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In this course, you will develop a working knowledge of linear relationship data in healthcare and practice using R statistical programming to analyze this data. You will learn about some of the most common univariate and multivariate statical methods used in healthcare data analysis and practice applying them in a statistical software package. While the course focuses on application and the use of these statistical methods, there is some discussion of the mathematical underpinning, relevant formulae, and assumptions necessary for understanding the application of statistical methods.
Read more
In this course, you will develop a working knowledge of linear relationship data in healthcare and practice using R statistical programming to analyze this data. You will learn about some of the most common univariate and multivariate statical methods used in healthcare data analysis and practice applying them in a statistical software package. While the course focuses on application and the use of these statistical methods, there is some discussion of the mathematical underpinning, relevant formulae, and assumptions necessary for understanding the application of statistical methods.
Read more
In this course, you will develop a working knowledge of linear relationship data in healthcare and practice using R statistical programming to analyze this data. You will learn about some of the most common univariate and multivariate statical methods used in healthcare data analysis and practice applying them in a statistical software package. While the course focuses on application and the use of these statistical methods, there is some discussion of the mathematical underpinning, relevant formulae, and assumptions necessary for understanding the application of statistical methods.
This self-paced course is comprised of written content, video content, step-by-step follow-along activities, and assessments to reinforce your learning (Assessments available to Verified Track learners only).
The course is comprised of 4 modules that you should complete in order, as each subsequent module builds on the previous one.
- Module 1: Introduction to Correlation and Linear Relationships
- Module 2: Simple OLS Linear Regression
- Module 3: Dummy Variables and Multiple OLS Linear Regression
- Module 4: OLS Linear Regression Diagnostic Tests
Register for this course and see more details by visiting:
OpenCourser.com/course/l46azd/linear
What's inside
Learning objectives
- By the end of this course, you will be able to:
- Implement simple and multiple linear regression models and interpret their results.
- Perform diagnostic tests for linear regression models to determine their validity.
- Use dummy variables in regressions and interpret their results.
- Communicate the results of their analysis to others in a simple language.
- By the end of this course, you will be able to:
- Implement simple and multiple linear regression models and interpret their results.
- Perform diagnostic tests for linear regression models to determine their validity.
- Use dummy variables in regressions and interpret their results.
- Communicate the results of their analysis to others in a simple language.
Syllabus
Verified Learners can earn a certificate for this course by scoring at least 80% overall. Your score in this course is comprised of two main components: the Module Quizzes and a Summative Assessment at the end of the course.
Module Quizzes: These quizzes come at the end of each of the four modules of this course. They are comprised of 5-10 multiple choice, multiple select, fill-in-the-blank, dropdown, and numeric response questions and assess your knowledge of the preceding module -- 60% (15% for each quiz)
Summative Assessment: A final quiz that will be taken at the end of the course. It is comprised of multiple choice and multiple select questions from all four modules of the course. This activity assesses your completion of the course learning objectives -- 40%
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills related to healthcare data analysis in R statistical programming, which is commonly used in the healthcare industry
Taught by HarvardX, who are recognized for their work in the healthcare industry
Provides a foundation for beginners in healthcare data analysis
Covers topics including correlation, linear relationships, simple OLS linear regression, dummy variables, and multiple OLS linear regression, which are core concepts in healthcare data analysis
Teaches how to perform diagnostic tests for linear regression models to determine their validity, which is essential for ensuring the accuracy and reliability of healthcare data analysis
Offers hands-on activities and assessments to reinforce learning, which can be beneficial for students in understanding and applying the concepts
Save this course
Save Linear Relationship Data in Healthcare to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Linear Relationship Data in Healthcare with these
activities:
Review R Programming Basics
Show steps
Familiarize yourself with the basics of R programming, which will be used throughout the course for data analysis.
Browse courses on
R Programming
Show steps
-
Follow an introduction to R tutorial
-
Practice using R commands in a coding environment
-
Complete sample exercises on data handling and visualization
Review 'Regression Analysis by Example'
Show steps
Gain a deeper understanding of regression analysis concepts and techniques.
View
Regression Analysis By Example Using R (Wiley...
on Amazon
Show steps
-
Read selected chapters relevant to the course topics
-
Summarize key concepts and formulas in your own notes
-
Attempt practice problems to reinforce your understanding
Review Essential Linear Algebra with Applications
Show steps
Reviewing this book will help you solidify your understanding of the underlying mathematical concepts that are the backbone of linear regression models.
View
Basic Linear Algebra
on Amazon
Show steps
-
Read Chapters 1-3
-
Complete the exercises at the end of each chapter
-
Summarize the key concepts in each chapter
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Practice Correlation and Linear Relationship Calculations
Show steps
Practicing these calculations will help you develop a strong foundation in the fundamentals of linear relationships and regression analysis.
Browse courses on
Correlation
Show steps
-
Solve practice problems on calculating correlation coefficients
-
Practice fitting linear regression models to data
-
Interpret the results of your analysis
Join a Study Group on Linear Regression
Show steps
Participating in a study group will provide you with opportunities to discuss the course material with other students and learn from their perspectives.
Browse courses on
Linear Regression
Show steps
-
Find a study group or form one with classmates
-
Meet regularly to discuss the course material
-
Work together on practice problems and assignments
Follow Tutorials on Multiple Linear Regression
Show steps
Following these tutorials will help you expand your knowledge of linear regression models to include multiple independent variables.
Browse courses on
Multiple Linear Regression
Show steps
-
Identify online tutorials on multiple linear regression
-
Follow the tutorials and complete the practice exercises
-
Apply the techniques you have learned to analyze real-world data
Attend a Healthcare Data Analytics Meetup
Show steps
Connect with professionals in the field of healthcare data analytics to expand your knowledge.
Browse courses on
Healthcare Data Analytics
Show steps
-
Research and find relevant meetups in your area or online
-
Attend the meetup and actively participate in discussions
-
Follow up with individuals you meet for further networking
Build a Linear Regression Model for Healthcare Data
Show steps
Building a regression model for healthcare data will allow you to apply the concepts you have learned in the course to a real-world problem.
Show steps
-
Identify a healthcare dataset
-
Clean and prepare the data for analysis
-
Develop a linear regression model
-
Evaluate the performance of your model
Attend a Regression Analysis Workshop
Show steps
Enhance your practical skills in regression analysis through hands-on instruction.
Browse courses on
Regression Analysis
Show steps
-
Research and identify reputable workshops led by experts
-
Register for the workshop and actively participate
-
Apply the techniques learned in the workshop to your own projects
Practice Simple Linear Regression Problems
Show steps
Strengthen your ability to apply simple linear regression techniques.
Browse courses on
Simple Linear Regression
Show steps
-
Solve a set of practice problems on simple linear regression
-
Use statistical software to perform regression analysis
-
Interpret the results and draw conclusions
Create a Regression Analysis Presentation
Show steps
Deepen your understanding of regression analysis by teaching it to others.
Browse courses on
Regression Analysis
Show steps
-
Research and gather information on the topic
-
Develop a clear and concise presentation outline
-
Use visual aids and examples to illustrate concepts
-
Practice your presentation and seek feedback
-
Deliver your presentation to a small group or online
Volunteer in a Healthcare Research Project
Show steps
Gain practical experience in healthcare data analysis while contributing to research.
Browse courses on
Healthcare
Show steps
-
Contact local hospitals or research institutions to find opportunities
-
Inquire about ongoing projects related to regression analysis
-
Offer your assistance and participate in data collection or analysis tasks
Contribute to an R Package for Healthcare Data Analysis
Show steps
Deepen your understanding of R by contributing to a real-world project in healthcare data analysis.
Browse courses on
R Programming
Show steps
-
Identify an open-source R package related to healthcare data analysis
-
Review the package documentation and identify potential areas for contribution
-
Make changes to the codebase, add features, or fix bugs
-
Submit a pull request with your changes for review and potential inclusion
Review R Programming Basics
Show steps
Familiarize yourself with the basics of R programming, which will be used throughout the course for data analysis.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Follow an introduction to R tutorial
- Practice using R commands in a coding environment
- Complete sample exercises on data handling and visualization
Review 'Regression Analysis by Example'
Show steps
Gain a deeper understanding of regression analysis concepts and techniques.
View
Regression Analysis By Example Using R (Wiley...
on Amazon
Show steps
Show steps
Show steps
- Read selected chapters relevant to the course topics
- Summarize key concepts and formulas in your own notes
- Attempt practice problems to reinforce your understanding
Review Essential Linear Algebra with Applications
Show steps
Reviewing this book will help you solidify your understanding of the underlying mathematical concepts that are the backbone of linear regression models.
View
Basic Linear Algebra
on Amazon
Show steps
Show steps
Show steps
- Read Chapters 1-3
- Complete the exercises at the end of each chapter
- Summarize the key concepts in each chapter
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Practice Correlation and Linear Relationship Calculations
Show steps
Practicing these calculations will help you develop a strong foundation in the fundamentals of linear relationships and regression analysis.
Browse courses on
Correlation
Show steps
Show steps
Show steps
- Solve practice problems on calculating correlation coefficients
- Practice fitting linear regression models to data
- Interpret the results of your analysis
Join a Study Group on Linear Regression
Show steps
Participating in a study group will provide you with opportunities to discuss the course material with other students and learn from their perspectives.
Browse courses on
Linear Regression
Show steps
Show steps
Show steps
- Find a study group or form one with classmates
- Meet regularly to discuss the course material
- Work together on practice problems and assignments
Follow Tutorials on Multiple Linear Regression
Show steps
Following these tutorials will help you expand your knowledge of linear regression models to include multiple independent variables.
Browse courses on
Multiple Linear Regression
Show steps
Show steps
Show steps
- Identify online tutorials on multiple linear regression
- Follow the tutorials and complete the practice exercises
- Apply the techniques you have learned to analyze real-world data
Attend a Healthcare Data Analytics Meetup
Show steps
Connect with professionals in the field of healthcare data analytics to expand your knowledge.
Browse courses on
Healthcare Data Analytics
Show steps
Show steps
Show steps
- Research and find relevant meetups in your area or online
- Attend the meetup and actively participate in discussions
- Follow up with individuals you meet for further networking
Build a Linear Regression Model for Healthcare Data
Show steps
Building a regression model for healthcare data will allow you to apply the concepts you have learned in the course to a real-world problem.
Show steps
Show steps
Show steps
- Identify a healthcare dataset
- Clean and prepare the data for analysis
- Develop a linear regression model
- Evaluate the performance of your model
Attend a Regression Analysis Workshop
Show steps
Enhance your practical skills in regression analysis through hands-on instruction.
Browse courses on
Regression Analysis
Show steps
Show steps
Show steps
- Research and identify reputable workshops led by experts
- Register for the workshop and actively participate
- Apply the techniques learned in the workshop to your own projects
Practice Simple Linear Regression Problems
Show steps
Strengthen your ability to apply simple linear regression techniques.
Browse courses on
Simple Linear Regression
Show steps
Show steps
Show steps
- Solve a set of practice problems on simple linear regression
- Use statistical software to perform regression analysis
- Interpret the results and draw conclusions
Create a Regression Analysis Presentation
Show steps
Deepen your understanding of regression analysis by teaching it to others.
Browse courses on
Regression Analysis
Show steps
Show steps
Show steps
- Research and gather information on the topic
- Develop a clear and concise presentation outline
- Use visual aids and examples to illustrate concepts
- Practice your presentation and seek feedback
- Deliver your presentation to a small group or online
Volunteer in a Healthcare Research Project
Show steps
Gain practical experience in healthcare data analysis while contributing to research.
Browse courses on
Healthcare
Show steps
Show steps
Show steps
- Contact local hospitals or research institutions to find opportunities
- Inquire about ongoing projects related to regression analysis
- Offer your assistance and participate in data collection or analysis tasks
Contribute to an R Package for Healthcare Data Analysis
Show steps
Deepen your understanding of R by contributing to a real-world project in healthcare data analysis.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Identify an open-source R package related to healthcare data analysis
- Review the package documentation and identify potential areas for contribution
- Make changes to the codebase, add features, or fix bugs
- Submit a pull request with your changes for review and potential inclusion
Career center
Learners who complete Linear Relationship Data in Healthcare will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/l46azd/linear
Reading list
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For more information about how these books relate to this course, visit:
OpenCourser.com/course/l46azd/linear
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Effort
2 to 4 hours per week for 4 weeks
Level
Intermediate
Via
edX
Institution
MGH Institute of Health Professions
Session
June 13, 2024
- January 1, 2025
Language
English
Transcript
English
Good to know
Develops skills related to healthcare data analysis in R statistical programming, which is commonly used in the healthcare industry
Taught by HarvardX, who are recognized for their work in the healthcare industry
Provides a foundation for beginners in healthcare data analysis
Covers topics including correlation, linear relationships, simple OLS linear regression, dummy variables, and multiple OLS linear regression, which are core concepts in healthcare data analysis
Teaches how to perform diagnostic tests for linear regression models to determine their validity, which is essential for ensuring the accuracy and reliability of healthcare data analysis
Offers hands-on activities and assessments to reinforce learning, which can be beneficial for students in understanding and applying the concepts
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