Data mining, data distribution and hypothesis testing

Important to know:
The course video is English with Romanian subtitles and test questions are in Romanian.

Overview

Useful information can be extracted from large data sets to determine what happened, what might happen, or what should happen. Explore descriptive, predictive, and prescriptive analytical data, including data extraction, distribution models, and hypothesis testing.

 

Objectives

  • Recognize key features of descriptive analytics
  • Recognize key features of descriptive analytics
  • Recognize key features of data mining
  • Identify important concepts and techniques of data mining
  • Identify methods of data mining used for predictive analytics
  • Identify standard features
  • Identify the characteristics of a distribution list the characteristics of Binomial and Poisson distributions
  • recognize the main features of testing and applying hypotheses
  • recognize the main features of one- and two-element hypothesis testing
  • match analytical problems with appropriate methods of data extraction

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Enrolled: 4 students
Video: 00:35:09
Level: Intermediate

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