课程信息
4.7
19 个评分
2 个审阅

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

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

完成时间大约为9 小时

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

英语(English)

字幕:英语(English)

您将学到的内容有

  • 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

您将获得的技能

Correlation And DependenceLinear RegressionR Programming

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

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

完成时间大约为9 小时

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

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 5 小时

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 个视频 (总计 34 分钟), 9 个阅读材料, 5 个测验
7 个视频
Pearson’s Correlation Part I3分钟
Pearson’s Correlation Part II6分钟
Intro to Linear Regression: Part I4分钟
Intro to Linear Regression: Part II3分钟
Linear Regression and Model Assumptions: Part I6分钟
Linear Regression and Model Assumptions: Part II5分钟
9 个阅读材料
About Imperial College London & the Team10分钟
How to be successful in this course10分钟
Grading policy10分钟
Data set and Glossary10分钟
Additional Reading10分钟
Reading: Linear Regression Models: Behind the Headlines5分钟
Linear Regression Models: Behind the Headlines: Written Summary20分钟
Warnings and precautions for Pearson's correlation20分钟
Introduction to Spearman correlation15分钟
5 个练习
Linear Regression Models: Behind the Headlines10分钟
Correlations30分钟
Spearman Correlation20分钟
Practice Quiz on Linear Regression20分钟
End of Week Quiz20分钟
2
完成时间为 4 小时

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 个视频 (总计 11 分钟), 8 个阅读材料, 2 个测验
3 个视频
Fitting the linear regression3分钟
Multiple Regression4分钟
8 个阅读材料
Recap on installing R10分钟
Assessing distributions and calculating the correlation coefficient in R 10分钟
Feedback10分钟
How to fit a regression model in R10分钟
Feedback15分钟
Fitting the Multiple Regression in R30分钟
Feedback10分钟
Summarising correlation and linear regression30分钟
2 个练习
Linear Regression20分钟
End of Week Quiz20分钟
3
完成时间为 4 小时

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 个视频 (总计 17 分钟), 9 个阅读材料, 2 个测验
4 个视频
Introduction to Key Dataset Features: Part II2分钟
Interactions between binary variables4分钟
Interactions between binary and continuous variables5分钟
9 个阅读材料
How to assess key features of a dataset in R20分钟
How to check your data in R10分钟
Good Practice Steps20分钟
Practice with R: Run a Good Practice Analysis30分钟
Practice with R: Run Multiple Regression30分钟
Feedback10分钟
Practice with R: Running and interpreting a multiple regression30分钟
Feedback15分钟
Additional Reading10分钟
2 个练习
Fitting and interpreting model results20分钟
Interpretation of interactions20分钟
4
完成时间为 3 小时

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 个视频 (总计 16 分钟), 7 个阅读材料, 2 个测验
5 个视频
Variable Selection3分钟
Developing a Model Building Strategy6分钟
Summary of developing a Model Building Strategy56
Summary of Course1分钟
7 个阅读材料
Feedback10分钟
Further details of limitations of stepwise10分钟
How many predictors can I include?10分钟
Practice with R: Developing your model
Practice with R: Fitting the final model10分钟
Feedback on developing the model10分钟
Final R Code20分钟
2 个练习
Problems with automated approaches20分钟
End of Course Quiz20分钟

讲师

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Alex Bottle

Reader in Medical Statistics
School of Public Health
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Victoria Cornelius

Senior Lecturer in Medical Statistics and Clinical Trials

立即开始攻读硕士学位

此 课程 隶属于 伦敦帝国学院 提供的 100% 在线 Global Master of Public Health。如果您被录取参加全部课程,您的课程将计入您的学位学习进程。

关于 伦敦帝国学院

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....

关于 Statistical Analysis with R for Public Health 专项课程

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

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