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.
What's inside
Three courses
Understanding and Visualizing Data with Python
(0 hours)
Understanding and Visualizing Data with Python
(0 hours)
Inferential Statistical Analysis with Python
(0 hours)
Inferential Statistical Analysis with Python
(0 hours)
Fitting Statistical Models to Data with Python
(0 hours)
Fitting Statistical Models to Data with Python
(0 hours)Learning objectives
- Create and interpret data visualizations using the python programming language and associated packages & libraries
- Apply and interpret inferential procedures when analyzing real data
- Apply statistical modeling techniques to data (ie. linear and logistic regression, linear models, multilevel models, bayesian inference techniques)
- Understand importance of connecting research questions to data analysis methods.
- Create and interpret data visualizations using the python programming language and associated packages & libraries
- Apply and interpret inferential procedures when analyzing real data
- Apply statistical modeling techniques to data (ie. linear and logistic regression, linear models, multilevel models, bayesian inference techniques)
- Understand importance of connecting research questions to data analysis methods.
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