Hypotheses Testing in Econometrics from Coursera

In this course, you will learn why it is rational to use the parameters recovered under the Classical Linear Regression Model for hypothesis testing in uncertain contexts. You will:

– Develop your knowledge of the statistical properties of the OLS estimator as you see whether key assumptions work.

– Learn that the OLS estimator has some desirable statistical properties, which are the basis of an approach for hypothesis testing to aid rational decision making.

– Examine the concept of null hypothesis and alternative hypothesis, before exploring a statistic and a distribution under the null hypothesis, as well as a rule for deciding which hypothesis is more likely to hold true.

– Discover what happens to the decision-making framework if some assumptions of the CLRM are violated, as you explore diagnostic testing.

– Learn the steps involved to detect violations, the consequences upon the OLS estimator, and the techniques that must be adopted to address these problems.

Before starting this course, it is expected that you have an understanding of some basic statistics, including mean, variance, skewness and kurtosis. It is also recommended that you have completed and understood the previous course in this Specialisation: The Classical Linear Regression model.

By the end of this course, you will be able to:

– Explain what hypothesis testing is

– Explain why the OLS is a rational approach to hypothesis testing

– Perform hypothesis testing for single and multiple hypothesis

– Explain the idea of diagnostic testing

– Perform hypothesis testing for single and multiple hypothesis with R

– Identify and resolve problems raised by identification of parameters.

What's inside

Syllabus

Properties of the OLS Approach

This week we are going to look at the properties of the OLS approach as a basis for the hypothesis testing, focussing on linearity, unbiasedness, efficiency and consistency.

Hypothesis Testing

This week we shall be exploring hypothesis testing, looking at the t-test and the F-test, and considering the problems raised by hypothesis testing.

Diagnostic Testing I

This week we shall be discussing diagnostic testing as we look at non-linearity, violation of full rank and errors correlated with regressors.

Diagnostic Testing II

This week we will continue to look at diagnostic testing as we consider spherical errors, heteroscedasticity, autocorrelation, Stochastic Regressors, and the non-normality of errors.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops understanding of hypothesis testing, aiding rational decision making

Examines potential problems in hypothesis testing, enabling learners to identify and resolve them

Offers hands-on experience with R, a powerful tool for hypothesis testing

Taught by Dr. Leone Leonida, an expert in hypothesis testing

Presumes prior knowledge of basic statistics, ensuring a foundational understanding

Requires completion of the previous course in the specialization, potentially limiting accessibility for beginners

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 Hypotheses Testing in Econometrics with these activities:

Review the key concepts of hypothesis testing

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Recapping the key concepts of hypothesis testing will help you prepare for the course material.

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Review lecture notes or online resources on hypothesis testing.
Summarize the main concepts in your own words.
Answer practice questions to test your understanding.

Review the concepts of probability and statistics

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A solid foundation in probability and statistics is crucial for understanding hypothesis testing.

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Review lecture notes or textbooks on probability and statistics.
Work through practice problems to reinforce your understanding.
Seek clarification from your instructor or peers if needed.

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Discussing hypothesis testing with peers can enhance your understanding and identify areas where you need further clarification.

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Find or create a study group or discussion forum dedicated to hypothesis testing.
Participate in discussions, ask questions, and share your insights.
Review and respond to others' contributions.

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Follow online tutorials on hypothesis testing

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Guided tutorials provide step-by-step instructions and examples, which can be helpful for solidifying your understanding of hypothesis testing.

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Search for online tutorials on hypothesis testing.
Choose a tutorial that aligns with your learning style and level.
Follow the tutorial and complete the exercises.

Work through practice problems for hypothesis testing

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Practicing hypothesis testing problems will reinforce the key concepts and principles covered in the course.

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Review the course materials on hypothesis testing.
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Check your answers against the provided solutions.

Compile a collection of resources on hypothesis testing

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Search for online resources on hypothesis testing, including articles, tutorials, and videos.
Bookmark or save the resources in a central location.
Review and organize the resources based on topic or relevance.

Conduct a hypothesis test using R

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Hands-on practice with R will help you apply the concepts of hypothesis testing to real-world data.

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Choose a dataset and research question that can be addressed through hypothesis testing.
Formulate a null and alternative hypothesis.
Perform the hypothesis test using appropriate R functions.
Interpret the results of the hypothesis test.
Write a brief report summarizing your findings.

Review the book 'Testing Statistical Hypotheses' by Lehmann and Romano

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This book provides a comprehensive and rigorous treatment of hypothesis testing, which can deepen your understanding of the concepts.

View Testing Statistical Hypotheses on Amazon

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Read the relevant chapters on hypothesis testing.
Work through the examples and exercises in the book.
Refer to the book when you need to clarify concepts or review material.

Career center

Learners who complete Hypotheses Testing in Econometrics will develop knowledge and skills that may be useful to these careers:

Econometrician

Econometricians collect and analyze data to build models that can be used to forecast economic trends and make informed decisions. They often need to use sophisticated statistical methods, such as hypothesis testing, to ensure that their models are accurate and reliable. This course would provide you with a strong foundation in hypothesis testing, which is essential for success in econometrics.

See salaries and explore the career path for Econometrician

Financial Analyst

Financial analysts use data to evaluate the financial performance of companies and make investment recommendations. They often need to use hypothesis testing to determine whether a particular investment is likely to be profitable. Understanding the theory behind statistical analysis is important for working with financial data.

See salaries and explore the career path for Financial Analyst

Data Scientist

Data scientists use data to solve problems and make informed decisions. They often need to use hypothesis testing to determine whether a particular hypothesis is supported by the data. This course will fortify the foundations in the hypothesis testing needed by data scientists.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

Quantitative analysts use mathematical and statistical models to analyze financial data and make investment decisions. They often need to use hypothesis testing to determine whether a particular investment is likely to be profitable. This course can help you develop the skills needed to be successful in this evolving field

See salaries and explore the career path for Quantitative Analyst

Statistician

Statisticians collect, analyze, and interpret data to provide insights and make informed decisions. They often need to use hypothesis testing to determine whether a particular hypothesis is supported by the data. This course will provide you with a strong foundation in hypothesis testing, which is essential for success in statistics.

See salaries and explore the career path for Statistician

Market Researcher

Market researchers use data to understand consumer behavior and make informed decisions about marketing campaigns. They often need to use hypothesis testing to determine whether a particular marketing campaign is likely to be successful. This course would provide you with a strong foundation in hypothesis testing, which is essential for success in market research.

See salaries and explore the career path for Market Researcher

Actuary

Actuaries use mathematical and statistical models to assess risk and make informed decisions about insurance policies. They often need to use hypothesis testing to determine whether a particular insurance policy is likely to be profitable. This course would provide you with a strong foundation in hypothesis testing, which is essential for success as an actuary.

See salaries and explore the career path for Actuary

Operations Research Analyst

Operations research analysts use mathematical and statistical models to improve the efficiency of business operations. They often need to use hypothesis testing to determine whether a particular change in operations is likely to be beneficial. This course would provide you with a strong foundation in hypothesis testing, which is essential for success as an operations research analyst.

See salaries and explore the career path for Operations Research Analyst

Risk Manager

Risk managers use data to identify and assess risks and make informed decisions about how to mitigate those risks. They often need to use hypothesis testing to determine whether a particular risk is likely to occur. This course would provide you with a strong foundation in hypothesis testing, which is essential for success as a risk manager.

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Business Analyst

Business analysts use data to analyze business problems and make informed decisions. They often need to use hypothesis testing to determine whether a particular business decision is likely to be successful. This course would provide you with a strong foundation in hypothesis testing, which is essential for success as a business analyst.

See salaries and explore the career path for Business Analyst

Data Analyst

Data analysts use data to solve problems and make informed decisions. They often need to use hypothesis testing to determine whether a particular hypothesis is supported by the data. This course would provide you with a strong foundation in hypothesis testing, which is essential for success as a data analyst.

See salaries and explore the career path for Data Analyst

Consultant

Consultants use data to solve problems and make informed decisions for their clients. They often need to use hypothesis testing to determine whether a particular hypothesis is supported by the data. This course would provide you with a strong foundation in hypothesis testing, which is essential for success as a consultant.

See salaries and explore the career path for Consultant