Mastering Tableau 2018.1, Second Edition 8.4: Clustering Data in Tableau

Mastering Tableau 2018.1, Second Edition 8.4: Clustering Data in Tableau

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Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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The video tutorial explains how to identify outliers using K-means clustering in Tableau. It covers creating scatter plots, applying clustering features, and editing clusters. The tutorial also describes how to analyze cluster inputs and outputs, and understand model values like P value and F statistic. The video concludes with a brief mention of the next topic, Pareto charts.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of using the K means cluster algorithm in data analysis?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the clustering process help in identifying outliers in a dataset?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the steps involved in creating a scatter plot for data analysis.

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What options are available for editing clusters in the analysis tool?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how the model values such as P value and F statistic are used in data analysis.

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