Fitting Statistical Models to Data with Python
Completed by ABDUL HANNAN SIDDIQUI
September 3, 2021
14 hours (approximately)
ABDUL HANNAN SIDDIQUI'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: Statistical Analysis
- Category: Predictive Modeling
- Category: Data Visualization Software
- Category: Advanced Analytics
- Category: Logistic Regression
- Category: Jupyter
- Category: Bayesian Statistics
- Category: Statistical Inference
- Category: Exploratory Data Analysis
- Category: Correlation Analysis
- Category: Python Programming
- Category: Statistical Modeling
