This course is targeted to early career and novice researchers writing their first major competitive biomedical / health research grant proposals. After the course, you will be able to:
Read more
This course is targeted to early career and novice researchers writing their first major competitive biomedical / health research grant proposals. After the course, you will be able to:
This course is targeted to early career and novice researchers writing their first major competitive biomedical / health research grant proposals. After the course, you will be able to:
1) Identify and summarize key decisions in study design that align scope and complexity with budget and timeline;
2) Describe key variables and their relationships to each other; and
3) Interpret essential parts of a power analysis and summarize appropriate questions for an expert biostatistician.
We are faculty at a major research institution with proven experience training others to health sciences research career success. Study design and analysis planning are key skills for grant writing. This course is part of a larger Specialization called Grant Writing for Health Researchers. Please consider taking the other two courses on (1) Grant proposal plans, sections, and resubmission, and (2) Scientific writing. Together, these have been a recipe for success for researchers at the University of Colorado and beyond. Upon completion, you will earn an e-badge to display your new skills. Please join us!
Three deals to help you save
What's inside
Syllabus
Study Design & Scope
Learn how your choices on study design affect project scope, especially data collection, intervention type, and timeline.
Read more
Syllabus
Good to know
Save this course
Save
Activities
Read 'Statistical Methods for Psychology' by Dale Lehman.
Show steps
This course builds upon several of the concepts from the primary text in this course. Completing this book before the class will provide a solid foundation for the course.
View
Advanced Fitness Assessment and Exercise...
on Amazon
Show steps
-
Read Chapter 1: Introduction to Statistics.
-
Read Chapter 2: Linear Regression.
Review linear regression.
Show steps
This course relies on learners already knowing how to compute a linear regression model and interpret the results. Review those concepts before beginning the course to enhance success.
Browse courses on
Linear Regression
Show steps
-
Review the linear regression formula and key assumptions.
-
Identify use cases where linear regression is the appropriate modeling strategy.
-
Practice fitting and evaluating a linear regression model using a programming language you are comfortable with.
Complete the Coursera tutorial on ANOVA.
Show steps
ANOVA is a key topic covered in this course. Following along with this tutorial will provide an introductory overview of the topic.
Show steps
-
Follow the Coursera tutorial on ANOVA.
-
Complete the practice exercises provided in the tutorial.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Solve 20 practice problems on hypothesis testing.
Show steps
Hypothesis testing plays a key role in statistical research. Solving a series of practice problems will help to solidify the key concepts.
Show steps
-
Find a set of 20 practice problems on hypothesis testing.
-
Solve the problems, showing all of your work.
-
Check your answers against the provided solutions.
Write a blog post explaining logistic regression.
Show steps
Logistic regression will be covered in this course. Creating a blog post will help master the material by organizing and summarizing it to then be able to clearly explain it.
Show steps
-
Explain the concept of logistic regression.
-
Provide examples of how logistic regression is used in practice.
-
Walk through a simple logistic regression example using a programming language or statistical software.
Attend a workshop on statistical power analysis.
Show steps
Statistical power analysis is an important topic covered in this course. Attending a workshop will provide an in-depth understanding of the topic.
Show steps
-
Identify a workshop on statistical power analysis that fits your schedule and interests.
-
Register for the workshop.
-
Attend the workshop and actively participate in the activities.
Join a study group and meet weekly to discuss the course material.
Show steps
Collaborative learning can greatly improve learning outcomes. This activity provides learners with an opportunity to work with peers to solidify their knowledge and understanding.
Show steps
-
Identify 2-3 other learners who are interested in forming a study group.
-
Meet weekly to discuss the course material.
-
Review the lecture notes and assigned readings before each meeting.
-
Take turns leading the discussion and presenting your understanding of the material.
Create a collection of resources on statistical methods.
Show steps
This course covers a wide range of statistical methods. Creating a collection of resources will help to organize and summarize the materials for easier reference.
Show steps
-
Identify and gather resources on statistical methods, such as articles, tutorials, and videos.
-
Organize the resources into a coherent structure.
-
Share the collection with other learners.
Conduct a small-scale statistical analysis project.
Show steps
This course aims to prepare students to conduct statistical analysis. Completing a small-scale project is a great way to apply the knowledge and skills gained from the course.
Show steps
-
Identify a research question that you are interested in exploring.
-
Collect data relevant to your research question.
-
Analyze the data using statistical methods.
-
Write a report summarizing your findings.
Read 'Statistical Methods for Psychology' by Dale Lehman.
Show steps
This course builds upon several of the concepts from the primary text in this course. Completing this book before the class will provide a solid foundation for the course.
View
Advanced Fitness Assessment and Exercise...
on Amazon
Show steps
- Read Chapter 1: Introduction to Statistics.
- Read Chapter 2: Linear Regression.
Review linear regression.
Show steps
This course relies on learners already knowing how to compute a linear regression model and interpret the results. Review those concepts before beginning the course to enhance success.
Browse courses on
Linear Regression
Show steps
- Review the linear regression formula and key assumptions.
- Identify use cases where linear regression is the appropriate modeling strategy.
- Practice fitting and evaluating a linear regression model using a programming language you are comfortable with.
Complete the Coursera tutorial on ANOVA.
Show steps
ANOVA is a key topic covered in this course. Following along with this tutorial will provide an introductory overview of the topic.
Show steps
- Follow the Coursera tutorial on ANOVA.
- Complete the practice exercises provided in the tutorial.
Solve 20 practice problems on hypothesis testing.
Show steps
Hypothesis testing plays a key role in statistical research. Solving a series of practice problems will help to solidify the key concepts.
Show steps
- Find a set of 20 practice problems on hypothesis testing.
- Solve the problems, showing all of your work.
- Check your answers against the provided solutions.
Write a blog post explaining logistic regression.
Show steps
Logistic regression will be covered in this course. Creating a blog post will help master the material by organizing and summarizing it to then be able to clearly explain it.
Show steps
- Explain the concept of logistic regression.
- Provide examples of how logistic regression is used in practice.
- Walk through a simple logistic regression example using a programming language or statistical software.
Attend a workshop on statistical power analysis.
Show steps
Statistical power analysis is an important topic covered in this course. Attending a workshop will provide an in-depth understanding of the topic.
Show steps
- Identify a workshop on statistical power analysis that fits your schedule and interests.
- Register for the workshop.
- Attend the workshop and actively participate in the activities.
Join a study group and meet weekly to discuss the course material.
Show steps
Collaborative learning can greatly improve learning outcomes. This activity provides learners with an opportunity to work with peers to solidify their knowledge and understanding.
Show steps
- Identify 2-3 other learners who are interested in forming a study group.
- Meet weekly to discuss the course material.
- Review the lecture notes and assigned readings before each meeting.
- Take turns leading the discussion and presenting your understanding of the material.
Create a collection of resources on statistical methods.
Show steps
This course covers a wide range of statistical methods. Creating a collection of resources will help to organize and summarize the materials for easier reference.
Show steps
- Identify and gather resources on statistical methods, such as articles, tutorials, and videos.
- Organize the resources into a coherent structure.
- Share the collection with other learners.
Conduct a small-scale statistical analysis project.
Show steps
This course aims to prepare students to conduct statistical analysis. Completing a small-scale project is a great way to apply the knowledge and skills gained from the course.
Show steps
- Identify a research question that you are interested in exploring.
- Collect data relevant to your research question.
- Analyze the data using statistical methods.
- Write a report summarizing your findings.
Career center
Reading list
Share
Similar courses
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
