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Mathematica Data Analysis

Mathematica Data Analysis

By : Sergiy Suchok
5 (1)
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Mathematica Data Analysis

Mathematica Data Analysis

5 (1)
By: Sergiy Suchok

Overview of this book

There are many algorithms for data analysis and it’s not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis. If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure. With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems. With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel.
Table of Contents (10 chapters)
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9
Index

Hypotheses about the variance


Suppose we have a sample with variance and we assume that the true value of the sample variance is , then we can test the following hypotheses: H0 - ratio and the alternative hypothesis HA:.

In practice, variance is often a measure of risk; therefore, while testing the hypothesis of the equality of variances, we evaluate how accurate is the risk degree is.

The verification of this hypothesis is performed with the help of the VarianceTest function. This function can also check hypotheses on the equality of variances in several samples. For example, if one sample's variance is and the other's -, then the main hypothesis will be an equality check, . Mathematica conducts a series of tests to determine the probability of the hypothesis's truth.

Test's name

Type of test

Description

"BrownForsythe"

Robust

A robust Levene test

"Conover"

Symmetry

This is based on squared ranks of the sample data

"FisherRatio"

Normality

This is based on

"Levene"

robust...

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