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John McGready, PhD, MS
Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, you'll extend simple regression to the prediction of a single outcome of interest on the basis of multiple variables. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include multiple logistic regression, the Spline approach, confidence intervals, p-values, multiple Cox regression, adjustment, and effect modification.
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Syllabus
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
Within this module, an overview of multiple regression will be provided. Additionally, examples and applications will be examined. A practice quiz is provided to test your knowledge before completing the graded quiz.
Read more
Syllabus
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
Within this module, an overview of multiple regression will be provided. Additionally, examples and applications will be examined. A practice quiz is provided to test your knowledge before completing the graded quiz.
Read more
Multiple Logistic Regression
Module two covers examples of multiple logistic regression, basics of model estimates, and a discussion of effect modification. In addition to lectures, you will also be completing a practice quiz and graded quiz.
Multiple Cox Regression
The last module for this class focuses on multiple Cox regression, the “Linearity” assumption, examples, and applications. You will complete a practice quiz, graded quiz, and project.
Course Project
During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about self-administration of injectable contraception and one about medical appointment scheduling in Brazil. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies. If you've already taken other courses in this specialization, then this scenario will be familiar.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds on students' linear regression skills to cover multiple regression, logistic regression, and Cox Regression
Emphasizes statistical concepts applied to real-world data from published health studies
Taught by a researcher with a PhD in Biostatistics from Johns Hopkins University
Suitable for learners interested in health and medical research or those seeking to advance their statistical skills
Requires a strong foundation in statistics, including probability, hypothesis testing, and regression analysis
May require additional resources for students who need to refresh their statistical knowledge
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Reviews summary
Multiple regression for public health
Learners say that this course is an outstanding introduction to multiple regression for public health and biostatistics. The course is well-structured with engaging examples. It is highly recommended for beginners to the field, as well as for learners looking to improve their understanding of biostatistics.
Course moves at a good pace
"Recommended for beginners in the field. Instructor John McGready presents the otherwise complex concepts of Biostatistics straightforwardly, with many examples and a perfect pace."
Course includes relevant examples from the field
"This course covers all types of Multiple Regressions. Instructor explained the complex topics in simple language. Relevant examples from clinical field and thorough explanation by the Instructor."
"Great way to learn multiple regression, the course applies multiple examples to make the concepts practical. Thanks."
"The course simplifies important concepts in understanding biostatistics using detailed and explanations and examples"
Instructor John McGready is passionate and engaging
"Professor McGready is a passionate instructor who makes BioStats interesting and concrete through his real-world experiences and exercises."
"Another excellent class from Dr. John."
"Recommended for beginners in the field. Instructor John McGready presents the otherwise complex concepts of Biostatistics straightforwardly, with many examples and a perfect pace."
Some mistakes in quizzes
"Moreover, there are always some mistakes in the quizzes. Not sure whether it is the problem with Coursera system or with the quiz content provided by the instructor."
"There are some mistakes in the quizzes and the answer sheets, and I think it is because Dr McGready used the lectures that he uses in his classes at JHU, but had to transcribe the quizzes into the Coursera format."
Assessments can be challenging
"Expectedly, this course is a notch higher in difficulty compared to the preceding course in the Coursera Specialization. The conceptual explanations were arguably splendid, and the quiz/test questions are quite challenging."
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 Multiple Regression Analysis in Public Health with these
activities:
Review basic statistics and probability concepts
Show steps
Strengthen your foundation by reviewing the underlying concepts that support multiple regression analysis.
Browse courses on
Statistics
Show steps
-
Go through your notes or textbooks from previous statistics and probability courses.
-
Complete online quizzes or practice problems to test your understanding.
Organize and review course materials
Show steps
Stay organized and improve retention by compiling and reviewing course materials regularly.
Show steps
-
Create a system for organizing lecture notes, assignments, and other course materials.
-
Periodically review your organized materials to reinforce your understanding.
Attend a workshop on multiple regression modeling
Show steps
Gain hands-on experience and insights from experts in the field by attending a specialized workshop.
Browse courses on
Multiple Regression
Show steps
-
Research and identify workshops on multiple regression modeling that fit your schedule and interests.
-
Register and attend the workshop, actively participating in the sessions.
-
Network with other participants and experts in the field to expand your knowledge.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Discuss case studies in multiple regression
Show steps
Engage with peers to explore real-world applications of multiple regression, solidifying your understanding.
Browse courses on
Multiple Regression
Show steps
-
Find a group of peers to collaborate with.
-
Select a case study that involves multiple regression analysis.
-
Discuss the case study, including the research question, methodology, results, and implications.
Practice interpreting multiple regression results
Show steps
Sharpen your ability to interpret multiple regression results, ensuring a solid understanding of the technique.
Browse courses on
Multiple Regression
Show steps
-
Review the course module on multiple regression.
-
Analyze real-world data and interpret the results using multiple regression techniques.
-
Discuss your interpretations with peers or the instructor for feedback and insights.
Mentor other students in multiple regression concepts
Show steps
Enhance your understanding by teaching others, reinforcing your knowledge and fostering a supportive learning environment.
Browse courses on
Multiple Regression
Show steps
-
Identify opportunities to mentor other students who are struggling with multiple regression.
-
Create a study plan or provide guidance on specific topics based on their needs.
-
Regularly meet with the students to discuss their progress and provide support.
Create a data visualization to illustrate multiple regression results
Show steps
Develop your ability to communicate complex statistical findings by creating engaging data visualizations.
Browse courses on
Multiple Regression
Show steps
-
Analyze a dataset using multiple regression.
-
Choose an appropriate data visualization format (e.g., graph, chart, table).
-
Design and create the data visualization, ensuring clear and effective communication of the results.
Explore advanced topics in multiple regression
Show steps
Delve deeper into advanced topics in multiple regression, expanding your knowledge and skillset.
Browse courses on
Multiple Regression
Show steps
-
Identify advanced topics in multiple regression that align with your interests.
-
Search for online tutorials, articles, or videos on these topics.
-
Complete the tutorials and apply the concepts to real-world datasets.
Contribute to open-source multiple regression projects
Show steps
Gain practical experience and contribute to the multiple regression community by participating in open-source projects.
Browse courses on
Multiple Regression
Show steps
-
Identify open-source multiple regression projects that align with your interests and skill level.
-
Review the project documentation and identify areas where you can contribute.
-
Make a meaningful contribution to the project, such as fixing bugs, adding features, or improving documentation.
Review basic statistics and probability concepts
Show steps
Strengthen your foundation by reviewing the underlying concepts that support multiple regression analysis.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Go through your notes or textbooks from previous statistics and probability courses.
- Complete online quizzes or practice problems to test your understanding.
Organize and review course materials
Show steps
Stay organized and improve retention by compiling and reviewing course materials regularly.
Show steps
Show steps
Show steps
- Create a system for organizing lecture notes, assignments, and other course materials.
- Periodically review your organized materials to reinforce your understanding.
Attend a workshop on multiple regression modeling
Show steps
Gain hands-on experience and insights from experts in the field by attending a specialized workshop.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Research and identify workshops on multiple regression modeling that fit your schedule and interests.
- Register and attend the workshop, actively participating in the sessions.
- Network with other participants and experts in the field to expand your knowledge.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Discuss case studies in multiple regression
Show steps
Engage with peers to explore real-world applications of multiple regression, solidifying your understanding.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Find a group of peers to collaborate with.
- Select a case study that involves multiple regression analysis.
- Discuss the case study, including the research question, methodology, results, and implications.
Practice interpreting multiple regression results
Show steps
Sharpen your ability to interpret multiple regression results, ensuring a solid understanding of the technique.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Review the course module on multiple regression.
- Analyze real-world data and interpret the results using multiple regression techniques.
- Discuss your interpretations with peers or the instructor for feedback and insights.
Mentor other students in multiple regression concepts
Show steps
Enhance your understanding by teaching others, reinforcing your knowledge and fostering a supportive learning environment.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Identify opportunities to mentor other students who are struggling with multiple regression.
- Create a study plan or provide guidance on specific topics based on their needs.
- Regularly meet with the students to discuss their progress and provide support.
Create a data visualization to illustrate multiple regression results
Show steps
Develop your ability to communicate complex statistical findings by creating engaging data visualizations.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Analyze a dataset using multiple regression.
- Choose an appropriate data visualization format (e.g., graph, chart, table).
- Design and create the data visualization, ensuring clear and effective communication of the results.
Explore advanced topics in multiple regression
Show steps
Delve deeper into advanced topics in multiple regression, expanding your knowledge and skillset.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Identify advanced topics in multiple regression that align with your interests.
- Search for online tutorials, articles, or videos on these topics.
- Complete the tutorials and apply the concepts to real-world datasets.
Contribute to open-source multiple regression projects
Show steps
Gain practical experience and contribute to the multiple regression community by participating in open-source projects.
Browse courses on
Multiple Regression
Show steps
Show steps
Show steps
- Identify open-source multiple regression projects that align with your interests and skill level.
- Review the project documentation and identify areas where you can contribute.
- Make a meaningful contribution to the project, such as fixing bugs, adding features, or improving documentation.
Career center
Learners who complete Multiple Regression Analysis in Public Health will develop knowledge and skills
that may be useful to these careers:
Biostatistician
Biostatistician
The course, *Multiple Regression Analysis in Public Health* provides a solid foundation in the application of statistical methods to health-related research. As a Biostatistician, you will be involved in the design and analysis of studies aimed at improving public health outcomes. The course's focus on multiple regression, along with topics such as multiple logistic regression and Cox regression, will equip you with the skills necessary to model and analyze complex health data. By taking this course, you will gain the statistical expertise required to make meaningful contributions to public health research and policy.
Epidemiologist
Epidemiologist
The course, *Multiple Regression Analysis in Public Health*, delves into the statistical techniques used to investigate the distribution and determinants of health-related events in populations. As an Epidemiologist, you will be responsible for conducting epidemiological studies to identify risk factors for diseases and develop strategies for prevention and control. The course's focus on multiple regression, along with topics such as adjustment and effect modification, will provide you with the skills necessary to analyze epidemiological data and draw valid conclusions. By taking this course, you will gain the statistical foundation required to contribute to the advancement of public health knowledge.
Statistician
Statistician
The course, *Multiple Regression Analysis in Public Health* delves into the application of statistics to the health sciences. As a Statistician, you will be responsible for collecting, analyzing, and interpreting data to inform public health decisions. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to extract meaningful insights from complex data in the context of public health. By studying this course, you will enhance your ability to conduct rigorous statistical analyses and contribute to evidence-based public health practice.
Public Health Analyst
Public Health Analyst
The course, *Multiple Regression Analysis in Public Health* provides a comprehensive overview of statistical methods used in public health research and practice. As a Public Health Analyst, you will be responsible for collecting, analyzing, and interpreting data to inform public health decisions. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to extract meaningful insights from complex data in the context of public health. By taking this course, you will gain the statistical expertise required to contribute to evidence-based public health policy and program development.
Data Scientist
Data Scientist
The course, *Multiple Regression Analysis in Public Health*, introduces statistical techniques used in data science. As a Data Scientist, you will be involved in collecting, cleaning, and analyzing data to extract meaningful insights. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to build and evaluate predictive models. By taking this course, you will gain the statistical expertise required to contribute to data-driven decision-making in various industries.
Health Scientist
Health Scientist
The course, *Multiple Regression Analysis in Public Health*, offers a comprehensive introduction to statistical methods used in health research. As a Health Scientist, you will be involved in the design and analysis of studies aimed at improving health outcomes. The course's focus on multiple regression, along with topics such as multiple logistic regression and Cox regression, will provide you with the skills necessary to model and analyze complex health data. By taking this course, you will gain the statistical expertise required to make meaningful contributions to the advancement of public health knowledge.
Data Analyst
Data Analyst
The course, *Multiple Regression Analysis in Public Health* provides a solid foundation in statistical methods used in data analysis. As a Data Analyst, you will be responsible for collecting, cleaning, and analyzing data to derive meaningful insights. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to extract valuable information from complex datasets. By taking this course, you will gain the statistical expertise required to contribute to data-driven decision-making in various industries.
Actuary
Actuary
The course, *Multiple Regression Analysis in Public Health* provides a foundation in statistical methods used in actuarial science. As an Actuary, you will be responsible for assessing and managing financial risks. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to model and analyze risk data. By taking this course, you will gain the statistical expertise required to make informed decisions in the insurance and financial industries.
Policy Analyst
Policy Analyst
The course, *Multiple Regression Analysis in Public Health* provides an overview of statistical methods used in policy analysis. As a Policy Analyst, you will be involved in evaluating the effectiveness of public policies and programs. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to analyze policy-related data and draw valid conclusions. By taking this course, you will gain the statistical expertise required to contribute to evidence-based policymaking.
Financial Analyst
Financial Analyst
The course, *Multiple Regression Analysis in Public Health*, introduces statistical techniques used in financial analysis. As a Financial Analyst, you will be responsible for analyzing financial data to make investment recommendations. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to model and analyze financial data. By taking this course, you will gain the statistical expertise required to make informed investment decisions.
Market Researcher
Market Researcher
The course, *Multiple Regression Analysis in Public Health*, introduces statistical techniques used in market research. As a Market Researcher, you will be responsible for conducting surveys, analyzing data, and identifying trends to inform marketing strategies. The course's focus on multiple regression, along with topics such as adjustment and effect modification, will provide you with the skills necessary to analyze market data and draw valid conclusions. By taking this course, you will gain the statistical foundation required to contribute to the development of effective marketing campaigns.
Software Engineer
Software Engineer
The course, *Multiple Regression Analysis in Public Health* may be useful for those interested in a career as a Software Engineer. As the course introduces statistical techniques used in machine learning and artificial intelligence, it can provide a foundation for understanding the algorithms and models used in software development. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to analyze and interpret data used in software applications.
Operations Research Analyst
Operations Research Analyst
The course, *Multiple Regression Analysis in Public Health* may be useful for those interested in a career as an Operations Research Analyst. As the course introduces statistical techniques used in optimization and decision-making, it can provide a foundation for understanding the quantitative methods used in operations research. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to analyze and interpret data used in operations research models.
Quantitative Analyst
Quantitative Analyst
The course, *Multiple Regression Analysis in Public Health* may be useful for those interested in a career as a Quantitative Analyst. As the course introduces statistical techniques used in financial modeling and risk management, it can provide a foundation for understanding the quantitative methods used in the financial industry. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to analyze and interpret financial data.
Business Analyst
Business Analyst
The course, *Multiple Regression Analysis in Public Health* may be useful for those interested in a career as a Business Analyst. As the course introduces statistical techniques used in data analysis and decision-making, it can provide a foundation for understanding the quantitative methods used in business analysis. The course's focus on multiple regression, along with topics such as confidence intervals and effect modification, will provide you with the skills necessary to analyze and interpret data used in business decision-making.
For more career information including salaries, visit:
OpenCourser.com/course/0bh98f/multiple
Reading list
We've selected 14 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Multiple Regression Analysis in Public Health .
Is an excellent resource for understanding logistic regression, which is covered in the second module of the course. It is widely used in the field and provides a thorough explanation of the topic.
Provides a foundational overview of regression analysis, which can help students understand the basics of multiple regression, especially linear regression techniques. It can supplement the course by providing a more in-depth explanation of some basic concepts.
Offers a comprehensive introduction to biostatistics, providing foundational knowledge for this course. It covers a wide range of topics, including regression analysis and survival analysis.
Provides a step-by-step guide to performing regression analysis using Stata software. It can be a valuable resource for students who want to gain practical experience with the software.
Covers survival analysis, including the Cox proportional hazards model, which is discussed in the third module of the course. It provides a practical guide to using S software for survival analysis.
Provides a gentle introduction to statistical learning methods, using R software. It can supplement the course by providing a more accessible explanation of some of the concepts covered.
Covers advanced regression models for categorical and limited dependent variables. While it might be too advanced for this course, it can serve as a valuable reference for students who want to explore these topics further.
Comprehensive resource on multiple regression and structural equation modeling. While it might be too in-depth for this course, it could serve as a valuable reference for students who want to explore these topics further.
Provides a comprehensive overview of nonparametric regression methods. While it might be too specialized for this course, it can serve as a valuable resource for students who want to explore these topics further.
Comprehensive reference on statistical learning methods. While it may be too advanced for this course, it can serve as a valuable resource for students who want to углубиться in the field.
Introduces Bayesian regression modeling. While it may be too advanced for this course, it can serve as a valuable reference for students who want to learn about this topic.
Provides insights into the complex development challenges facing Africa. While it is not directly related to the course content, it can be a valuable resource for students who want to understand the broader context of global health.
Discusses the economic factors that contribute to poverty and proposes strategies for addressing them. While it is not directly related to the course content, it can be a valuable resource for students who want to understand the broader context of global health.
This report provides a comprehensive overview of global health statistics. While it is not directly related to the course content, it can be a valuable resource for students who want to understand the current state of global health.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0bh98f/multiple
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Effort
4 weeks, 3-4 hours/week
Level
Introductory
Via
Coursera
Institution
Johns Hopkins University
Instructor
John McGready, PhD, MS
Language
English
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آذربایجان دیلی
This course belongs to a
collection
called
Biostatistics in Public Health . It's comprised of four courses:
- Hypothesis Testing in Public Health
- Multiple Regression Analysis in Public Health (viewing)
- Summary Statistics in Public Health
- Simple Regression Analysis in Public Health
Good to know
Builds on students' linear regression skills to cover multiple regression, logistic regression, and Cox Regression
Emphasizes statistical concepts applied to real-world data from published health studies
Taught by a researcher with a PhD in Biostatistics from Johns Hopkins University
Suitable for learners interested in health and medical research or those seeking to advance their statistical skills
Requires a strong foundation in statistics, including probability, hypothesis testing, and regression analysis
May require additional resources for students who need to refresh their statistical knowledge
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