We may earn an affiliate commission when you visit our partners.
Ronald Rogers,
Katie Kormanik,
and
Sean Laraway
Take Udacity's Introduction to Inferential Statistics and learn how to test your hypotheses and make predictions based on statistical results drawn from data! Learn online with Udacity.
Register for this course and see more details by visiting:
OpenCourser.com/course/8ikiwt/udacity
Here's a deal for you
Save money when you learn with a deal that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
OPENCOURSER
What's inside
Syllabus
Introduction and Lesson 7 Review
Estimation
Problem Set 8
Hypothesis Testing
Read more
Syllabus
Introduction and Lesson 7 Review
Estimation
Problem Set 8
Hypothesis Testing
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Explores core concepts in fundamental statistics, like hypothesis testing and prediction
Taught by Ronald Rogers, Katie Kormanik, and Sean Laraway, all known instructors
Develops inferential statistic skills, which are a core skill in many research fields
Covers essential inferential statistics topics, including estimation, hypothesis testing, and ANOVA
Incorporates problem sets, providing hands-on practice in applying statistical methods
Teaches statistical concepts through a blend of videos, readings, and discussions
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Reviews summary
Solid theoretical foundation in inferential statistics
According to learners, this course provides a strong foundation in inferential statistics. Reviewers often highlight the clear explanations of core concepts, making it accessible for beginners. The problem sets are frequently cited as challenging but helpful, effectively reinforcing learning. However, some students note a heavy theoretical focus, wishing for more real-world examples or guidance on practical application using software like R or Python. A few reviewers also mentioned the pacing felt uneven, particularly in later topics, and that some problem sets could be confusing or require external resources. Learners should be prepared for a significant amount of math.
Students should be prepared for a lot of math.
"Need to be prepared for a lot of math."
"The assignments were purely mathematical formulas..."
Assignments effectively reinforce concepts but are tough.
"...the problem sets were challenging but helpful. I feel like I have a good foundation now."
"Decent coverage of topics. The problem sets were key to understanding, though some were quite hard."
"Great course! Covered a lot of ground clearly and effectively. The problem sets really cemented the knowledge."
"The problem sets were challenging but fair."
"The content is okay, but the problem sets were sometimes confusing..."
"Loved this course! Great lectures and challenging, rewarding problems."
Concepts are explained clearly, accessible for beginners.
"Excelente curso, claro, didático e com boa profundidade dentro do proposto."
"The lectures were clear and the problem sets were challenging but helpful."
"Very well explained, especially the concepts of hypothesis testing and confidence intervals."
"Perfect course for building a foundation in stats. The instructors were clear and the material was presented logically."
"Fantastic overview. Cleared up many concepts I struggled with before."
"Clear explanations for the most part."
May require external resources for deeper understanding.
"I needed to supplement with other resources."
"It's an alright introduction, but you will definitely need other resources to fully grasp the concepts and their application."
"The problem sets sometimes introduced concepts not fully covered in lectures."
Early lessons slow, later topics can feel rushed.
"Some parts felt a bit rushed, particularly ANOVA and Regression..."
"Pacing was a bit uneven. Early parts were slow, later parts felt rushed."
"...it picked up pace and covered the key inferential methods well."
Strong on concepts, less on practical software use.
"Too theoretical and not practical enough. The assignments were purely mathematical formulas without showing how to apply them with tools like R or Python. Disappointed."
"Solid theoretical foundation provided. Could benefit from more hands-on application or software use examples."
"It's an alright introduction... wish there were more real-world examples..."
"Good for getting the theoretical basics, but don't expect to learn how to run these tests in software."
"Not enough practical examples."
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 Intro to Inferential Statistics with these
activities:
Review Basic Statistical Principles
Show steps
Brushing up on basic statistical concepts that have not been used in a while will reduce time spent looking up these concepts during the course.
Browse courses on
Probability
Show steps
-
Review a probability and statistics textbook or online resources.
-
Solve practice problems related to basic statistical concepts.
Create a Comprehensive Course Resource Folder
Show steps
Organizing and maintaining a central repository of course materials enhances accessibility and promotes regular review, contributing to retention and understanding.
Show steps
-
Gather all relevant notes, slides, assignments, and supplementary materials.
-
Organize and categorize materials in a structured and accessible manner.
Review Hypothesis Testing Concepts
Show steps
Reviewing hypothesis testing concepts will help you build a strong foundation for this course.
Browse courses on
Hypothesis Testing
Show steps
-
Review the definition and purpose of hypothesis testing.
-
Go over the steps involved in hypothesis testing.
-
Practice identifying the null and alternative hypotheses.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Review Modern Mathematical Statistics with Applications
Show steps
This book provides a comprehensive overview of statistical principles, techniques, and applications, reinforcing the concepts covered in the course.
View
Modern Mathematical Statistics with...
on Amazon
Show steps
-
Read the assigned chapters and take notes on key concepts.
-
Solve practice problems and exercises to test understanding.
Connect with Experienced Statisticians
Show steps
Seeking guidance from experienced professionals provides invaluable insights, support, and networking opportunities, enhancing the learning experience.
Show steps
-
Identify and reach out to potential mentors in academia or industry.
-
Schedule regular meetings to discuss progress, seek advice, and explore career paths.
Discuss Hypothesis Testing with Peers
Show steps
Engaging in discussions with peers will allow you to share and exchange knowledge, as well as learn from different perspectives on hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
-
Find a study group or online forum dedicated to hypothesis testing.
-
Participate in discussions and ask questions.
-
Share your insights and help others understand the concepts.
Explore Online Tutorials on Hypothesis Testing
Show steps
Exploring online tutorials will provide you with additional resources and perspectives on hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
-
Search for online tutorials on hypothesis testing.
-
Identify reputable sources and resources.
-
Follow the instructions and complete the exercises provided in the tutorials.
Develop Statistical Notations Guide
Show steps
Creating a reference guide will improve understanding and ongoing application of statistical notations in different contexts.
Browse courses on
Statistical Notation
Show steps
-
Identify and make a list of notations used in statistical analysis.
-
Classify and categorize notations based on their types or usage.
-
Create clear and concise definitions or explanations for each notation.
Create a Hypothesis Testing Cheat Sheet
Show steps
Creating a cheat sheet will help you organize and retain key concepts in hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
-
Gather relevant information on hypothesis testing.
-
Organize the information into a concise and structured format.
-
Include formulas, definitions, and key steps in the cheat sheet.
Peer-led Study Group
Show steps
Working regularly with peers provides opportunities to discuss concepts, clarify doubts, and reinforce learning through active engagement and collaborative problem-solving.
Show steps
-
Establish a consistent meeting time and dedicated study space.
-
Divide responsibilities for preparing topics for each session.
-
Facilitate discussions, share perspectives, and engage in problem-solving exercises.
Solve Hypothesis Testing Practice Problems
Show steps
Solving practice problems will enhance your understanding and proficiency in hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
-
Find practice problems on hypothesis testing.
-
Attempt to solve the problems on your own.
-
Check your solutions against provided answer keys or consult online resources for guidance.
Develop a Statistical Consulting Proposal
Show steps
Working on a comprehensive proposal simulates real-world consulting scenarios, enhancing communication, problem-solving, and presentation skills.
Browse courses on
Data Analysis
Show steps
-
Identify a specific research question or business problem.
-
Develop a plan for data analysis and statistical modeling.
-
Create a clear and well-organized proposal outlining the approach, methodology, and expected outcomes.
Solve Applied Statistical Problems
Show steps
Solving real-world statistical problems will reinforce understanding and hone problem-solving skills, improving the ability to interpret and apply statistical results.
Browse courses on
Hypothesis Testing
Show steps
-
Find or generate datasets that provide context for real-world problems.
-
Apply appropriate statistical techniques to analyze data and test hypotheses.
-
Interpret and draw meaningful conclusions based on the statistical results.
Participate in Statistical Hackathons
Show steps
Engaging in competitions provides an immersive and challenging environment to apply statistical skills, fostering creativity and problem-solving abilities in a real-world context.
Browse courses on
Data Analysis
Show steps
-
Identify and register for statistical hackathons relevant to interests.
-
Assemble a team with complementary skills.
-
Analyze data, develop models, and present findings in a clear and engaging manner.
Review Basic Statistical Principles
Show steps
Brushing up on basic statistical concepts that have not been used in a while will reduce time spent looking up these concepts during the course.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Review a probability and statistics textbook or online resources.
- Solve practice problems related to basic statistical concepts.
Create a Comprehensive Course Resource Folder
Show steps
Organizing and maintaining a central repository of course materials enhances accessibility and promotes regular review, contributing to retention and understanding.
Show steps
Show steps
Show steps
- Gather all relevant notes, slides, assignments, and supplementary materials.
- Organize and categorize materials in a structured and accessible manner.
Review Hypothesis Testing Concepts
Show steps
Reviewing hypothesis testing concepts will help you build a strong foundation for this course.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Review the definition and purpose of hypothesis testing.
- Go over the steps involved in hypothesis testing.
- Practice identifying the null and alternative hypotheses.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Review Modern Mathematical Statistics with Applications
Show steps
This book provides a comprehensive overview of statistical principles, techniques, and applications, reinforcing the concepts covered in the course.
View
Modern Mathematical Statistics with...
on Amazon
Show steps
Show steps
Show steps
- Read the assigned chapters and take notes on key concepts.
- Solve practice problems and exercises to test understanding.
Connect with Experienced Statisticians
Show steps
Seeking guidance from experienced professionals provides invaluable insights, support, and networking opportunities, enhancing the learning experience.
Show steps
Show steps
Show steps
- Identify and reach out to potential mentors in academia or industry.
- Schedule regular meetings to discuss progress, seek advice, and explore career paths.
Discuss Hypothesis Testing with Peers
Show steps
Engaging in discussions with peers will allow you to share and exchange knowledge, as well as learn from different perspectives on hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Find a study group or online forum dedicated to hypothesis testing.
- Participate in discussions and ask questions.
- Share your insights and help others understand the concepts.
Explore Online Tutorials on Hypothesis Testing
Show steps
Exploring online tutorials will provide you with additional resources and perspectives on hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Search for online tutorials on hypothesis testing.
- Identify reputable sources and resources.
- Follow the instructions and complete the exercises provided in the tutorials.
Develop Statistical Notations Guide
Show steps
Creating a reference guide will improve understanding and ongoing application of statistical notations in different contexts.
Browse courses on
Statistical Notation
Show steps
Show steps
Show steps
- Identify and make a list of notations used in statistical analysis.
- Classify and categorize notations based on their types or usage.
- Create clear and concise definitions or explanations for each notation.
Create a Hypothesis Testing Cheat Sheet
Show steps
Creating a cheat sheet will help you organize and retain key concepts in hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Gather relevant information on hypothesis testing.
- Organize the information into a concise and structured format.
- Include formulas, definitions, and key steps in the cheat sheet.
Peer-led Study Group
Show steps
Working regularly with peers provides opportunities to discuss concepts, clarify doubts, and reinforce learning through active engagement and collaborative problem-solving.
Show steps
Show steps
Show steps
- Establish a consistent meeting time and dedicated study space.
- Divide responsibilities for preparing topics for each session.
- Facilitate discussions, share perspectives, and engage in problem-solving exercises.
Solve Hypothesis Testing Practice Problems
Show steps
Solving practice problems will enhance your understanding and proficiency in hypothesis testing.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Find practice problems on hypothesis testing.
- Attempt to solve the problems on your own.
- Check your solutions against provided answer keys or consult online resources for guidance.
Develop a Statistical Consulting Proposal
Show steps
Working on a comprehensive proposal simulates real-world consulting scenarios, enhancing communication, problem-solving, and presentation skills.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify a specific research question or business problem.
- Develop a plan for data analysis and statistical modeling.
- Create a clear and well-organized proposal outlining the approach, methodology, and expected outcomes.
Solve Applied Statistical Problems
Show steps
Solving real-world statistical problems will reinforce understanding and hone problem-solving skills, improving the ability to interpret and apply statistical results.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Find or generate datasets that provide context for real-world problems.
- Apply appropriate statistical techniques to analyze data and test hypotheses.
- Interpret and draw meaningful conclusions based on the statistical results.
Participate in Statistical Hackathons
Show steps
Engaging in competitions provides an immersive and challenging environment to apply statistical skills, fostering creativity and problem-solving abilities in a real-world context.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify and register for statistical hackathons relevant to interests.
- Assemble a team with complementary skills.
- Analyze data, develop models, and present findings in a clear and engaging manner.
Career center
Learners who complete Intro to Inferential Statistics will develop knowledge and skills
that may be useful to these careers:
Statistician
Statistician
Statisticians use statistical methods to collect, analyze, and interpret data. This course can help Statisticians by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the data they are working with and make more informed decisions.
Data Scientist
Data Scientist
Data Scientists use statistical methods to analyze data and extract insights from it. This course can help Data Scientists by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the data they are working with and make more informed decisions about how to use it.
Data Analyst
Data Analyst
Data Analysts use statistical methods to analyze data and extract insights from it. This course can help Data Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the data they are working with and make more informed decisions.
Market Research Analyst
Market Research Analyst
Market Research Analysts collect, analyze, and interpret market data to help businesses make informed decisions. This course can help Market Research Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand their target market and develop effective marketing campaigns.
Financial Analyst
Financial Analyst
Financial Analysts use statistical methods to analyze financial data and make investment recommendations. This course can help Financial Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the financial data they are working with and make more informed investment decisions.
Business Analyst
Business Analyst
Business Analysts use statistical methods to analyze business data and make recommendations for improvement. This course can help Business Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the business data they are working with and make more informed recommendations for improvement.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use statistical methods to analyze and improve operations. This course can help Operations Research Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the operations they are working with and make more informed recommendations for improvement.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts use statistical methods to ensure that products and services meet quality standards. This course can help Quality Assurance Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the quality of the products and services they are working with and make more informed decisions about how to improve them.
Salesforce Analyst
Salesforce Analyst
Salesforce Analysts use statistical methods to analyze Salesforce data and make recommendations for improvement. This course can help Salesforce Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the Salesforce data they are working with and make more informed recommendations for improvement.
Marketing Analyst
Marketing Analyst
Marketing Analysts use statistical methods to analyze marketing data and make recommendations for improvement. This course can help Marketing Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the marketing data they are working with and make more informed recommendations for improvement.
Biostatistician
Biostatistician
Biostatisticians use statistical methods to analyze biological data. This course can help Biostatisticians by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the biological data they are working with and make more informed recommendations for research and treatment.
Clinical Research Associate
Clinical Research Associate
Clinical Research Associates use statistical methods to design and conduct clinical trials. This course can help Clinical Research Associates by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the clinical trials they are working on and make more informed decisions about how to design and conduct them.
Epidemiologist
Epidemiologist
Epidemiologists use statistical methods to study the distribution and patterns of health-related events. This course can help Epidemiologists by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the health-related events they are studying and make more informed recommendations for prevention and control.
Risk Analyst
Risk Analyst
Risk Analysts use statistical methods to analyze and manage risk. This course can help Risk Analysts by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the risks that businesses are facing and make more informed decisions about how to manage those risks.
Actuary
Actuary
Actuaries use statistical methods to assess risk. This course can help Actuaries by teaching them how to test hypotheses and make predictions based on statistical results drawn from data. This can help them to better understand the risks that businesses are facing and make more informed decisions about how to manage those risks.
For more career information including salaries, visit:
OpenCourser.com/course/8ikiwt/udacity
Reading list
We've selected ten 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
Intro to Inferential Statistics.
A comprehensive textbook that covers the theory and methods of statistical inference. It provides a solid foundation for understanding the concepts and techniques used in inferential statistics.
A practical guide to statistical methods that emphasizes the interpretation of data and the communication of results. It provides a good overview of the key concepts and methods used in inferential statistics.
A more advanced textbook that covers a wide range of statistical learning methods, including supervised and unsupervised learning. It provides a good overview of the latest developments in statistical inference.
An introduction to Bayesian data analysis, which powerful approach to statistical inference that allows for the incorporation of prior knowledge and uncertainty. It provides a good overview of the basic concepts and methods of Bayesian inference.
A practical guide to Bayesian data analysis using the Stan programming language. It provides a good overview of the key concepts and methods of Bayesian inference, and it is particularly useful for those who want to apply Bayesian methods to real-world problems.
Save
An open-source textbook that provides a comprehensive overview of statistical concepts and methods. It good resource for those who want to learn more about the theory and practice of statistics.
Save
A concise textbook that covers the core concepts and methods of statistical inference. It good resource for those who want to learn the basics of inferential statistics, and it is particularly useful for those who are interested in pursuing further study in statistics.
Save
A textbook that provides a rigorous introduction to the theory of probability and mathematical statistics. It good resource for those who want to learn the mathematical foundations of statistical inference.
Save
A textbook that provides a practical guide to data analysis. It good resource for those who want to learn how to use statistical methods to analyze data.
A textbook that provides a practical guide to statistical analysis using the R programming language. It good resource for those who want to learn how to use R to analyze data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8ikiwt/udacity
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
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 - 2025 OpenCourser