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Experimentation
Sebastian Thrun
and
Josh Bernhard
Sebastian Thrun
and
Josh Bernhard
Experimentation is one of the most important topics in all of statistics because it tells us whether our conclusions are statistically significant. In this course, you will learn about the fundamental role statistics plays in experimentation as well as how to...
Read more
Experimentation is one of the most important topics in all of statistics because it tells us whether our conclusions are statistically significant. In this course, you will learn about the fundamental role statistics plays in experimentation as well as how to...
Read more
Experimentation is one of the most important topics in all of statistics because it tells us whether our conclusions are statistically significant. In this course, you will learn about the fundamental role statistics plays in experimentation as well as how to implement statistical concepts in Python.
Register for this course and see more details by visiting:
OpenCourser.com/course/lrgrhl/experimentatio
What's inside
Syllabus
In this lesson, we begin the course by meeting the instructors and giving a quick introduction to experimentation.
In this lesson, you'll learn the mathematics behind moving from a coin flip to a normal distribution.
Read more
Syllabus
In this lesson, we begin the course by meeting the instructors and giving a quick introduction to experimentation.
In this lesson, you'll learn the mathematics behind moving from a coin flip to a normal distribution.
Read more
In this lesson, you'll learn all about the underpinning of confidence intervals and hypothesis testing - sampling distributions.
In this lesson, you'll learn how to use sampling distributions and bootstrapping to create a confidence interval for any parameter of interest.
In this lesson, you'll learn the necessary skills to create and analyze the results of hypothesis testing.
In this lesson, you'll work through a case study of how A/B testing works in the context of website metrics for an online education company.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational principles and advanced concepts of experimentation in statistics
Emphasizes the practical application of statistical concepts through hands-on Python coding exercises
Provides a comprehensive understanding of confidence intervals and hypothesis testing
Features real-world case studies to demonstrate the relevance of statistical techniques
Taught by experienced instructors with a strong reputation in the field of statistics
Assumes some prior knowledge of statistics, making it suitable for intermediate-level learners
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Save Experimentation to your list so you can find it easily later:
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Activities
Coming soon
We're preparing activities for
Experimentation.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Experimentation will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Data Scientists who need to be able to analyze data and draw valid conclusions.
Statistician
Statistician
A Statistician designs, conducts, and analyzes statistical surveys and experiments. They use mathematical and statistical techniques to analyze data and draw conclusions.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Statisticians who need to be able to design and analyze experiments and draw valid conclusions from data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models and algorithms to solve complex problems. They use statistical techniques to analyze data and build models that can make predictions or decisions.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Machine Learning Engineers who need to be able to design and analyze experiments and draw valid conclusions from data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve complex problems in business and industry. They use statistical techniques to analyze data and identify trends and patterns.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Operations Research Analysts who need to be able to analyze data and draw valid conclusions.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. They use statistical techniques to analyze data and identify trends and patterns.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Quantitative Analysts who need to be able to analyze data and draw valid conclusions.
Market Research Analyst
Market Research Analyst
Market Research Analysts conduct surveys and experiments to collect data about consumer behavior and preferences. They use statistical techniques to analyze data and identify trends and patterns.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Market Research Analysts who need to be able to analyze data and draw valid conclusions.
Clinical Research Associate
Clinical Research Associate
CRAs monitor clinical trials to ensure that they are conducted according to protocol and that the data is collected and managed according to Good Clinical Practice (GCP) guidelines. They use statistical techniques to analyze data and identify trends and patterns.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for CRAs who need to be able to analyze data and draw valid conclusions.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to the design, conduct, and analysis of research studies in the biomedical sciences. They use statistical techniques to analyze data and draw conclusions about the effectiveness and safety of medical treatments.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Biostatisticians who need to be able to analyze data and draw valid conclusions.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and patterns of disease and injury in populations. They use statistical techniques to analyze data and identify risk factors and trends.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Epidemiologists who need to be able to analyze data and draw valid conclusions.
Sales Analyst
Sales Analyst
Sales Analysts use statistical techniques to analyze sales data and identify trends and patterns. They use this information to make recommendations to sales teams on how to improve their performance.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Sales Analysts who need to be able to analyze data and draw valid conclusions.
Business Analyst
Business Analyst
Business Analysts use statistical techniques to analyze data and identify trends and patterns. They use this information to make recommendations to businesses on how to improve their operations and decision-making.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Business Analysts who need to be able to analyze data and draw valid conclusions.
Financial Analyst
Financial Analyst
Financial Analysts use statistical techniques to analyze financial data and make investment recommendations. They use statistical techniques to analyze data and identify trends and patterns.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Financial Analysts who need to be able to analyze data and draw valid conclusions.
Risk Analyst
Risk Analyst
Risk Analysts use statistical techniques to analyze data and identify risks. They use this information to make recommendations to businesses on how to manage their risks.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Risk Analysts who need to be able to analyze data and draw valid conclusions.
Insurance Actuary
Insurance Actuary
Insurance Actuaries use statistical techniques to analyze data and assess risk. They use this information to set insurance rates and design insurance products.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Insurance Actuaries who need to be able to analyze data and draw valid conclusions.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists use statistical techniques to create visual representations of data. They use this information to communicate insights about data to businesses and stakeholders.
This course can help you build a strong foundation in statistical concepts, including sampling distributions, confidence intervals, and hypothesis testing. These skills are essential for Data Visualization Specialists who need to be able to analyze data and draw valid conclusions.
For more career information including salaries, visit:
OpenCourser.com/course/lrgrhl/experimentatio
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
Experimentation.
Classic text on the design of experiments. It provides a comprehensive overview of the principles and methods used in experimental design.
Comprehensive overview of causal inference. It covers a wide range of topics, from basic concepts to advanced techniques.
Save
Comprehensive overview of deep learning. It covers a wide range of topics, from basic concepts to advanced techniques.
Comprehensive overview of reinforcement learning. It covers a wide range of topics, from basic concepts to advanced techniques.
Save
Comprehensive overview of time series analysis. It covers a wide range of topics, from basic concepts to advanced techniques.
Comprehensive overview of Bayesian data analysis. It covers a wide range of topics, from basic concepts to advanced techniques.
Comprehensive overview of Bayesian statistics. It covers a wide range of topics, from basic concepts to advanced techniques.
Comprehensive overview of econometrics. It covers a wide range of topics, from basic concepts to advanced techniques.
Comprehensive overview of statistical learning methods. It covers a wide range of topics, from basic concepts to advanced techniques.
Provides a comprehensive overview of probability and statistics for engineers and scientists.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/lrgrhl/experimentatio
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Time
900 hours
Level
Introductory
Via
Udacity
Instructors
Sebastian Thrun
Josh Bernhard
Language
English
Good to know
Develops foundational principles and advanced concepts of experimentation in statistics
Emphasizes the practical application of statistical concepts through hands-on Python coding exercises
Provides a comprehensive understanding of confidence intervals and hypothesis testing
Features real-world case studies to demonstrate the relevance of statistical techniques
Taught by experienced instructors with a strong reputation in the field of statistics
Assumes some prior knowledge of statistics, making it suitable for intermediate-level learners
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