Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.
Offered By
Johns Hopkins UniversityAbout this Course
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Understand the process of drawing conclusions about populations or scientific truths from data
Describe variability, distributions, limits, and confidence intervals
Use p-values, confidence intervals, and permutation tests
Make informed data analysis decisions
Skills you will gain
- Statistics
- Statistical Inference
- Statistical Hypothesis Testing
Could your company benefit from training employees on in-demand skills?
Try Coursera for Business
Offered by
Syllabus - What you will learn from this course
Week 1: Probability & Expected Values
Week 2: Variability, Distribution, & Asymptotics
Week: Intervals, Testing, & Pvalues
Week 4: Power, Bootstrapping, & Permutation Tests
Reviews
- 5 stars57.44%
- 4 stars23.13%
- 3 stars10.08%
- 2 stars4.55%
- 1 star4.78%
TOP REVIEWS FROM STATISTICAL INFERENCE
The strategy for model selection in multivariate environment should have been explained with an example. This will make the model selection process, interaction and its interpretation more clear.
A very conceptual course to understand the fundamentals of Inferential Statistics. I would recommend this course to all aspiring data analysts/scientists or business analysts.
Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .
For starters, it will demand a lot of out of class studies. It took me three months to go through the basics in Khan Academy before attempting it - and after that it was straight forward.
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.
