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6/1/2020
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Statistics with Python Specialization is the name of a new and practical course of statistical thinking for everyone, in which Python is used for statistical illustration, inference and modeling. This set is designed to teach learners the basic and intermediate concepts of statistical analysis using the Python programming language. Learners will learn where data comes from and the types of data that can be collected, and then learn about data design, data management, and how to explore and visualize data. Learners will also be able to use data to estimate and evaluate theories, construct confidence intervals, interpret inferential results, and implement advanced statistical modeling processes, and finally be able to relate the importance and how research questions relate to statistics and analysis methods. Understand the data they are taught.
Build and interpret data visualizations using the Python programming language and related packages and libraries
Implement and interpret inferential processing to analyze real data
Applying statistical modeling techniques to data (logical and linear regression, linear models, multilevel models and Bayesian inference techniques)
Understand the importance of the relationship between research questions and data analysis methods
Publisher: Coursera Instructors: Brenda Gunderson, Brady T. West and Kerby Shedden English language Level of training: Introductory Number of courses: 3
COURSE 1 Understanding and Visualizing Data with Python
COURSE 2 Inferential Statistical Analysis with Python
COURSE 3 Fitting Statistical Models to Data with Python
High school-level algebra is the only background knowledge mandatory for the first course in the series. A basic Python and/or coding background is recommended.
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Subtitle: English and other languages
Quality: 720
This collection includes 3 different courses.
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