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Data Tutorial: Calculating growth rates for cattle, pigs, and small ruminants

by Cynthia Naydani | The Power of Data in Farm Animal Practice Timestamps 0:00 - Recap 0:30 - Why calculate growth rates? 1:20 - Calculating daily live weight gain using…

From  Chris Smith 0 likes 71 plays 0  

HealthyR demo: Create table one

Data and code at: https://github.com/SurgicalInformatics/healthyr_demos

From  Sarah Elliot 0 likes 58 plays 0  

HealthyR demo: Reproducible examples (reprex)

Data and code at: https://github.com/SurgicalInformatics/healthyr_demos

From  Riinu Pius 0 likes 79 plays 0  

HealthyR demo: geom_bar() vs geom_col()

Data and code at: https://github.com/SurgicalInformatics/healthyr_demos

From  Riinu Pius 0 likes 74 plays 0  

Causal Inference: Johannes Buck

This talk has been automatically captioned. You can remove these by pressing CC on the video toolbar. Name: Johannes Buck Talk Title: Properties and Consistency of QTree in Max-Linear Models…

From  Belle Taylor 0 likes 20 plays 0  

Univariate Tail Estimation: Jonathan El Methni

This talk has been automatically captioned. You can remove these by pressing CC on the video toolbar. Name: Jonathan El Methni Talk Title: A bias-reduced version of the Weissman extreme…

From  Belle Taylor 0 likes 32 plays 0  

Jonathan El Methni EVA Talk Preview

This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Jonathan El Methni Talk Title: A bias-reduced version of the Weissman extreme quantile estimator Abstract:…

From  Anna Munro 0 likes 29 plays 0  

11.b

The second video of the Inf2d lecture on Unification.

From  Claudia-Elena Chirita 0 likes 197 plays 0  

FDS-S2-01-2-5 Maximum likelihood estimation of logistic regression coefficients

We introduce the principle of maximum likelihood, and show how to derive the likelihood as a function of the coefficients for logistic regression. We also mention one topical application of logistic…

From  David Sterratt 0 likes 338 plays 0  

FDS-S1-11-2-3 Estimating the confidence interval of means of large samples

We'll derive confidence intervals for the mean of large samples, when we can assume the sampling distribution of the mean is normal.

From  David Sterratt 0 likes 360 plays 0  

Topic 4: Mathematical Prerequisites for the SNADA course (SNADA, Chapter 1)

This topic motivates the need for using mathematical analysis in this course on sensor network and data analysis course, emphasising that relying on pre-existing software solution is…

From  James Hopgood 0 likes 333 plays 0  

The Terry Wall Lecture 2020: Professor Claire Voisin, Collège de France

Subtitles have been automatically addeded to this lecture, to turn off please select "cc". Professor Claire Voisin, Collège de France - Quadratic Extensions: Algebra and Geometry …

From  Liam Holligan 0 likes 43 plays 0  

FP - Lecture 3 - Lists and Recursion

This is the video of the third FP lecture, covering Lists and Recursion.

From  Claudia-Elena Chirita 0 likes 876 plays 0  

Lecture 3 Part 3: But there's no solution...

What happens when the method in the first part of the lecture fails. We look at why and find a way of dealing with the problem.

From  David Ingram 0 likes 128 plays 0  

Lecture 2 Part 2: Boundary Conditions

In the second part of this lecture we look at a the use of boundary conditions expressed as both initial value and boundary value problems to find the unknown coefficients in the general solution and…

From  David Ingram 0 likes 146 plays 0  

Preparing Data

Preparing Data

From  Matt Sanders 0 likes 1,074 plays 0