À propos de ce cours

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Dates limites flexibles
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Niveau intermédiaire

You'll need to have taken the Statistical Thinking and Linear Regression courses in this series or have equivalent knowledge.

Approx. 12 heures pour terminer
Anglais
Sous-titres : Anglais

Ce que vous allez apprendre

  • Describe a data set from scratch using descriptive statistics and simple graphical methods as a first step for advanced analysis using R software

  • Interpret the output from your analysis and appraise the role of chance and bias as potential explanations

  • Run multiple logistic regression analysis in R and interpret the output

  • Evaluate the model assumptions for multiple logistic regression in R

Compétences que vous acquerrez

Logistic RegressionR Programming
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire

You'll need to have taken the Statistical Thinking and Linear Regression courses in this series or have equivalent knowledge.

Approx. 12 heures pour terminer
Anglais
Sous-titres : Anglais

Enseignant

Offert par

Logo Imperial College London

Imperial College London

Commencez à travailler pour obtenir votre master

Ce cours fait partie du diplôme intégralement en ligne Global Master of Public Health de Imperial College London. Si vous êtes admis au programme complet, vos cours seront pris en compte dans votre apprentissage diplômant.

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1

Semaine 1

2 heures pour terminer

Introduction to Logistic Regression

2 heures pour terminer
3 vidéos (Total 12 min), 7 lectures, 2 quiz
3 vidéos
Introduction to Logistic Regression5 min
Odds and Odds Ratios3 min
7 lectures
About Imperial College & the team5 min
How to be successful in this course5 min
Grading policy5 min
Data set and Glossary10 min
Additional Reading10 min
Why does linear regression not work with binary outcomes?10 min
Odds Ratios and Examples from the Literature10 min
2 exercices pour s'entraîner
Logistic Regression10 min
End of Week Quiz10 min
Semaine
2

Semaine 2

3 heures pour terminer

Logistic Regression in R

3 heures pour terminer
2 vidéos (Total 11 min), 4 lectures, 2 quiz
2 vidéos
Logistic Regression in R5 min
4 lectures
How to Describe Data in R20 min
Results of Cross Tabulation20 min
Practice in R: Simple Logistic Regression15 min
Feedback - Output and Interpretation from Simple Logistic Regression35 min
2 exercices pour s'entraîner
Cross Tabulation30 min
Interpreting Simple Logistic Regression30 min
Semaine
3

Semaine 3

3 heures pour terminer

Running Multiple Logistic Regression in R

3 heures pour terminer
1 vidéo (Total 4 min), 6 lectures, 1 quiz
6 lectures
Describing your Data and Preparing to Run Multiple Logistic Regression35 min
Practice in R: Describing Variables20 min
Feedback20 min
Practice in R: Running Multiple Logistic Regression15 min
Feedback: Multiple Regression Model
Feedback on the Assessment10 min
1 exercice pour s'entraîner
Running A New Logistic Regression Model30 min
Semaine
4

Semaine 4

5 heures pour terminer

Assessing Model Fit

5 heures pour terminer
3 vidéos (Total 17 min), 10 lectures, 3 quiz
3 vidéos
Overfitting and Non-convergence6 min
Summary of the Course3 min
10 lectures
Model Fit in Logistic Regression10 min
How to Interpret Model Fit and Performance Information in R10 min
Further Reading on Model Fit20 min
Summary of Different Ways to Run Multiple Regression10 min
Practice in R: Applying Backwards Elimination30 min
Feedback: Backwards Elimination20 min
Practice in R: Run a Model with Different Predictors30 min
Feedback on the New Model10 min
Further Reading on Model Selection Methods20 min
R Code for the Whole Module20 min
3 exercices pour s'entraîner
Quiz on R’s Default Output for the Model30 min
Overfitting and Model Selection20 min
End of Course Quiz

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À propos du Spécialisation Analyse statistique avec R pour la santé publique

Statistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health. In this specialisation, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis. You’ll learn about key statistical concepts like sampling, uncertainty, variation, missing values and distributions. Then you’ll get your hands dirty with analysing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalisation – using R, one of the most widely used and versatile free software packages around. This specialisation consists of four courses – statistical thinking, linear regression, logistic regression and survival analysis – and is part of our upcoming Global Master in Public Health degree, which is due to start in September 2019. The specialisation can be taken independently of the GMPH and will assume no knowledge of statistics or R software. You just need an interest in medical matters and quantitative data....
Analyse statistique avec R pour la santé publique

Foire Aux Questions

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