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Overview
What you will do during this Statistical Inference in R course offered by Data Camp:
- Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
- In this course you'll learn how to leverage statistical techniques for working with categorical data.
- In this course you'll learn techniques for performing statistical inference on numerical data.
- In this course you'll learn how to perform inference using linear models.
Programme Structure
Courses include:
- Inference in R
- Inference for Categorical Data in R
- Inference for Numerical Data in R
- Inference for Linear Regression in R
Key information
Duration
- Part-time
- 2 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
- There are no prerequisites for this track
- This Track is suitable for beginners. It covers the foundations of inference and provides an introduction to the core set of skills in statistical inference. The courses are designed to develop a user's skill set, no matter their current level of expertise.
- This Track is beneficial for any job that requires a basic understanding of statistical inference. This includes jobs in data analytics, machine learning, and data science.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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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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