Introduction to Healthcare Data Analysis
In this course, you will develop a solid foundational understanding of the most common statistical methods used in health care data analysis.
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In this course, you will develop a solid foundational understanding of the most common statistical methods used in health care data analysis.
In this course, you will develop a solid foundational understanding of the most common statistical methods used in health care data analysis.
This course covers some of the most common univariate and multivariate statistical methods used in healthcare data analysis. Students will also learn how to apply these methods using a statistical software package. The course covers basic data wrangling that is necessary for data analysis. It uses examples from the healthcare industry. This course focuses on the use of statistical methods although there may be some discussion of the mathematical underpinnings and 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 5 modules that you should complete in order, as each subsequent module builds on the previous one.
- Module 1: Descriptive Statistics and Data Distributions
- Module 2: Sampling Distribution and Hypothesis Tests
- Module 3: Visualize and Summarize Data in R
- Module 4: Independent and Paired Sample t-tests
- Module 5: ANOVA
What's inside
Learning objectives
- By the end of this course, you will be able to:
- Use basic statistical concepts such as distributions, statistics such as range, mean, median, variance, standard deviation, and visualizations such as histograms and boxplots.
- Apply basic data wrangling in r statistical program, such as loading data, transforming data, getting basic summary statistics, aggregating data, etc.
- Apply t-test and anova analysis to healthcare data and interpret the results.
- Apply hypothesis testing and interpret the results.
- Communicate the results of their analysis to others in a simple language.
- By the end of this course, you will be able to:
- Use basic statistical concepts such as distributions, statistics such as range, mean, median, variance, standard deviation, and visualizations such as histograms and boxplots.
- Apply basic data wrangling in r statistical program, such as loading data, transforming data, getting basic summary statistics, aggregating data, etc.
- Apply t-test and anova analysis to healthcare data and interpret the results.
- Apply hypothesis testing and interpret the results.
- Communicate the results of their analysis to others in a simple language.
Syllabus
Course time commitment
2-4 hours per module (10-20 hours total)
Grading and certificate
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.
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Syllabus
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Activities
Review Biostatistics for the Biological and Health Sciences
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Biostatistics is foundational to this course. A review of this textbook will help you understand its key concepts.
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Biostatistics for the Biological and Health...
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-
Read chapters 1-3
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Complete the end of the chapter exercises for those chapters
Review basic data wrangling in R
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This course assumes a foundational understanding of basic data wrangling techniques in R. This dataset will help you quickly review these skills.
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Data Wrangling
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Complete the data wrangling tutorial
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Complete the practice exercises
Practice hypothesis testing
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Hypothesis testing is a critical skill in this course. This activity will strengthen your skill to perform hypothesis testing.
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Hypothesis Testing
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Read the materials on hypothesis testing
-
Complete the exercises on hypothesis testing
Two other activities
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Create visualizations using ggplot2
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This course requires you to be able to visualize data. This activity will provide practice in creating visualizations in R using ggplot2.
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Data Visualization
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-
Watch the video tutorials on creating visualizations with ggplot2
-
Complete the practice exercises
Share your learnings with others
Show steps
Translating statistical analysis results into plain language and sharing your findings helps reinforce learning.
Browse courses on
Communication
Show steps
-
Identify an audience and purpose for your communication
-
Write a short report or create a presentation to share your findings
-
Share your report or presentation with your audience
Review Biostatistics for the Biological and Health Sciences
Show steps
Biostatistics is foundational to this course. A review of this textbook will help you understand its key concepts.
View
Biostatistics for the Biological and Health...
on Amazon
Show steps
- Read chapters 1-3
- Complete the end of the chapter exercises for those chapters
Review basic data wrangling in R
Show steps
This course assumes a foundational understanding of basic data wrangling techniques in R. This dataset will help you quickly review these skills.
Browse courses on
Data Wrangling
Show steps
- Complete the data wrangling tutorial
- Complete the practice exercises
Practice hypothesis testing
Show steps
Hypothesis testing is a critical skill in this course. This activity will strengthen your skill to perform hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
- Read the materials on hypothesis testing
- Complete the exercises on hypothesis testing
Create visualizations using ggplot2
Show steps
This course requires you to be able to visualize data. This activity will provide practice in creating visualizations in R using ggplot2.
Browse courses on
Data Visualization
Show steps
- Watch the video tutorials on creating visualizations with ggplot2
- Complete the practice exercises
Share your learnings with others
Show steps
Translating statistical analysis results into plain language and sharing your findings helps reinforce learning.
Browse courses on
Communication
Show steps
- Identify an audience and purpose for your communication
- Write a short report or create a presentation to share your findings
- Share your report or presentation with your audience
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