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Sampling in R

28 reviews

Master sampling to get more accurate statistics with less data.

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4 Hours15 Videos51 Exercises9,797 Learners4000 XPData Analyst with R TrackData Scientist with R TrackData Scientist Professional with R TrackStatistician with R TrackStatistics Fundamentals with R Track

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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.
  1. 1

    Introduction to Sampling


    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

In the following tracks

Data Analyst with RData Scientist with RData Scientist Professional with RStatistician with RStatistics Fundamentals with R


Dr. Chester Ismay
Richie Cotton Headshot

Richie 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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  • Dimitris L.
    3 days

    well organized and presented

  • nanfah k.
    about 1 month

    Like it

  • Deyanira L.
    about 2 months

    Very helpful to begin to study sampling

  • Stuart K.
    about 2 months

    Really well explained. Made the content both enjoyable and understandable.

  • Marc A.
    about 2 months

    Very interesting course! Thanks.

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"well organized and presented"

Dimitris L.

"Like it"

nanfah k.

"Very helpful to begin to study sampling"

Deyanira L.

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