Statistical graphics for communicating

Peter Ellis

June 2016

Today’s content

Different purposes of graphics
What makes graphics excellence
Improving graphics

Purposes of graphics

Data science workflow

datascience

Grolemund and Wickham, http://r4ds.had.co.nz/introduction.html

Different purposes

…exploratory…

…analysis and diagnosis…

…presentation…

Comprehend this:

data(anscombe)
anscombe[ , c(1,5,2,6,3,7,4,8)]

##    x1    y1 x2   y2 x3    y3 x4    y4
## 1  10  8.04 10 9.14 10  7.46  8  6.58
## 2   8  6.95  8 8.14  8  6.77  8  5.76
## 3  13  7.58 13 8.74 13 12.74  8  7.71
## 4   9  8.81  9 8.77  9  7.11  8  8.84
## 5  11  8.33 11 9.26 11  7.81  8  8.47
## 6  14  9.96 14 8.10 14  8.84  8  7.04
## 7   6  7.24  6 6.13  6  6.08  8  5.25
## 8   4  4.26  4 3.10  4  5.39 19 12.50
## 9  12 10.84 12 9.13 12  8.15  8  5.56
## 10  7  4.82  7 7.26  7  6.42  8  7.91
## 11  5  5.68  5 4.74  5  5.73  8  6.89

compared to:

Put the data in its place

Use during analysis

present results

Compare to


	Dependent variable:

	MedianIncome

MeanBedrooms	0.012
	(0.011)

PropPrivateDwellings	0.650^***
	(0.111)

PropSeparateHouse	-0.148^***
	(0.025)

PropMultiPersonHH	-0.082
	(0.105)

PropNotOwnedHH	0.170^***
	(0.033)

MedianRentHH	0.0002^***
	(0.00003)

PropLandlordPublic	-0.014
	(0.018)

PropNoMotorVehicle	-0.274^***
	(0.067)

PropOld	0.490^***
	(0.073)

PropAreChildren	0.221^***
	(0.075)

PropSameResidence5YearsAgo	-0.053^*
	(0.029)

PropOverseas5YearsAgo	-0.501^***
	(0.087)

PropMaori	-0.074^***
	(0.028)

PropPacific	-0.249^***
	(0.041)

PropAsian	-0.296^***
	(0.031)

PropNoReligion	-0.137^***
	(0.035)

PropSmoker	0.064
	(0.068)

PropSeparated	-0.318^***
	(0.075)

PropDoctorate	1.914^***
	(0.215)

PropPTStudent	0.334^*
	(0.184)

PropUnemploymentBenefit	-0.211
	(0.172)

PropStudentAllowance	-1.959^***
	(0.189)

PropFullTimeEmployed	1.674^***
	(0.056)

PropPartTimeEmployed	0.095
	(0.107)

PropUnemployed	0.058
	(0.208)

PropEmployer	0.876^***
	(0.073)

PropSelfEmployedNoEmployees	-0.333^***
	(0.053)

PropTrades	-0.492^***
	(0.079)

PropLabourers	-0.460^***
	(0.057)

PropAgForFish	0.029
	(0.034)

PropPubAdmin	0.120^**
	(0.047)

PropFinServices	0.996^***
	(0.158)

PropProfServices	1.235^***
	(0.088)

PropWorked40_49hours	0.277^***
	(0.060)

PropPublicTransport	-0.005
	(0.057)

PropWalkJogBike	-0.076^*
	(0.043)

PropNoUnpaidActivities	-0.842^***
	(0.086)

Constant	8.878^***
	(0.139)


Observations	1,785

Note:	p<0.1; p<0.05; p<0.01

Illustrate concepts

animation1

Graphic excellence

Principles

well-designed presentation of interesting data - substance, statistics, and design
complex ideas communicated with clarity, precision, and efficiency
greatest number of ideas in the shortest time with the least ink in the smallest space
nearly always multivariate
telling the truth about the data

Adapted from Tufte

Some specifics

Comparative
Multivariate
High data density
Reveal interactions and comparisons
Nearly all the ink is data ink

Examples

Change this…

…to this:

This is good

But this is better

This is good

But this is better

More detailed examples

Perception of quantity

From best to worst

Position
Length
Area
Volume
Area and slope
Colour and density

Statistical graphics for communicating

Peter Ellis

June 2016

Today’s content

Purposes of graphics

Data science workflow

Different purposes

Comprehend this:

compared to:

Put the data in its place

Use during analysis

present results

Compare to

Illustrate concepts

Graphic excellence

Principles

Some specifics

Examples

Change this…

…to this:

This is good

But this is better

This is good

But this is better

More detailed examples

Perception of quantity

Typical stacked bars…

Orient for easy reading

Sequential colours

Diverging scale

Use position

Much better than

Cluttered

Minimal axis guides

Fade axis title

Remove borders

Remove boxes

Guidelines to back

Background to back

Consistent doc theme