Course Summary
This course focuses on applying statistical concepts to real-world projects. Students will learn how to formulate a statistical question, collect and analyze data, and communicate their findings through written reports and presentations.Key Learning Points
- Develop skills in statistical analysis and data visualization
- Learn how to apply statistics to real-world projects
- Gain experience in communicating statistical findings through written reports and presentations
Related Topics for further study
Learning Outcomes
- Ability to formulate statistical questions and design experiments
- Skills in data analysis and visualization
- Experience in communicating statistical findings through written reports and presentations
Prerequisites or good to have knowledge before taking this course
- Basic understanding of statistics
- Familiarity with a statistics software package such as R or SPSS
Course Difficulty Level
IntermediateCourse Format
- Self-paced
- Online
- Project-based
Similar Courses
- Data Analysis and Statistical Inference
- Applied Data Science with Python
- Data Science Math Skills
Related Education Paths
Notable People in This Field
- Nate Silver
Related Books
Description
The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. A large and complex dataset will be provided to learners and the analysis will require the application of a variety of methods and techniques introduced in the previous courses, including exploratory data analysis through data visualization and numerical summaries, statistical inference, and modeling as well as interpretations of these results in the context of the data and the research question. The analysis will implement both frequentist and Bayesian techniques and discuss in context of the data how these two approaches are similar and different, and what these differences mean for conclusions that can be drawn from the data.
Outline
- About the Capstone Project
- Welcome to the Statistics with R Capstone course
- Introduction to the Capstone Course
- Tips for Success and Suggested Work Pace
- What to Do This Week
- Learning Objectives for Courses 1-4
- Exploratory Data Analysis (EDA)
- What to Do This Week
- EDA Quiz - Assignment Guide
- EDA Quiz
- EDA and Basic Model Selection - Submission
- What to Do This Week
- EDA and Basic Model Selection - Evaluation
- What to Do This Week
- Model Selection and Diagnostics
- What to Do This Week
- Model Selection and Diagnostics Quiz - Assignment Guide
- Model Selection and Diagnostics Quiz
- Out of Sample Prediction
- What do Do This Week
- Out of Sample Prediction Quiz - Assignment Guide
- Out of Sample Prediction Quiz
- Final Data Analysis - Submission
- What to Do This Week
- Final Data Analysis - Evaluation
- What to Do This Week
Summary of User Reviews
The Statistics Project course on Coursera has received positive reviews from users. The course provides a comprehensive understanding of statistics and its various applications. Many users appreciated the interactive nature of the course, which allowed them to apply their learning to real-world scenarios.Key Aspect Users Liked About This Course
The interactive nature of the course, allowing users to apply their learning to real-world scenarios.Pros from User Reviews
- Comprehensive understanding of statistics and its various applications
- Interactive course design
- Real-world applications
- Engaging instructors
- Well-structured content
Cons from User Reviews
- Content may be too basic for advanced learners
- Some technical issues with the platform
- Limited opportunities for interaction with instructors
- Some users found the course pace to be too slow
- Some users found the course too theoretical
Merlise A Clyde
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