About this Course

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Shareable Certificate
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100% online
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Intermediate Level

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

Approx. 15 hours to complete
English

What you will learn

  • 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

Skills you will gain

  • Correlation And Dependence
  • Linear Regression
  • R Programming
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

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

Approx. 15 hours to complete
English

Offered by

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Imperial College London

Start working towards your Master's degree

This course is related to the 100% online Global Master of Public Health from Imperial College London. It will provide you with a preview of the topics, materials and instructors so you can decide if the full online degree program is right for you.

Syllabus - What you will learn from this course

Content RatingThumbs Up97%(1,311 ratings)Info
Week
1

Week 1

5 hours to complete

INTRODUCTION TO LINEAR REGRESSION

5 hours to complete
7 videos (Total 34 min), 9 readings, 5 quizzes
Week
2

Week 2

4 hours to complete

Linear Regression in R

4 hours to complete
3 videos (Total 11 min), 8 readings, 2 quizzes
Week
3

Week 3

4 hours to complete

Multiple Regression and Interaction

4 hours to complete
4 videos (Total 17 min), 9 readings, 2 quizzes
Week
4

Week 4

3 hours to complete

MODEL BUILDING

3 hours to complete
5 videos (Total 16 min), 7 readings, 2 quizzes

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About the Statistical Analysis with R for Public Health Specialization

Statistical Analysis with R for Public Health

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