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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis 2. Data Preprocessing FREE CHAPTER 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Descriptive statistics

A descriptive statistic is a function that computes a numeric value which in some way summarizes the data in a numeric dataset.

We saw two statistics in Chapter 3, Data Visualization: the sample mean, Descriptive statistics, and the sample standard deviation, s. Their formulas are:

Descriptive statistics
Descriptive statistics

The mean summarizes the central tendency of the dataset. It is also called the simple average or mean average. The standard deviation is a measure of the dispersion of the dataset. Its square, s2, is called the sample variance.

The maximum of a dataset is its greatest value, the minimum is its least value, and the range is their difference.

If w = (w1, w2, …, wn) is a vector with the same number of components as the dataset, then we can use it to define the weighted mean:

Descriptive statistics

In linear algebra, this expression is called the inner product of the two vectors, w and x = (x1, x2, …, xn). Note that if we choose all the weights to be 1/n, then the resulting weighted mean is just the sample mean.

The median...

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