In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling.
About this Course
High school algebra
Skills you will gain
High school algebra
University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
- 5 stars76.09%
- 4 stars18.54%
- 3 stars3.62%
- 2 stars0.84%
- 1 star0.88%
TOP REVIEWS FROM UNDERSTANDING AND VISUALIZING DATA WITH PYTHON
A very well explained and well-structered course. I highly recommend to those who want learn statistics along with python programming. This course majorly focuses on the visualization aspect.
I've learned so much about the Python programming as well as general statistical skills. This course also lead me to change my initial university's major from Finance to Data Science.
Well organized material. The Discussion forum was the best one I've experienced in my Coursera education. All my questions were answered within one day. The best statistics class I've taken yet!
Really enjoyed this course. Looking forward to the next part of the specialization. I thought the quality of the lectures was excellent and made the topic interesting and digestible
About the Statistics with Python Specialization
This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language. Learners will learn where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization. They will be able to utilize data for estimation and assessing theories, construct confidence intervals, interpret inferential results, and apply more advanced statistical modeling procedures. Finally, they will learn the importance of and be able to connect research questions to the statistical and data analysis methods taught to them.
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.