Statistics with Python
Description
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.
-
Subject
-
Language
English
-
Duration
12 weeks
-
Status
Available
-
U-M Credit Eligible
No
Data Science
Instructors
-
Brenda Gunderson
Lecturer IV and Research Fellow
Department of Statistics
-
Kerby Shedden
Professor
Department of Statistics
-
Brady West
Research Associate Professor
Institute for Social Research
Courses (3)
-
Learn moreUnderstanding and Visualizing Data with Python
|
4 weeks
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 differ -
Learn moreInferential Statistical Analysis with Python
|
4 weeks
In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population -
Learn moreFitting Statistical Models to Data with Python
|
4 weeks
In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in