Fitting Statistical Models to Data with Python
Completed by Ozeias Antonio da Silva
February 2, 2021
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: Logistic Regression
- Category: Bayesian Statistics
- Category: Statistical Modeling
- Category: Data Analysis
- Category: Statistical Inference
- Category: Statistical Software
- Category: Statistical Programming
- Category: Advanced Analytics
- Category: Exploratory Data Analysis
- Category: Statistical Analysis
- Category: Statistical Methods
- Category: Dependency Analysis
