À propos de ce cours
4.7
16 notes
2 avis

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 should know the basics of types of variables, distributions, hypothesis testing, p values and confidence intervals using R, though I'll recap.

Approx. 9 heures pour terminer

Recommandé : 4 weeks of study 3-5 hours per week ...

Anglais

Sous-titres : Anglais

Ce que vous allez apprendre

  • Check

    Describe when a linear regression model is appropriate to use

  • Check

    Read in and check a data set's variables using the software R prior to undertaking a model analysis

  • Check

    Fit a multiple linear regression model with interactions, check model assumptions and interpret the output

Compétences que vous acquerrez

Correlation And DependenceLinear RegressionR Programming

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 should know the basics of types of variables, distributions, hypothesis testing, p values and confidence intervals using R, though I'll recap.

Approx. 9 heures pour terminer

Recommandé : 4 weeks of study 3-5 hours per week ...

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
5 heures pour terminer

INTRODUCTION TO LINEAR REGRESSION

Before jumping ahead to run a regression model, you need to understand a related concept: correlation. This week you’ll learn what it means and how to generate Pearson’s and Spearman’s correlation coefficients in R to assess the strength of the association between a risk factor or predictor and the patient outcome. Then you’ll be introduced to linear regression and the concept of model assumptions, a key idea underpinning so much of statistical analysis....
7 vidéos (Total 34 min), 9 lectures, 5 quiz
7 vidéos
Pearson’s Correlation Part I3 min
Pearson’s Correlation Part II6 min
Intro to Linear Regression: Part I4 min
Intro to Linear Regression: Part II3 min
Linear Regression and Model Assumptions: Part I6 min
Linear Regression and Model Assumptions: Part II5 min
9 lectures
About Imperial College London & the Team10 min
How to be successful in this course10 min
Grading policy10 min
Data set and Glossary10 min
Additional Reading10 min
Reading: Linear Regression Models: Behind the Headlines5 min
Linear Regression Models: Behind the Headlines: Written Summary20 min
Warnings and precautions for Pearson's correlation20 min
Introduction to Spearman correlation15 min
5 exercices pour s'entraîner
Linear Regression Models: Behind the Headlines10 min
Correlations30 min
Spearman Correlation20 min
Practice Quiz on Linear Regression20 min
End of Week Quiz20 min
Semaine
2
4 heures pour terminer

Linear Regression in R

You’ll be introduced to the COPD data set that you’ll use throughout the course and will run basic descriptive analyses. You’ll also practise running correlations in R. Next, you’ll see how to run a linear regression model, firstly with one and then with several predictors, and examine whether model assumptions hold....
3 vidéos (Total 11 min), 8 lectures, 2 quiz
3 vidéos
Fitting the linear regression3 min
Multiple Regression4 min
8 lectures
Recap on installing R10 min
Assessing distributions and calculating the correlation coefficient in R 10 min
Feedback10 min
How to fit a regression model in R10 min
Feedback15 min
Fitting the Multiple Regression in R30 min
Feedback10 min
Summarising correlation and linear regression30 min
2 exercices pour s'entraîner
Linear Regression20 min
End of Week Quiz20 min
Semaine
3
4 heures pour terminer

Multiple Regression and Interaction

Now you’ll see how to extend the linear regression model to include binary and categorical variables as predictors and learn how to check the correlation between predictors. Then you’ll see how predictors can interact with each other and how to incorporate the necessary interaction terms into the model and interpret them. Different kinds of interactions exist and can be challenging to interpret, so we will take it slowly with worked examples and opportunities to practise....
4 vidéos (Total 17 min), 9 lectures, 2 quiz
4 vidéos
Introduction to Key Dataset Features: Part II2 min
Interactions between binary variables4 min
Interactions between binary and continuous variables5 min
9 lectures
How to assess key features of a dataset in R20 min
How to check your data in R10 min
Good Practice Steps20 min
Practice with R: Run a Good Practice Analysis30 min
Practice with R: Run Multiple Regression30 min
Feedback10 min
Practice with R: Running and interpreting a multiple regression30 min
Feedback15 min
Additional Reading10 min
2 exercices pour s'entraîner
Fitting and interpreting model results20 min
Interpretation of interactions20 min
Semaine
4
3 heures pour terminer

MODEL BUILDING

The last part of the course looks at how to build a regression model when you have a choice of what predictors to include in it. It describes commonly used automated procedures for model building and shows you why they are so problematic. Lastly, you’ll have the chance to fit some models using a more defensible and robust approach....
5 vidéos (Total 16 min), 7 lectures, 2 quiz
5 vidéos
Variable Selection3 min
Developing a Model Building Strategy6 min
Summary of developing a Model Building Strategy56s
Summary of Course1 min
7 lectures
Feedback10 min
Further details of limitations of stepwise10 min
How many predictors can I include?10 min
Practice with R: Developing your model
Practice with R: Fitting the final model10 min
Feedback on developing the model10 min
Final R Code20 min
2 exercices pour s'entraîner
Problems with automated approaches20 min
End of Course Quiz20 min

Enseignants

Avatar

Alex Bottle

Reader in Medical Statistics
School of Public Health
Avatar

Victoria Cornelius

Senior Lecturer in Medical Statistics and Clinical Trials

Commencez à travailler pour obtenir votre master

This cours is part of the 100% online Global Master of Public Health from Imperial College London. If you are admitted to the full program, your courses count towards your degree learning.

À propos de Imperial College London

Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges. Imperial students benefit from a world-leading, inclusive educational experience, rooted in the College’s world-leading research. Our online courses are designed to promote interactivity, learning and the development of core skills, through the use of cutting-edge digital technology....

À propos de la Spécialisation Statistical Analysis with R for Public Health

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....
Statistical Analysis with R for Public Health

Foire Aux Questions

  • Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.

  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

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