# eda

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```					Principios de

Graphical
Tools
ıstica

ıa    e
Leonardo Collado Torres y Mar´ Guti´rrez Arcelus
o
Licenciatura en Ciencias Gen´micas, UNAM
www.lcg.unam.mx/~mgutierr/index.php

e
Cuernavaca, M´xico
Febrero - Junio, 2009

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Exploratory Data Analysis with R

Principios de

Graphical
Tools

1 Graphical Tools

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Diaps. de Jim

Principios de

Graphical
Tools

Estas diapositivas corresponden a las 28, 29 y 30 de la
o
presentaci´n EDA de Jim.

3/6
boxplots

Principios de
Estad´ıstica       boxplot : A plotting method for generating Tukey’s
boxplots.
Graphical           Excellent for comparing location shifts of k distributions of
Tools
varying size.
Assess skewness and spread of either of one or more
distributions.
Boxplots are often a much better summary of a
distribution than are histograms as they do not suﬀer from
either bandwidth choice or the need to have large data
sets.
Example
What does skewness look like on a boxplot, spread? can we
generate some data to exemplify these things? (hint:
remember all of the random number generators which we
talked about in the ﬁrst lecture)                               4/6
Anatomy of a boxplot

Principios de

Graphical
Tools

A, B : lower/upper adjacent values:

r      |q75 − q25 |             (1)
A = inf{xi : xi > q25 − 1.5r }   (2)
B = sup{xi : xi < q75 + 1.5r }   (3)

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Anatomy of a boxplot

Principios de
Estad´ıstica                             The anatomy of a Boxplot

outlier              q
3
Graphical
Tools                           outlier              q

B
2
1

q0.75
0

q0.5
q0.25
−1
−2

A

outlier              q

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```
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