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 stars65.52%
- 4 stars20.28%
- 3 stars8.26%
- 2 stars3.43%
- 1 star2.49%
TOP REVIEWS FROM FITTING STATISTICAL MODELS TO DATA WITH PYTHON
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.
Awesome overview about what can we do with statictics knowlegde! Half theory, half practice with Python is a great format
Very informative. But had few confusions in the last course. Also the python code explanations were not good as the instructor was rushing through it without explaining.
It was very technical and a lot of the mathematics behind the models were not explained properly. The codes were also not explained properly
About the Statistics with Python Specialization

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