Fitting Statistical Models to Data with Python
Completed by Richard Nice
January 19, 2020
14 hours (approximately)
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What you will learn
Deepen your understanding of statistical inference techniques by mastering the art of fitting statistical models to data.
Connect research questions with data analysis methods, emphasizing objectives, relationships between variables, and making predictions.
Explore various statistical modeling techniques like linear regression, logistic regression, and Bayesian inference using real data sets.
Work through hands-on case studies in Python with libraries like Statsmodels, Pandas, and Seaborn in the Jupyter Notebook environment.
Skills you will gain
- Category: Advanced Analytics
- Category: Statistical Methods
- Category: Data Analysis
- Category: Dependency Analysis
- Category: Statistical Modeling
- Category: Regression Analysis
- Category: Model Evaluation
- Category: Bayesian Statistics
- Category: Statistical Software
- Category: Logistic Regression
- Category: Statistical Inference
- Category: Predictive Modeling
