In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods. We will also focus on various modeling objectives, including making inference about relationships between variables and generating predictions for future observations.
This course is part of the Statistics with Python Specialization
Offered By
About this Course
Completion of the first two courses in this specialization; high school-level algebra
Skills you will gain
- Bayesian Statistics
- Python Programming
- Statistical Model
- statistical regression
Completion of the first two courses in this specialization; high school-level algebra
Offered by
Syllabus - What you will learn from this course
WEEK 1 - OVERVIEW & CONSIDERATIONS FOR STATISTICAL MODELING
WEEK 2 - FITTING MODELS TO INDEPENDENT DATA
WEEK 3 - FITTING MODELS TO DEPENDENT DATA
WEEK 4: Special Topics
Reviews
- 5 stars65.62%
- 4 stars20.31%
- 3 stars8.28%
- 2 stars3.43%
- 1 star2.34%
TOP REVIEWS FROM FITTING STATISTICAL MODELS TO DATA WITH PYTHON
Great course. It really improved my understanding of statistical modeling methodologies.
Good course, but the last of three was the most difficult one. I hope that it were a good introduction to the fascinating world of statistics and data science
A great introduction to regression and bayesian analysis in python. I get that the content is hard, but they sum it all well. I would recommend for those who have prior knowledge of statistics.
These whole three certifications lays the foundation for learning Machine Learning a more in-depth way.
About the Statistics with Python Specialization

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