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Sampling in R

4.3+
40 reviews
Intermediate

Master sampling to get more accurate statistics with less data.

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4 Hours15 Videos51 Exercises
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Course Description

Sampling is a cornerstone of inference statistics and hypothesis testing. It's tremendously important in survey analysis and experimental design. This course 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.
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In the following Tracks

Certification Available

Data Analyst with R

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Certification Available

Associate Data Scientist in R

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Statistician with R

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  1. 1

    Introduction to Sampling

    Free

    Learn what sampling is and why it is useful, understand the problems caused by convenience sampling, and learn about the differences between true randomness and pseudo-randomness.

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    Sampling and point estimates
    50 xp
    Reasons for sampling
    50 xp
    Simple sampling with dplyr
    100 xp
    Simple sampling with base-R
    100 xp
    Convenience sampling
    50 xp
    Are findings from the sample generalizable?
    100 xp
    Are these findings generalizable?
    100 xp
    Pseudo-random number generation
    50 xp
    Generating random numbers
    100 xp
    Understanding random seeds
    100 xp
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Data Analyst with R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

Statistician with R

Go To Track

In other tracks

Statistics Fundamentals with R

Collaborators

Collaborator's avatar
Dr. Chester Ismay
Richie Cotton HeadshotRichie Cotton

Data Evangelist at DataCamp

Richie is a Data Evangelist at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.
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Don’t just take our word for it

*4.3
from 40 reviews
60%
18%
20%
0%
3%
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  • Nurym S.
    9 months

    Insightful

  • Thomas S.
    10 months

    Helped me a lot to understand sampling and bootstrapping.

  • Fulvio B.
    10 months

    Well structured, it gives the basis to understand sampling and to decide which type of sampling is better.

  • Richard L.
    about 1 year

    Solid instruction and materials that covers the intricacies of doing sampling in a statistically correct way

  • Nguyễn K.
    about 1 year

    Great course

"Insightful"

Nurym S.

"Helped me a lot to understand sampling and bootstrapping."

Thomas S.

"Well structured, it gives the basis to understand sampling and to decide which type of sampling is better."

Fulvio B.

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