- Level Professional
- المدة 5 ساعات hours
- الطبع بواسطة Tufts University
-
Offered by
عن
In today's job market, leaders need to understand the fundamentals of data to be competitive. An essential procedure to understand business and analytics is hypothesis testing. This short course, designed by Tufts University expert faculty, will teach the fundamentals of hypothesis testing of a population mean and a population proportion, using Excel and Python for calculations. You'll also discover the central limit theorem, which is essential for hypothesis testing. To conclude the course, you will apply your newfound skills by creating a plan for an experiment in your own workplace that uses hypothesis testing.الوحدات
Hypothesis Testing of Means
1
Assignment
- Mean Hypothesis Testing Practice Quiz
1
Labs
- Python Practice: Hypothesis Testing for Means
3
Videos
- Central Limit Theorem for Sample Means
- Hypothesis Testing of Population Mean: Excel Example
- Python for Hypothesis Testing of Population Mean
3
Readings
- Introduction
- Basics of Hypothesis Testing
- Hypothesis Test Examples for Means
Hypothesis Testing of Proportions
1
Assignment
- Proportion Hypothesis Testing Practice Quiz
1
Labs
- Python Practice: Hypothesis Testing for Proportions
2
Videos
- Central Limit Theorem for Sample Proportions
- Python for Hypothesis Testing of Population Proportion
1
Readings
- Hypothesis Test Examples for Proportions
Business Applications of Hypothesis Testing
1
Assignment
- Final Quiz
1
Peer Review
- Business Applications Peer Review Assignment
2
Readings
- Course Recap
- Learn more about Tufts
Auto Summary
Enhance your data science skills with "Hypothesis Testing with Python and Excel" by Tufts University on Coursera. This professional-level course delves into hypothesis testing fundamentals, using Excel and Python for practical applications. Over 300 minutes, learn about population mean and proportion testing, and the central limit theorem. Ideal for leaders aiming to stay competitive, it offers Starter and Professional subscription options.

Gerald S. Brown

Kishore K. Pochampally