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Mathematica Data Analysis

You're reading from   Mathematica Data Analysis Learn and explore the fundamentals of data analysis with power of Mathematica

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Product type Paperback
Published in Dec 2015
Publisher
ISBN-13 9781785884931
Length 164 pages
Edition 1st Edition
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Author (1):
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Sergiy Suchok Sergiy Suchok
Author Profile Icon Sergiy Suchok
Sergiy Suchok
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Toc

Table of Contents (10) Chapters Close

Preface 1. First Steps in Data Analysis FREE CHAPTER 2. Broad Capabilities for Data Import 3. Creating an Interface for an External Program 4. Analyzing Data with the Help of Mathematica 5. Discovering the Advanced Capabilities of Time Series 6. Statistical Hypothesis Testing in Two Clicks 7. Predicting the Dataset Behavior 8. Rock-Paper-Scissors – Intelligent Processing of Datasets Index

Checking the degree of sample dependence


In statistical analysis, it is important to understand whether we are dealing with dependent or independent sets of data. This affects the system model building approach, and thus, the forecast quality.

The independence of the two data samples (represented in a vector or matrix form) is carried out with the help of the IndependenceTest function. This function conducts a series of tests to check the main hypothesis H0 to see whether the vectors are independent, and to check the alternative hypothesis HA to see whether the vectors are dependent.

The following tests are conducted:

Test's name

Type of test

Description

"BlomqvistBeta"

Monotonic

This is based on Blomqvist's β

"GoodmanKruskalGamma"

Monotonic, vector

This is based on the γ-coefficient

"HoeffdingD"

Vector

This is based on Hoeffding's D

"KendallTau"

Monotonic

This is based on Kendall's τ-b

"PearsonCorrelation"

Linear, normality, vector

This is based on Pearson's product-moment...

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