Sampling With and Without Replacement: Easy Explanation for Data Scientists

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In this video, we’ll be talking all about sampling. What is it, why is it useful, and how will you likely encounter sampling in your work as a Data Scientist? All things we’ll cover together! I’ll spend time differentiating sampling with and without replacement to help you leave this video with a solid understanding of how you’ll come across sampling in the real world.

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Contents of this video:
====================
00:00 Introduction to Sampling
00:38 Why Do We Need Sampling?
02:49 What Is Sampling?
03:54 Sampling With Replacement
04:34 Sampling Without Replacement
06:28 To Summarize
  1. Emma Ding
  2. Data Science
  3. Data Science Interview
  4. Emma Ding
  5. Data Interview Pro
  6. sampling without replacement
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Комментарии
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Looking forward to your next video! Interesting.

starbuststream
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Looking forward to the sampling methods!

spikeydude
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Hello miss in order words the larger data set from which we do our sampling can also be called a « sampling frame? »

Thanks for your videos

cococnk
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Hello Miss,

For what size N (of the population) do we think the population size is large enough for us to not make a distinction between sampling with/without replacement ?

cococnk