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 stars76.06%
- 4 stars18.57%
- 3 stars3.63%
- 2 stars0.84%
- 1 star0.88%
TOP REVIEWS FROM UNDERSTANDING AND VISUALIZING DATA WITH PYTHON
Excellent high level introduction, would have like the assessment to be more challenging. The additional materials are just amazing for most of them. The notebooks to practice are also excellent.
A very basic but good introduction to understanding data. An introduction to data visualization. Not a good introduction to Python, but does show how to use Python functions to present data.
Excellent introductory course to statistics. Great use of NHANES dataset to demonstrate techniques on real dataset. I would appreciate a more demanding project at the course end.
It is a great introduction to the basics of Statistics, all the concepts were laid out perfectly by the instructors. I can't wait to keep learning with the last 2 courses of the Specialization.
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.
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