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DataCamp – Foundations of Inference No ratings yet.

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DataCamp Foundations of Inference

Created/Published/Taught by:
Jo Hardin
Nick Carchedi
Tom Jeon

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Free? Partially: Some Free Content, Some Paid

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$0.00 - $29.00

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From DataCamp:

“One of the foundational aspects of statistical analysis is inference, or the process of drawing conclusions about a larger population from a sample of data. Although counter intuitive, the standard practice is to attempt to disprove a research claim that is not of interest. For example, to show that one medical treatment is better than another, we can assume that the two treatments lead to equal survival rates only to then be disproved by the data. Additionally, we introduce the idea of a p-value, or the degree of disagreement between the data and the hypothesis. And last, we dive into confidence intervals, which measure the magnitude of the effect of interest (e.g. how much better one treatment is than another).”

This course consists of four chapters:

  1. Introduction to ideas of inference
  2. Completing a randomization test: gender discrimination
  3. Hypothesis testing errors: opportunity cost
  4. Confidence intervals

Recommended Prerequisites: none specified

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