Applied Statistics with Python (edX)

By leveraging the pandas and matplotlib python libraries, you’ll gain exposure to tools used in data analysis, visualization, and data science.

This course specifically explores inferential statistics - the science of applying statistical techniques to quantify and answer real-world data analysis questions.

The content covers three components – descriptive statistics and probability, hypothesis tests and confidence intervals and linear regression analysis.

Upon completing this course, you’ll be able to:

Formulate real-world data analysis questions as problems in statistical frameworks

- Explain how statistical concepts are applied in authentic situations

- Represent data numerically and visually

- Calculate and apply general and normal distribution probabilities

Analyze real-world problems using hypothesis tests and confidence interval techniques

- Construct hypothesis test and confidence interval models to solve problems

- Calculate hypothesis test and confidence interval results using technology

- Interpret the results of hypothesis test and confidence interval calculations

Analyze real-world problems using linear regression analysis techniques

- Construct linear regression models to solve problems

- Calculate linear regression results using technology

- Interpret the results of linear regression calculations

This is the second course in the introductory, undergraduate-level offering that makes up the larger Business Analytics Foundations MicroBachelors program. We recommend taking them in order, unless you have a background in these areas already and feel comfortable skipping ahead.

1. Scripting with Python - starting February 2021

2. Applied Statistics with Python - starting February 2021

This course is part of the Business Analytics Foundations MicroBachelors.

What you'll learn

- Collect and classify data

- Summarize data using visual and numeric techniques

- Quantify answers to questions about estimating parameters using hypothesis test and confidence interval techniques

- Quantify answers to questions about the correlation between variables using linear regression techniques