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.
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Subject
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Language
English
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Duration
12 weeks
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Status
Available
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U-M Credit Eligible
No
Data Science
Instructors
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Brenda Gunderson
Lecturer IV and Research Fellow
Department of Statistics
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Brady West
Research Associate Professor
Institute for Social Research
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Kerby Shedden
Professor
Department of Statistics
Courses (3)
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Learn moreUnderstanding and Visualizing Data with Python
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4 weeks
Learn statistical fundamentals, including study design, data visualization, and inference, while using Python tools like Pandas and Matplotlib to analyze data. -
Learn moreInferential Statistical Analysis with Python
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4 weeks
Build confidence in inferential statistics using Python to estimate population values and test hypotheses with real-world data. -
Learn moreFitting Statistical Models to Data with Python
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4 weeks
Learn to fit statistical models using Python and apply regression, Bayesian, and mixed-effects methods to real data.