Fitting Statistical Models to Data with Python
Completed by Yakov Rabinovich
September 19, 2020
14 hours (approximately)
Yakov Rabinovich's account is verified. Coursera certifies their successful completion of Fitting Statistical Models to Data with Python
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: Data Analysis
- Category: Bayesian Statistics
- Category: Statistical Programming
- Category: Data Visualization Software
- Category: Statistical Inference
- Category: Statistical Methods
- Category: Dependency Analysis
- Category: Advanced Analytics
- Category: Statistical Software
- Category: Statistical Modeling
- Category: Statistical Analysis
- Category: Regression Analysis
