Course Summary
This course covers the basics of summary statistics, including measures of central tendency, measures of variability, and hypothesis testing.Key Learning Points
- Learn how to calculate and interpret measures of central tendency and variability
- Understand the basics of hypothesis testing and how to apply it to real-world scenarios
- Gain practical skills in data analysis using statistical software
Related Topics for further study
Learning Outcomes
- Ability to calculate and interpret measures of central tendency and variability
- Understanding of hypothesis testing and its application
- Hands-on experience with statistical software
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of algebra
- Familiarity with statistical software (recommended)
Course Difficulty Level
BeginnerCourse Format
- Online
- Self-paced
Similar Courses
- Introduction to Probability and Statistics
- Applied Data Science with Python
Related Education Paths
Related Books
Description
Biostatistics is the application of statistical reasoning to the life sciences, and it is the key to unlocking the data gathered by researchers and the evidence presented in the scientific literature. In this course, we'll focus on the use of statistical measurement methods within the world of public health research. Along the way, you'll be introduced to a variety of methods and measures, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include summary measures, visual displays, continuous data, sample size, the normal distribution, binary data, the element of time, and the Kaplan-Meir curve.
Knowledge
- Calculate continuous data measures
- Interpret data visualizations
- Analyze binary data
- Analyze time to event data
Outline
- The Role of Statistics in Public Health Research
- Welcome
- Introduction and Overview
- Samples Versus Population
- Considerations with Regard to Study Design
- Data Types and Summarization
- Additional Examples
- Continuous Data Measures
- Introduction
- Useful Summary Statistics
- Visual Displays
- The Role of Sample Size on Sample Based Estimates
- Comparing Distributions of Continuous Data
- Additional Examples
- Summative Quiz Solutions
- Practice: Continuous Data Measures
- Continuous Data Measures
- The Normal Distribution
- Introduction
- The Standard Normal Distribution Defined
- Applying the Principles of the Normal Distribution to Sample Data to Estimate Characteristics of Population Data
- What Happens When We Apply the Properties of the Normal Distribution to Data Not Approximately Normal: A Warning
- Additional Examples
- Practice: The Normal Distribution
- The Normal Distribution
- Binary Data
- Introduction
- Binary Data: Definition and Summarization (Binomial Distribution, P-Hat, SD)
- Comparing Distributions of Binary Data: Risk Difference and Relative Risk
- Comparing Distributions of Binary Data: Odds Ratios
- A Brief Note About Ratios (Will Also Be Revisited Later in the Course)
- Additional Examples
- Summative Quiz Solutions
- Practice: Binary Data
- Binary Data
- Dealing with the Element of Time
- Introduction
- Time to Event Data: Definition (Censoring) and Numerical Summary Measures (Incidence Rates)
- Numerically Comparing Groups on Time to Event Outcomes
- Summarizing Time-to-Event Data, Graphically
- Graphically Comparing Groups on Time to Event Outcomes
- Additional Examples
- Dealing with Elements of Time
- Course Project
- Biostatistical Consulting Project
- Course Project Quiz
Summary of User Reviews
Read reviews of Summary Statistics course on Coursera. Students have praised the course for its clear explanations of statistical concepts and useful examples. The course has received an overall high rating from users.Key Aspect Users Liked About This Course
Many users thought the course did an excellent job of breaking down complex statistical concepts into easy-to-understand examples.Pros from User Reviews
- Clear explanations of statistical concepts
- Useful examples that help students understand complex topics
- Well-structured course that is easy to follow
Cons from User Reviews
- Some students found the pace of the course too slow
- The course doesn't cover more advanced statistical topics
- Some students wished there were more opportunities for hands-on practice
John McGready, PhD, MS
4.8 Raiting
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