This video describes how to do Logistic Regression in R, step-by-step. We start by importing a dataset and cleaning it up, then we perform logistic regression on a very simple model, followed by a fancy model. Lastly we draw a graph of the predicted probabilities that came from the Logistic Regression.

The code that I use in this video can be found on the StatQuest GitHub:
https://github.com/StatQuest/logistic_regression_demo/blob/master/logistic_regression_demo.R

For more details on what’s going on, check out the following StatQuests:

For a general overview of Logistic Regression:

The odds and log(odds), clearly explained:

The odds ratio and log(odds ratio), clearly explained:

Logistic Regression, Details Part 1, Coefficients:

Logistic Regression, Details Part 2, Fitting a line with Maximum Likelihood:

Logistic Regression Details Part 3, R-squared and its p-value:

Saturated Models and Deviance Statistics, Clearly Explained:

Deviance Residuals, Clearly Explained:

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0:00 Awesome song and introduction
0:29 Load and format data
3:54 Dealing with missing data
5:03 Verifying that the data is not imbalanced
6:44 Logistic regression with one independent variable
12:48 Logistic regression with many independent variables
15:13 Graphing the predicted probabilities

#statquest #logistic
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Learn how to use R to fit a model to a binary (yes/no) response variable, regardless of whether you have raw data or proportions. If this vid helps you, please help me a tiny bit by mashing that ‘like’ button. For more #rstats joy, crush that ‘subscribe’ button!
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Paul Andersen explains how populations eventually reach a carrying capacity in logistic growth. He begins with a brief discussion of population size ( N ), growth rate ( r ) and exponential growth. He then explains how density dependent limiting factors eventually decrease the growth rate until a population reaches a carrying capacity ( K ). A mathematical simulation of this process is included along with a brief discussion of r and K selected species.

Intro Music Atribution
Title: I4dsong_loop_main.wav
Artist: CosmicD
Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/
Creative Commons Atribution License

All images are either Public Domain or Creative Commons Attribution Licenses:
“File:Frog in Frogspawn.jpg.” Wikipedia, the Free Encyclopedia. Accessed April 19, 2013. http://en.wikipedia.org/wiki/File:Frog_in_frogspawn.jpg.
“File:Stress-coloured Brookesia Desperata Female with Two Recently Laid Eggs.png.” Wikipedia, the Free Encyclopedia. Accessed April 19, 2013. http://en.wikipedia.org/wiki/File:Stress-coloured_Brookesia_desperata_female_with_two_recently_laid_eggs.png.
Nevit. English: White Rabbit, 2011. Own work. https://commons.wikimedia.org/wiki/File:Rabbit_nevit.svg.
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Keep going! Check out the next lesson and practice what you’re learning:
https://www.khanacademy.org/science/hs-biology/x4c673362230887ef:matter-and-energy-in-ecosystems/x4c673362230887ef:population-growth-and-carrying-capacity/a/population-growth-and-carrying-capacity-article

Learn about population growth rates and how they can be modeled by exponential and logistic equations.

Watch the next lesson: https://www.khanacademy.org/science/biology/ecology/population-growth-and-regulation/v/density-dependent-and-density-independent-population-regulation

Missed the previous lesson? Watch here: https://www.khanacademy.org/science/biology/ecology/population-ecology/v/organism-life-history-and-fecundity

Ecology on Khan Academy: Why are polar bears found only in the Arctic? Why does mildew grow in your shower and not (hopefully) in your sock drawer? Learn how ecologists study the interactions between organisms and their environment, and how these interactions affect where, and in what numbers, different types of organisms are found.

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This calculus video tutorial explains the concept behind the logistic growth model function which describes the limits of population growth. This shows you how to derive the general solution or logistic growth formula starting from a differential equation which describes the population growth rate. This video contains 1 example problem with multiple parts.

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