Acerca de este Curso

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Resultados profesionales del estudiante

50%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio

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

Aprox. 15 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

Qué aprenderás

  • Describe when a linear regression model is appropriate to use

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

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

Habilidades que obtendrás

Correlation And DependenceLinear RegressionR Programming

Resultados profesionales del estudiante

50%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio

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

Aprox. 15 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

ofrecido por

Logotipo de Imperial College London

Imperial College London

Comienza a trabajar para obtener tu maestría

Este curso es parte del Global Master of Public Health completamente en línea de Imperial College London. Si eres aceptado en el programa completo, tus cursos cuentan para tu título.

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

5 horas para completar

INTRODUCTION TO LINEAR REGRESSION

5 horas para completar
7 videos (Total 34 minutos), 9 lecturas, 5 cuestionarios
7 videos
Pearson’s Correlation Part I3m
Pearson’s Correlation Part II6m
Intro to Linear Regression: Part I4m
Intro to Linear Regression: Part II3m
Linear Regression and Model Assumptions: Part I6m
Linear Regression and Model Assumptions: Part II5m
9 lecturas
About Imperial College London & the Team10m
How to be successful in this course10m
Grading policy10m
Data set and Glossary10m
Additional Reading10m
Linear Regression Models: Behind the Headlines5m
Linear Regression Models: Behind the Headlines: Written Summary20m
Warnings and precautions for Pearson's correlation20m
Introduction to Spearman correlation15m
5 ejercicios de práctica
Linear Regression Models: Behind the Headlines10m
Correlations30m
Spearman Correlation20m
Practice Quiz on Linear Regression20m
End of Week Quiz20m
Semana
2

Semana 2

4 horas para completar

Linear Regression in R

4 horas para completar
3 videos (Total 11 minutos), 8 lecturas, 2 cuestionarios
3 videos
Fitting the linear regression3m
Multiple Regression4m
8 lecturas
Recap on installing R10m
Assessing distributions and calculating the correlation coefficient in R 10m
Feedback10m
How to fit a regression model in R10m
Feedback15m
Fitting the Multiple Regression in R30m
Feedback10m
Summarising correlation and linear regression30m
2 ejercicios de práctica
Linear Regression20m
End of Week Quiz20m
Semana
3

Semana 3

4 horas para completar

Multiple Regression and Interaction

4 horas para completar
4 videos (Total 17 minutos), 9 lecturas, 2 cuestionarios
4 videos
Introduction to Key Dataset Features: Part II2m
Interactions between binary variables4m
Interactions between binary and continuous variables5m
9 lecturas
How to assess key features of a dataset in R20m
How to check your data in R10m
Good Practice Steps20m
Practice with R: Run a Good Practice Analysis30m
Practice with R: Run Multiple Regression30m
Feedback10m
Practice with R: Running and interpreting a multiple regression30m
Feedback15m
Additional Reading10m
2 ejercicios de práctica
Fitting and interpreting model results20m
Interpretation of interactions20m
Semana
4

Semana 4

3 horas para completar

MODEL BUILDING

3 horas para completar
5 videos (Total 16 minutos), 7 lecturas, 2 cuestionarios
5 videos
Variable Selection3m
Developing a Model Building Strategy6m
Summary of developing a Model Building Strategy56s
Summary of Course1m
7 lecturas
Feedback10m
Further details of limitations of stepwise10m
How many predictors can I include?10m
Practice with R: Developing your model
Practice with R: Fitting the final model10m
Feedback on developing the model10m
Final R Code20m
2 ejercicios de práctica
Problems with automated approaches20m
End of Course Quiz20m

Revisiones

Principales revisiones sobre LINEAR REGRESSION IN R FOR PUBLIC HEALTH

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Acerca de Programa especializado: Análisis estadístico con R para el área de la salud pública

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....
Análisis estadístico con R para el área de la salud pública

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