05/05/2017 16:20 - Duration: 00:05:57 - Views: 1

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Lecture 13J: Single slide overview

Course “situations” - A single slide “tree overview” of the course

Date: 05/05/2017 16:19 - Duration: 00:06:23 - Views: 1

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Lecture 13I: Course summary: day 12

Statistics for proportions and frequency tables.

Date: 05/05/2017 16:17 - Duration: 00:04:59 - Views: 1

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Lecture 13H: Course summary: day 10-11

One- and twoway Analysis of Variance, ANOVA

Date: 05/05/2017 16:16 - Duration: 00:06:18 - Views: 1

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Lecture 13G: Course summary: day 9

Multiple linear regression (MLR)

Date: 05/05/2017 16:15 - Duration: 00:06:41 - Views: 1

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Lecture 13F: Course summary: day 8

Simple linear regression

Date: 05/05/2017 16:13 - Duration: 00:06:02 - Views: 1

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Lec 13E: Course summary: day 7

Simulation and simulation based statistics, bootstrapping.

Date: 05/05/2017 15:36 - Duration: 00:04:32 - Views: 1

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Lec 13D: Course summary: day 6

Two sample statistics: CIs and hypothesis test.

Date: 05/05/2017 15:22 - Duration: 00:02:23 - Views: 1

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Lec 13C: day 5

One sample hypothesis testing, p-values.

Date: 05/05/2017 15:20 - Duration: 00:04:37 - Views: 1

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Lec 13B: Course summary, day 4

One sample confidence intervals

Date: 05/05/2017 15:15 - Duration: 00:14:11 - Views: 1

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Lec 13A. Course summary, day 1-3

Descriptive statistics and probability.

Date: 05/05/2017 15:13 - Duration: 00:16:07 - Views: 3

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Lec 12H: Analysis of proportions in R

Examples including the malformation data.

Date: 25/04/2017 17:02 - Duration: 00:13:41 - Views: 16

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Lec 12G: Analysis of contingency tables.

Frequency tables, r-by-c tables.

Date: 25/04/2017 17:00 - Duration: 00:08:49 - Views: 19

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Lec 12F: Chi-square test

Comparing several proportions

Date: 25/04/2017 16:59 - Duration: 00:17:35 - Views: 13

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Lec 12E: Two proportions

Confidence interval and hypothesis test.

Date: 25/04/2017 16:57 - Duration: 00:09:20 - Views: 18

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Lec 12D: Hypothesis test for one proportion

And examples

Date: 25/04/2017 16:56 - Duration: 00:08:23 - Views: 16

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Lec 12C: Planning for precision of proportion

How to chose n to meet wanted margin of error for proportion.

Date: 25/04/2017 16:54 - Duration: 00:09:10 - Views: 20

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Lec 12B: Confidence interval for one proportion

And examples.

Date: 25/04/2017 16:52 - Duration: 00:15:02 - Views: 19

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Lec 12A: Proportions - intro

Example: Malformation proportions among newborns in Denmark.

Date: 25/04/2017 16:50 - Duration: 00:16:01 - Views: 13

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Lec 11G: Twoway ANOVA, case study

A complete worked through example

Date: 20/04/2017 05:22 - Duration: 00:24:44 - Views: 26

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Lec 11F: Twoway ANOVA, model control

Residual investigations.

Date: 20/04/2017 05:21 - Duration: 00:04:33 - Views: 23

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Lec 11E: Twoway ANOVA post hoc

How to summarize and finish the statistical analysis.

Date: 20/04/2017 05:19 - Duration: 00:17:28 - Views: 25

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Lec 11D: Twoway ANOVA - F-test

Testing hypotheses of equal means.

Date: 20/04/2017 05:18 - Duration: 00:13:26 - Views: 22

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Lec 11C: Twoway ANOVA computations

The decomposition of variability and the ANOVA table

Date: 20/04/2017 05:16 - Duration: 00:06:53 - Views: 26

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Lec 11B: Twoway ANOVA, Model

And estimation of means.

Date: 20/04/2017 05:14 - Duration: 00:07:35 - Views: 26

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Lec 11A: Twoway ANOVA, Intro

TV data and small example

Date: 20/04/2017 05:12 - Duration: 00:19:18 - Views: 27

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Lec 10H: Oneway ANOVA. A complete example.

A worked through example from the book.

Date: 04/04/2017 20:58 - Duration: 00:17:05 - Views: 36

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Lec 10G: Oneway ANOVA. Model control

Residual plotting.

Date: 04/04/2017 20:51 - Duration: 00:04:20 - Views: 28

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Lec 10F: Oneway ANOVA. Post hoc.

How to find pairwise CIs and hypothesis tests.

Date: 04/04/2017 20:42 - Duration: 00:14:05 - Views: 34

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Lec 10E: Oneway ANOVA and two-sample t-test

The relation to the pooled independent samples t-test.

Date: 04/04/2017 20:34 - Duration: 00:08:48 - Views: 42

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Lec 10D: Oneway ANOVA. F-test.

Testing the hypothesis of equal means.

Date: 04/04/2017 20:29 - Duration: 00:10:07 - Views: 37

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Lec 10C: Oneway ANOVA. Computation

Variance decomposition and the ANOVA table

Date: 04/04/2017 20:23 - Duration: 00:18:57 - Views: 40

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Lec 10B: Oneway ANOVA.

Model and hypothesis.

Date: 04/04/2017 20:22 - Duration: 00:05:53 - Views: 40

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Lec 10A: Oneway ANOVA.

Intro and TV data example

Date: 04/04/2017 20:20 - Duration: 00:15:11 - Views: 45

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Lec 09H: The overall MLR method

How to approach and proceed in an analysis

Date: 29/03/2017 19:21 - Duration: 00:06:50 - Views: 32

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Lec 09G: Colinarity in MLR

The challenge of having several x-variables expressing almost the same.

Date: 29/03/2017 19:20 - Duration: 00:15:51 - Views: 52

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Lec 09F: Confidence and prediction intervals

For the MLR model fit.

Date: 29/03/2017 19:19 - Duration: 00:06:44 - Views: 43

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Lec 09E: Curvilinearity with MLR.

How to validate linearity by fitting a polynomial regression.

Date: 29/03/2017 19:17 - Duration: 00:08:09 - Views: 28

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Lec 09D: Model validation: Residual investigations

Normality, variance homogeneity and linearity structure.

Date: 28/03/2017 17:11 - Duration: 00:09:56 - Views: 54

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Lec 09C: Model selection in MLR.

Forward and Backward.

Date: 28/03/2017 17:05 - Duration: 00:11:37 - Views: 49

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Lec 09B: MLR, Multiple Linear Regression

Model, computations and statistical inference in R.

Date: 28/03/2017 17:03 - Duration: 00:14:56 - Views: 64

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Lec 09A: Linear regression warm up

With a view towards multiple linear regression.

Date: 28/03/2017 17:01 - Duration: 00:21:40 - Views: 43

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Lec 08I: Model control.

Residual investigation - checking for model assumptions.

Date: 21/03/2017 16:24 - Duration: 00:07:09 - Views: 61

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Lec 08H: Correlation and regression

The connection. Explained variation.

Date: 21/03/2017 16:23 - Duration: 00:10:13 - Views: 60

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Lec 08G: The R-output.

A summary of the R-output from simple linear regression.

Date: 21/03/2017 16:21 - Duration: 00:03:05 - Views: 60

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Lec 08F: Confidence and prediction intervals

For the line itself.

Date: 21/03/2017 16:19 - Duration: 00:07:38 - Views: 55

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Lec 08E: Hypothesis testing and confidence intervals.

Statistical inference for slope and intercept.

Date: 21/03/2017 16:18 - Duration: 00:14:48 - Views: 65

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Lec 08D: Statistics and linear regression.

Sampling uncertainties in finding the line.

Date: 21/03/2017 16:17 - Duration: 00:14:53 - Views: 63

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Lec 08C: Least squares method.

How to find the best possible line.

Date: 21/03/2017 16:15 - Duration: 00:12:21 - Views: 58

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Lec 08B: The regression model.

The statistical model expression.

Date: 21/03/2017 16:13 - Duration: 00:09:55 - Views: 60

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Lec 08A: Linear regression, example.

The height-weight example as a motivation.

Date: 21/03/2017 16:12 - Duration: 00:11:31 - Views: 64

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Lec 07H: Non-parametric bootstrap - two sample setting.

Confidence interval for the difference between any two features.

Date: 14/03/2017 18:14 - Duration: 00:07:47 - Views: 43

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Lec 07G: Non-parametric bootstrap.

The one-sample setting. Confidence interval for any feature.

Date: 14/03/2017 18:12 - Duration: 00:09:50 - Views: 45

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Lec 07F: Parametric bootstrap - two sample setting

Confidence interval for the difference of any feature

Date: 14/03/2017 18:06 - Duration: 00:06:25 - Views: 47

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Lec 07E: Parametric Bootstrap

The one-sample setting. Confidence interval for any feature.

Date: 14/03/2017 18:05 - Duration: 00:19:50 - Views: 60

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Lec 07D: Bootstrapping - an intro

Parametric and non-parametric and Von Munchausen

Date: 14/03/2017 18:03 - Duration: 00:04:25 - Views: 48

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Lec 07C: Error propagation

The approximate classical rule and the simulation approach.

Date: 14/03/2017 18:02 - Duration: 00:18:13 - Views: 60

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Lec 07B: Simulation example

The area of plates with random lengths and widths

Date: 14/03/2017 18:01 - Duration: 00:11:10 - Views: 60

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Lec 07A: Introduction to simulation

What is it really?

Date: 14/03/2017 17:59 - Duration: 00:16:44 - Views: 56

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Lec 06K: The pooled two-sample t-test

An alternative assuming that the two population variances are equal.

Date: 07/03/2017 15:56 - Duration: 00:04:02 - Views: 54

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Lec 06J: Planning: Power and sample size

Learn about power and how to find the needed sample sizes (n) for one- and two-sample mean investigations.

Date: 07/03/2017 15:54 - Duration: 00:14:01 - Views: 43

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Lec 06I: Planning for wanted precision

Wanted width of the CI can give you the size of n needed.

Date: 07/03/2017 15:53 - Duration: 00:07:01 - Views: 41

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Lec 06H: Checking the normality assumption for two samples

Just do twice what was learned foro one-sample, e.g. the Wally plot.

Date: 07/03/2017 15:51 - Duration: 00:03:24 - Views: 44

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Lec 06G: The paired design and the paired t-test.

See the benefits of the paired design, and learn how to do the paired t-test. Incl. example in R.

Date: 07/03/2017 15:49 - Duration: 00:17:30 - Views: 48

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Lec 06F: Overlapping confidence intervals?

See why one should be careful with interpreting two separate CIs togethe.

Date: 07/03/2017 15:47 - Duration: 00:07:46 - Views: 58

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Lec 06E: The confidence interval for the difference of two means.

And an example and the link to hypothesis testing.

Date: 07/03/2017 15:46 - Duration: 00:10:00 - Views: 51

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Lec 06D: The two-sample t-test.

The method, an example and how-to in R.

Date: 07/03/2017 15:44 - Duration: 00:13:05 - Views: 64

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Lec 06C: Hypothesis test and p-values - a repetition.

In general terms

Date: 07/03/2017 15:43 - Duration: 00:08:18 - Views: 56

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Lec 06B: The first Kahoot question

About hypothesis testing

Date: 07/03/2017 15:42 - Duration: 00:03:58 - Views: 40

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Lec 06A: Two-sample comparison, motivation

A small example and the results.

Date: 07/03/2017 15:37 - Duration: 00:07:28 - Views: 61

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Lec 05H: Log-transforming data towards normality

An example of data-transformation.

Date: 28/02/2017 17:25 - Duration: 00:11:52 - Views: 52

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Lec 05G: The Wally plot - an R-tutorial.

How to run, use and interpret the wally plot for the investigation of the normality assumption.

Date: 28/02/2017 17:23 - Duration: 00:04:09 - Views: 52

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Lec 05F: Checking for normality

The QQ-plot to investigate the normality assumption and the "Find Wally" version of it.

Date: 28/02/2017 17:21 - Duration: 00:18:27 - Views: 56

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Lec 05E: Hypotethis test in general.

The overall method and the two types of potential errors that can be made.

Date: 28/02/2017 17:18 - Duration: 00:15:42 - Views: 64

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Lec 05D: Critical value and relation to the confidence interval

Detailing the connection between hypothesis testing and the confidence interval method.

Date: 28/02/2017 17:16 - Duration: 00:07:54 - Views: 65

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Lec 05C: The one-sample t-test

Hypothesis test for the mean of one-sample data.

Date: 28/02/2017 17:13 - Duration: 00:21:29 - Views: 72

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Lec 05B: Inital Kahooting of the day

Three recap-questions.

Date: 28/02/2017 17:11 - Duration: 00:05:07 - Views: 49

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Lec 05A: Introduction to hypothesis test

An example and a link to the global discussion of p-values.

Date: 28/02/2017 17:10 - Duration: 00:15:48 - Views: 66

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Lec 04G: The confidence interval for the variance and standard deviation

Meet the chi-square distribution as the way to quantify uncertainties of sample variance computations. Example with R.

Date: 24/02/2017 11:21 - Duration: 00:13:07 - Views: 55

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Lec 04F: A formal interpretation of the confidence interval method

See the long term random dance behaviour of the CI-method.

Date: 24/02/2017 11:19 - Duration: 00:09:52 - Views: 64

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Lec 04E: Non-normal data, Central Limit Theorem (CLT)

See how and why the t-distribution CI-method also works for many non-normal data situations.

Date: 24/02/2017 11:17 - Duration: 00:12:00 - Views: 54

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Lec 04D: The language of statistics and the formal framework

Recap of the basic concepts and the principle of random sampling.

Date: 24/02/2017 11:15 - Duration: 00:12:43 - Views: 60

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Lec 04C: The confidence interval (CI) for the mean.

The actual one sample CI method and example using R.

Date: 24/02/2017 11:13 - Duration: 00:14:11 - Views: 63

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Lec 04B: Quantifying the error in estimating the mean

How to be intelligent in using a sample mean and the t-distribution.

Date: 24/02/2017 11:11 - Duration: 00:23:16 - Views: 67

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Lec 04A: Intro example with confidence intervals

The two confidence intervals of the module exemplified in use.

Date: 24/02/2017 11:08 - Duration: 00:10:02 - Views: 62

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Lec 03H: Identities for the mean and variance

Calculation rules linear functions of random variables.

Date: 15/02/2017 23:50 - Duration: 00:16:04 - Views: 71

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Lec 03G: The exponential distribution

With example and relation to the Poisson distribution

Date: 15/02/2017 23:49 - Duration: 00:11:07 - Views: 58

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Lec 03F: The log-normal distribution

and how it relates to the normal distribution.

Date: 15/02/2017 23:47 - Duration: 00:03:21 - Views: 58

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Lec 03E: The standard normal distribution

How to standardize any normal distribution to the standard normal distribution.

Date: 15/02/2017 23:44 - Duration: 00:08:43 - Views: 53

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Lec 03D: The normal distribution

The famous normal distribution Chapters: 11:56 - Example: Question 2; 17:05 - Example: Quantiles; 05:31 - Example: Normal distribution, Question 1;

Date: 15/02/2017 23:38 - Duration: 00:19:49 - Views: 65

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Lec 03A: The uniform distribution

The "flat" distribution.

Date: 15/02/2017 23:29 - Duration: 00:13:33 - Views: 66

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Lec 03B: Mean and variance of ontinuous random variables

Use integration for the continuous versions of the mean and variance

Date: 15/02/2017 23:24 - Duration: 00:12:27 - Views: 68

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Lec 03A: Continuous random variables, density and distribution functions

Introduction and definition of continuous distributions

Date: 15/02/2017 23:11 - Duration: 00:20:59 - Views: 93

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Lec 02G: Mean and variance for discrete distributions

Definitions and concepts, and results for the specific distributions.

Date: 07/02/2017 17:08 - Duration: 00:12:05 - Views: 75

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Lec 02F: Specific distributions in R

See how we have "d", "p" and "r"-versions of many specific distributins in R.

Date: 07/02/2017 17:06 - Duration: 00:02:47 - Views: 60

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Lec 02E: The Poisson distribution

The probability model for counting events in time or space with example.

Date: 07/02/2017 17:04 - Duration: 00:13:32 - Views: 67

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Lec 02D: The hypergeometric distribution

The sampling without replacement probability model with quality control example.

Date: 07/02/2017 17:03 - Duration: 00:17:40 - Views: 77

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Lec 02C: Specific discrete distributions: The binomial

Definition, the binomial coefficient, example in R. Chapters: 11:06 - Simulating the number of life time major research application successes; 15:21 - Example on daily error correction;

Date: 07/02/2017 16:58 - Duration: 00:26:15 - Views: 102

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Lec 02B: Discrete distribution function

Definition and dice roll example.

Date: 07/02/2017 16:48 - Duration: 00:05:02 - Views: 79

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Lec 02A: Discrete Random variabls and the density function

Definitions and dice-roll examples in R.

Date: 07/02/2017 16:45 - Duration: 00:15:26 - Views: 105

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Lec 01I: R and data visualization

A brief introduction to R and its role in the course.

Date: 01/02/2017 10:17 - Duration: 00:15:54 - Views: 95

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Lec 01H: Summary statistics IV: Covariance and correlation

Measuring the linear relation between two variables. Height and weigh example.

Date: 01/02/2017 10:15 - Duration: 00:12:26 - Views: 88

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Lec 01G: Summary statistics III: Quantiles

Definitions and examples.

Date: 01/02/2017 09:48 - Duration: 00:08:32 - Views: 68

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Lec 01F: Summary statistics II: Variance and standard deviation

Definitions and examples

Date: 01/02/2017 09:45 - Duration: 00:13:03 - Views: 75

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Lec 01E: Summary statistics I: Mean and Median

Why summary statistics and defining and exemplifying the mean and the median.

Date: 01/02/2017 09:40 - Duration: 00:09:59 - Views: 79

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Lec 01D: Statistics and Engineers?

Why statistics is important for most engineers with some DTU Compute perspectives.

Date: 01/02/2017 09:37 - Duration: 00:14:33 - Views: 60

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Lec 01C: Why statistics?

A primer of statistics with focus on human health in 1000 years!

Date: 01/02/2017 09:34 - Duration: 00:11:12 - Views: 70

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Lec 01B: Kahoot Start

The first Kahoot question of the course.

Date: 01/02/2017 09:31 - Duration: 00:03:37 - Views: 62

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Lec 01A: Course Information

An overview of the practical course structure.

Date: 01/02/2017 08:40 - Duration: 00:05:12 - Views: 99

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Total duration: 20:45:26