We may earn an affiliate commission when you visit our partners.
Sebastian Thrun
and
Josh Bernhard
This capstone project gives you hands-on experience with A/B testing, a key practical application of statistical analysis. Students will produce a detailed technical analysis in a Jupyter Notebook, along with a non-technical slide deck presentation designed to effectively communicate their findings and recommendations to business stakeholders.
Register for this course and see more details by visiting:
OpenCourser.com/course/gn4q8q/statistics
Here's a deal for you
We found an offer that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
UDACITY40
What's inside
Syllabus
You will be working to understand the results of an A/B test run by an e-commerce website. Your goal is to work through to help the company understand if they should implement the new page design.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops practical skills in A/B testing, which is a key statistical analysis tool in industry
Instructed by Sebastian Thrun and Josh Bernhard, professors recognized for their work in statistics
Utilized hands-on Jupyter Notebooks and presentations, which help learners build practical proficiencies
Save this course
Save Statistics for Data Analysis - Capstone Project to your list so you can find it easily later:
Save
Save
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 Statistics for Data Analysis - Capstone Project with these
activities:
Organize and review course materials
Show steps
Regularly review and organize course materials to enhance understanding and retention.
Show steps
-
Gather lecture notes, assignments, and other resources
-
Review materials and identify key concepts
-
Summarize and condense information for easy reference
Follow tutorials on A/B testing best practices
Show steps
Follow tutorials and read articles to learn best practices for conducting A/B tests.
Browse courses on
A/B Testing
Show steps
-
Identify reputable sources
-
Follow tutorials and take notes
-
Apply the best practices to your own projects
Create a visual representation of A/B test results
Show steps
Create a visual representation of the A/B test results to better understand the impact of the changes.
Browse courses on
A/B Testing
Show steps
-
Select a data visualization tool
-
Gather and clean the data
-
Create the visualization
Four other activities
Expand to see all activities and additional details
Show all seven activities
Discuss A/B testing strategies with peers
Show steps
Engage in discussions with peers to exchange ideas and learn from different perspectives on A/B testing.
Browse courses on
A/B Testing
Show steps
-
Join a study group or online forum
-
Participate in discussions and share insights
-
Seek feedback and constructive criticism
Develop a proposal for implementing A/B testing on a website
Show steps
Create a detailed proposal outlining the benefits, methods, and potential impact of implementing A/B testing on a specific website.
Browse courses on
A/B Testing
Show steps
-
Define the problem and goals
-
Research and analyze the website
-
Design the A/B test
-
Write the proposal
Contribute to an open-source A/B testing project
Show steps
Gain hands-on experience with A/B testing by contributing to an open-source project and collaborating with a community of developers.
Browse courses on
A/B Testing
Show steps
-
Identify an open-source A/B testing project
-
Join the project community and learn about the codebase
-
Make code contributions and participate in discussions
Participate in an A/B testing competition
Show steps
Challenge yourself and test your skills in A/B testing by participating in a competition and showcasing your abilities to solve real-world problems.
Browse courses on
A/B Testing
Show steps
-
Identify and research A/B testing competitions
-
Form a team or work individually
-
Develop and implement an A/B testing strategy
-
Analyze results and submit your findings
Organize and review course materials
Show steps
Regularly review and organize course materials to enhance understanding and retention.
Show steps
Show steps
Show steps
- Gather lecture notes, assignments, and other resources
- Review materials and identify key concepts
- Summarize and condense information for easy reference
Follow tutorials on A/B testing best practices
Show steps
Follow tutorials and read articles to learn best practices for conducting A/B tests.
Browse courses on
A/B Testing
Show steps
Show steps
Show steps
- Identify reputable sources
- Follow tutorials and take notes
- Apply the best practices to your own projects
Create a visual representation of A/B test results
Show steps
Create a visual representation of the A/B test results to better understand the impact of the changes.
Browse courses on
A/B Testing
Show steps
Show steps
Show steps
- Select a data visualization tool
- Gather and clean the data
- Create the visualization
Four other activities
Expand to see all activities and additional details
Show all seven activities
Discuss A/B testing strategies with peers
Show steps
Engage in discussions with peers to exchange ideas and learn from different perspectives on A/B testing.
Browse courses on
A/B Testing
Show steps
Show steps
Show steps
- Join a study group or online forum
- Participate in discussions and share insights
- Seek feedback and constructive criticism
Develop a proposal for implementing A/B testing on a website
Show steps
Create a detailed proposal outlining the benefits, methods, and potential impact of implementing A/B testing on a specific website.
Browse courses on
A/B Testing
Show steps
Show steps
Show steps
- Define the problem and goals
- Research and analyze the website
- Design the A/B test
- Write the proposal
Contribute to an open-source A/B testing project
Show steps
Gain hands-on experience with A/B testing by contributing to an open-source project and collaborating with a community of developers.
Browse courses on
A/B Testing
Show steps
Show steps
Show steps
- Identify an open-source A/B testing project
- Join the project community and learn about the codebase
- Make code contributions and participate in discussions
Participate in an A/B testing competition
Show steps
Challenge yourself and test your skills in A/B testing by participating in a competition and showcasing your abilities to solve real-world problems.
Browse courses on
A/B Testing
Show steps
Show steps
Show steps
- Identify and research A/B testing competitions
- Form a team or work individually
- Develop and implement an A/B testing strategy
- Analyze results and submit your findings
Career center
Learners who complete Statistics for Data Analysis - Capstone Project will develop knowledge and skills
that may be useful to these careers:
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to improve the efficiency of business processes. They work in a variety of industries, including manufacturing, transportation, and healthcare. This course may be useful as it will help you build a strong foundation in statistical analysis, which is a critical skill for Operations Research Analysts. You'll also gain experience with A/B testing, which is a valuable tool for understanding how different changes to a business process can impact its efficiency.
Statistician
Statistician
Statisticians use data to solve problems and make informed decisions. They work in a variety of industries, including healthcare, education, and government. This course may be useful as it will help you build a strong foundation in statistical analysis, which is essential for Statisticians in all industries. You'll also gain experience with A/B testing, which is a valuable tool for understanding how different changes to a product or service can impact its success.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. They work in a variety of industries, including technology, healthcare, and finance. This course may be useful as it will help you build a strong foundation in statistical analysis, which is a critical skill for Machine Learning Engineers. You'll also gain experience with A/B testing, which is a valuable tool for understanding how different changes to a machine learning model can impact its performance.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. They work in a variety of industries, including banking, insurance, and asset management. This course may be useful as it will help you build a strong foundation in statistical analysis, which is a critical skill for Quantitative Analysts. You'll also gain experience with A/B testing, which is a valuable tool for understanding how different changes to a financial product or service can impact its risk and return.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess risk. They work in a variety of industries, including insurance, pensions, and healthcare. This course may be useful as it will help you build a strong foundation in statistical analysis, which is a critical skill for Actuaries. You'll also gain experience with A/B testing, which is a valuable tool for understanding how different changes to an insurance policy or pension plan can impact its risk.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks. They work in a variety of industries, including banking, insurance, and healthcare. This course may be useful as it will help you build a strong foundation in statistical analysis, which is a critical skill for Risk Managers. You'll also gain experience with A/B testing, which is a valuable tool for understanding how different changes to a risk management strategy can impact its effectiveness.
Data Scientist
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to solve complex problems. They work in a variety of industries, including healthcare, finance, and technology. This course may be useful as it will help you build a strong foundation in statistical analysis, which is a critical skill for Data Scientists. You'll also gain experience with A/B testing, which is a valuable tool for understanding how users respond to different products and services.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for the development and implementation of marketing campaigns. They work in a variety of industries, including technology, healthcare, and consumer goods. This course may be useful as it will give you hands-on experience with A/B testing, a skill that is essential for Marketing Managers in all industries. You'll learn how to use data to make informed decisions about marketing campaign design and implementation.
Market Researcher
Market Researcher
Market Researchers help their organizations understand their target market by conducting surveys, focus groups, and other research methods. They use this information to develop marketing campaigns that are more likely to be successful. This course may be useful as it will help you build a foundation in statistical analysis, which is essential for Market Researchers in all industries. You'll also gain experience with A/B testing, which is a valuable skill for understanding how customers respond to different marketing campaigns.
Business Analyst
Business Analyst
Business Analysts work as a bridge between the IT and business divisions of their companies. They analyze data to identify areas for improvement and provide solutions to business challenges. This course may be useful as it will give you hands-on experience with A/B testing, a skill that is essential for Business Analysts. You'll learn how to use data to make recommendations and improve business outcomes.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work in a variety of industries, including technology, healthcare, and finance. This course may be useful as it will give you hands-on experience with A/B testing, a skill that can be valuable for Software Engineers working on web development projects. You'll learn how to use data to make informed decisions about software design and development.
Data Analyst
Data Analyst
Data Analysts may work in numerous fields such as healthcare, education, and finance. They help their organizations find new insights by reviewing past data and performing statistical analysis. This course may be useful as it will help you build a foundation in statistical analysis, which is essential for Data Analysts in all industries. By taking it, you'll gain experience with the tools and techniques that Data Analysts use every day.
Financial Analyst
Financial Analyst
Financial Analysts use data to make recommendations about investments. They work in a variety of industries, including banking, insurance, and asset management. This course may be useful as it will help you build a foundation in statistical analysis, which is essential for Financial Analysts in all industries. You'll also gain experience with A/B testing, which is a valuable tool for understanding how investors respond to different financial products and services.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products and services. They work in a variety of industries, including technology, healthcare, and consumer goods. This course may be useful as it will give you hands-on experience with A/B testing, a skill that is essential for Product Managers in all industries. You'll learn how to use data to make informed decisions about product design and development.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure that is used to store and process data. They work in a variety of industries, including technology, healthcare, and finance. This course may be useful as it will give you hands-on experience with A/B testing, a skill that can be valuable for Data Engineers working on projects that involve large datasets. You'll learn how to use data to make informed decisions about data storage and processing.
For more career information including salaries, visit:
OpenCourser.com/course/gn4q8q/statistics
Reading list
We've selected seven 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
Statistics for Data Analysis - Capstone Project.
An authoritative guide to statistical methods used in A/B testing, with emphasis on practical applications and code examples. It's highly recommended for those who need a deeper understanding of the statistical side of A/B testing.
Offers a comprehensive overview of data science and analytics, including topics such as data mining, data visualization, and machine learning. It provides a solid foundation for understanding A/B testing within the broader context of data analysis.
Save
A highly accessible introduction to statistics, written for a non-technical audience. It helps build intuition for statistical concepts and provides a strong foundation for understanding the statistical concepts used in A/B testing.
An influential book in the realm of entrepreneurship and innovation, it promotes the concept of iterative development and customer validation. While not specifically about A/B testing, it emphasizes the importance of experimentation and data-driven decision-making, principles that are fundamental to A/B testing.
A classic textbook on experimental design and statistics, covering a wide range of topics including A/B testing. It emphasizes the importance of statistical thinking and provides a rigorous foundation for understanding the design and analysis of experiments.
A comprehensive treatment of causal inference, including methods for identifying and controlling for confounding factors. While not essential for A/B testing, it provides a deeper understanding of causal relationships and can help inform the design and interpretation of A/B tests.
A comprehensive introduction to regression analysis, with coverage of a variety of models and techniques. While regression is not a primary focus of A/B testing, understanding regression concepts can enhance the understanding of statistical significance and effect size in A/B testing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/gn4q8q/statistics
Share
Similar courses
Here are nine courses similar to
Statistics for Data Analysis - Capstone Project.
Trading - Fundamentals of Technical Analysis
OpenCourser.com/course/w8zg3l/trading
Trading - Fundamentals of Technical Analysis
Quantitative Technical Analysis
OpenCourser.com/course/eloy6i/quantitative
Quantitative Technical Analysis
Technical Analysis and the Skill of Day Trading
OpenCourser.com/course/rs3tht/technical
Technical Analysis and the Skill of Day Trading
Communicating Model Results and Data Insights for Data Scientists
OpenCourser.com/course/8qqtmv/communicating
Communicating Model Results and Data Insights for Data...
Complex Problem Structuring: a Socio-Technical Perspective
OpenCourser.com/course/90j49e/complex
Complex Problem Structuring: a Socio-Technical Perspective
Project Valuation and the Capital Budgeting Process
OpenCourser.com/course/i99iq2/project
Project Valuation and the Capital Budgeting Process
The Technical Business Analyst
OpenCourser.com/course/vdbe87/the
The Technical Business Analyst
Business Analysis: The Skills and Competencies of Effective Business Analysts
OpenCourser.com/course/wuw699/business
Business Analysis: The Skills and Competencies of...
Stages of Incident Response
OpenCourser.com/course/56jq3r/stages
Stages of Incident Response
Time
133920 hours
Level
Introductory
Via
Udacity
Instructors
Sebastian Thrun
Josh Bernhard
Language
English
Good to know
Develops practical skills in A/B testing, which is a key statistical analysis tool in industry
Instructed by Sebastian Thrun and Josh Bernhard, professors recognized for their work in statistics
Utilized hands-on Jupyter Notebooks and presentations, which help learners build practical proficiencies
Our mission
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.
Affiliate disclosure
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.
© 2016 - 2024 OpenCourser