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Overview
Context
Sampling is a cornerstone of inference statistics and hypothesis testing. It's tremendously important in survey analysis and experimental design.
This Sampling in R course offered by Data Camp explains when and why sampling is important, teaches you how to perform common types of sampling, from simple random sampling to more complex methods like stratified and cluster sampling.
Later, the course covers estimating population statistics, and quantifying uncertainty in your estimates by generating sampling distributions and bootstrap distributions.
Throughout the course, you'll explore real-world datasets on coffee ratings, Spotify songs, and employee attrition.
Programme Structure
Chapters include:
- Sampling
- Sampling Methods
- Sampling Distributions
- Bootstrap Distributions
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- New York City, United States
Disciplines
Statistics View 110 other Short Courses in Statistics in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prerequisites
- Introduction to Statistics in R
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions
Funding
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