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Hypothesis Testing with Python and Excel

Master statistical hypothesis testing using Python and Excel, focusing on population means and proportions for data-driven business decisions.

Master statistical hypothesis testing using Python and Excel, focusing on population means and proportions for data-driven business decisions.

This practical course teaches the fundamentals of hypothesis testing for business analytics, focusing on population means and proportions. Students learn to apply the central limit theorem and conduct statistical tests using both Excel and Python. The course combines theoretical knowledge with hands-on practice, enabling learners to design and implement hypothesis tests in real business scenarios. Perfect for professionals seeking to enhance their data analysis capabilities.

4.2

(23 ratings)

3,283 already enrolled

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Hypothesis Testing with Python and Excel

This course includes

5 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,435

What you'll learn

  • Conduct hypothesis tests effectively using Python

  • Apply statistical testing in workplace scenarios

  • Perform hypothesis testing with Excel

  • Understand the central limit theorem

  • Analyze population means and proportions

  • Design experimental plans for business applications

Skills you'll gain

Python Programming
Statistical Analysis
Hypothesis Testing
Excel Analytics
Data Analysis
Business Analytics
Statistical Inference
Population Statistics

This course includes:

24 Minutes PreRecorded video

3 assignments, 1 peer review, 2 ungraded labs

Access on Mobile, Tablet, Desktop

FullTime access

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There is 1 module in this course

This comprehensive course covers essential concepts in hypothesis testing for business analytics. Students learn to test population means and proportions using both Excel and Python, understand the central limit theorem, and apply these skills to real-world business scenarios. The curriculum combines theoretical foundations with practical applications, preparing learners to conduct meaningful statistical analysis in professional settings.

Hypothesis Testing

Module 1 · 5 Hours to complete

Fee Structure

Payment options

Financial Aid

Instructors

Gerald S. Brown
Gerald S. Brown

4.2 rating

8 Reviews

3,329 Students

4 Courses

Data Analytics Expert and Supply Chain Management Specialis

Dr. Gerald S. Brown serves as Part-time Senior Lecturer at the Gordon Institute of Tufts University, where he specializes in process improvement and supply chain management. His professional experience includes positions at IBM-France and Andersen Consulting, bringing practical industry expertise to his academic role. At Tufts, he teaches courses focusing on data analytics, process improvement methodologies, and supply chain optimization. His teaching approach combines theoretical foundations with practical applications, as demonstrated in his Coursera course "Hypothesis Testing with Python and Excel," which has enrolled over 3,000 students. The course reflects his expertise in applying statistical methods to business problems, teaching fundamental concepts of hypothesis testing using both Excel and Python. His work emphasizes the importance of data-driven decision-making in modern business environments, particularly in supply chain management and process optimization contexts.

Kishore K. Pochampally
Kishore K. Pochampally

4.2 rating

8 Reviews

3,376 Students

4 Courses

Operations Management Expert and Analytics Specialist

Dr. Kishore K. Pochampally serves as Professor of Quantitative Studies, Operations and Project Management at Southern New Hampshire University and Part-time Senior Lecturer at Tufts University's Gordon Institute. His academic journey includes postdoctoral work at MIT's Sloan School of Management, a Ph.D. and M.S. in Industrial Engineering from Northeastern University, and a B.E. in Mechanical Engineering from the National Institute of Technology in India. His expertise spans lean six sigma, business analytics, project management, and operations management, earning him two nominations for SNHU's teaching excellence award. He holds prestigious certifications including Six Sigma Black Belt (ASQ), Project Management Professional (PMP®), and Certified Analytics Professional (CAP®). His research impact is evidenced by citations across six continents and four published books in six sigma, reliability analysis, supply chain design, and design of experiments. Through his Coursera course "Hypothesis Testing with Python and Excel," he helps students master data analysis techniques while conducting corporate workshops on lean six sigma and project management, training professionals for PMP® and six sigma certification exams.

Hypothesis Testing with Python and Excel

This course includes

5 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,435

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.2 course rating

23 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.