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Distractions and amusements, with a sandwich and coffee.

And whatever I do will become forever what I've done.
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• don't rehearse
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Words are easy, like the wind;

Faithful friends are hard to find.

—William Shakespeare

Somedays it's hard to know what you feel.

Maybe it's because you don't have a word for it yet.

Did that flight leave you *quacy* because of the *kadful* food? Next time, you should be more *infulic* and insist on an upgrade.

I like my friends both *kessive* and *wanric*, which I find to provide a nice balance. I don't generally like those who are *sadry* or *tamty*.

If this makes you *weable*, keep it to yourself.

Below are the alphabetically first 5–12 letter single-word unanimals for each letter. In some cases, no names of a given length were generated for a given letter.

aacec

baagd

bacac

caane

caary

daagy

daany

eabed

eable

faary

faaty

gaaly

gaany

haady

haced

iaded

iaden

jahed

jamid

kebed

kecig

laasy

labed

machy

maded

naavy

nabul

oated

obeed

pabed

pabey

qaaly

qafed

rabus

racin

saady

saany

taamy

tably

uadec

uaned

vaaty

vable

waady

waany

xated

xeany

yaced

yagre

zalil

zfust

aadare

bacint

badeny

caanoy

caaove

dabred

dacric

eaapte

eacomt

faaded

faalul

gaajly

gaaole

hacied

hadful

iadeve

iafhed

jadent

jadicy

kadful

kagful

laafil

laared

maaded

macfil

nabfle

nabime

oabenn

oadant

paaced

pacful

qacant

qacent

raadry

raatyd

saaded

saated

taaikl

tadeny

uacape

uadess

vaadyd

vaased

waapmy

wacful

xashed

xefric

yaefus

yaptec

zadful

zorted

aaciwed

baadive

baatain

caalave

caamful

dabrned

dacefun

eaagate

eabnsed

faarirt

faathul

gacaved

gacgest

habived

haceful

iagerad

iamimed

jaative

jaceaul

kaiding

karefol

laatful

laching

maacful

maasful

naanhed

nabefus

oaadein

oablagy

paative

pabrecy

qaading

qabilgy

raading

raaehgy

saaempe

saaflen

taateng

tabsang

uabrant

uafcans

vaakive

vaasted

waadful

waaekly

xeiricy

xerting

yanaced

yannant

ziclatl

zipfred

aacfiled

bacigled

badessed

caabefol

caadepus

daatated

daceased

eaabided

eabllive

faaciwty

faanhyen

gaatited

gadeding

habateng

hacantic

iabliged

iabumled

jabonted

jacerous

karkefus

katiomat

labpinty

lacioest

maaniked

mabrathy

naaqated

nabheful

oablieed

oacemhed

paatefel

pachapte

qaaloved

qaeigued

rabenooy

rablnred

saafiled

saagluse

tacdeful

tacerate

uabhliac

uadenabe

vaadeful

vaatious

waathful

waberous

xeadliun

xeenated

yagdaned

yaolapte

zafrebus

zleefled

aadeiaged

baaderaus

babefaled

caacitave

caafaligy

dacfirive

daenimast

eaadimate

eablagied

faadented

faarulhed

gacsitive

gagpalled

habuinate

hacenglic

iabuttant

iadelaced

jaadevieg

jacrucsid

kacergiag

kelrerous

laasivain

lachdysmy

mabuilive

macelomed

nabfiated

nabiovain

oablasted

oablatled

paacratky

paaikline

qaterated

qeatioped

rabomated

racastaon

sacedable

sacgented

taayhlive

tabelious

uabussing

uadenated

vaalenabe

vaashious

waadoemat

wabenated

xilretate

xiserompe

yamrictun

yamurhing

zlevenist

zonansicy

aacrlacted

babralkant

baerkanped

caabiohant

caapenious

dacmulting

dagrutased

eacadageed

eadgitated

faagyerave

facimfelit

gaeomasine

gamheluted

hacopaglic

hadgensted

iaberanted

iacapoaged

jafapified

jamhelable

kameracive

karionaled

lachulated

lacisingfe

machklaved

madncgreen

nachinamed

nackeluted

oablaghang

oadamative

padhinated

padhuivien

qafeleased

qauolivive

raanttuled

rachimhive

sabplegted

sacitusiol

tacfuleked

tacpuented

uacricited

uafeitomed

vacticaled

vactinated

wacherlaty

wacinpefol

xantosored

xeangerted

yanilisive

yellahaged

zhiwufolad

zomiunable

aadofaagave

baminathais

banaterible

caamilavive

cabmiusated

damimatited

danklusicom

eadhiecated

eapriuhated

faatigomate

facantefuon

gaanhwelady

gadateroped

hacapigefel

hacngomrens

iadegeasiel

iafolorable

jargionafil

jerhuvessed

katterative

keranhiving

labwefusant

lacingresen

mabmantkrey

maciraleful

nabtowinned

nactupivied

oabemptaced

oanhissenac

padiwabtent

paexhufiond

qeeferenged

qeesetaeste

raadivisged

racfistaled

saasterheve

sabesatired

taesaglenhe

tamgurtined

uafurentful

uaoraverene

vacerslaons

vacimartatt

waadrwfaced

wacgertions

xingfolsent

yansictivac

yericishing

zosperusted

abdepeastiad

banokrariled

basigousated

caaperousais

caarimiasate

damismainabl

daninpicided

eaisderiured

eampaptitive

faadolenated

faadyrerosed

garmristeful

geajrefobled

hacnimisated

hadcomtanful

ianasioraled

ianhistecite

jadhitiraled

joicawiveful

kanclinneful

kintimageful

laemkovapole

lalerblessed

madenstetint

maichapfiled

naberitenhed

nactimivital

oafiwhililed

obeigonhawed

paerhomerate

paevimionape

qaoishaustus

qrecsipinted

racigatergec

ragrionative

saanhionable

sacgrocelous

taapmincoary

taforetisteg

ubforsiolate

ubnaterative

vaborlarxfol

vacupatenous

wacforstrove

wamtechevons

xursiwolated

yanthrlevous

yastituflesd

Here are all some lists with common suffixes

***acy**
abmacy baplacy clacy eghacy feacy geacy henacy iceacy jhacy leacy meacy ncacy ornacy peacy quacy reacy somacy taracy unpncacy veacy weacy

***aed**
abmenaed baribraed calyifaed deidonaed eeraed filicaed gearaed henisifaed icifaed jrabyaed lafaed meciupaed nasibaed odaed pevibaed ralaed sadyraed tarlifaed uduraed valaed warpuifaed yisivaed

***ant**
aadedenant babralkant caabiohant dalhant eaxant facagrant galhant hamtlihant iabuttant jepulant kesretant lanant macnant nactant oabtant pairant qacant ranntant sabsant tanjerant uabrant vagkant wasgimant yannant zontoghant

***anted**
aagranted cadanted deanted eadhanted fatanted hintanted iaberanted leanted manted nanted ocranted partanted recinanted samtanted tachanted unhanted vanted wisanted yononanted

***any**
abany brany ceany daany ecmeraany foany gaany heany iodany krany lorany memany nmany orcany puabrany reany saany tiany umamany veany waany xeany yrany

***ate**
aadiwenate bodenate cabriocate damtate eaadimate faesiosate ganaonate habuinate iasate kocaterate latlerate mapicuate naiclenate oagrenate paciciate qrate rarhenate sabnate tacerate uaoonate vasferate wacteruate xelate yinanate

***ated**
aachinated baiated caated daatated eaderated facated gaeated haoiated iacmatated jeated keinerated lachulated maminated naaqated oalforated padhinated qated rabomated saated taidated uadenated vactinated wabenated xated yedeated

***ble**
aasable banible caceable damerable eable fagilable garable hafelible ibepapible jamhelable kiballible lable malable naenable oarhawable pable qafable raconable sablable tacsble uatharible vablable wacerable zomiunable

***ed**
aablined babefaled caagimed daatated eaabided faaded gaared habived iaberanted jabonted karionaled laared maaded naanhed oablasted paaced qaaloved raanttuled saaded tacfuleked uacricited vaased waanked xantosored yaced zimed

***ful**
aanful badeful caamful dadhful eacreful faapsful gacful haceful iatful jadeful kadful laatful maacful nabheful oanelful pacful qaitful raasful sabmeful tacdeful uasanful vaadeful waadful yenteful zadful

***gy**
abeegy bengy caafaligy daagy eubagy fantrbangy gengy halkagy inalgy jangy larpurgy mancracgy ncangy oablagy pagigy qabilgy raaehgy sadhargy tarpiwekgy ulergy vactongy wacikgy

***hed**
abmonhed bailhed caihed damurhed eafliched faarulhed galhed halowhed iafhed jahed kroufhed lemashed macithed naanhed oacemhed pached qeihed ralerhed sached tamhed ubmarhed vacihed wanished xashed yisathed

***ic**
aanomic bestic cabpulic dacric eafmic faatic galfic hacantic iavicatic jeoloouaic kapfic lacic maastic nameic oamaspic panatic qlatic ragburic saavicic talic uamericic vakic wacic xefric yassic

***ied**
aasivied banipatied cabrafied daomipied eablagied feafied gapatgied hacied iasirfied jafapified kolpiried lelrified mandumried napied obentified pagied qoied radied sabied taied udracied veatofied walied yasrified

***ive**
aastessive baadive caavive dacfirive eabllive fafresvive gacsitive hacfive iasive jaative kameracive lactive mabuilive nadvosive oadamative paative qasative racensive saanive taayhlive uafunitive vaakive wadotive xipilivive yanilisive zonixive

***lic**
acfulic borilic cabpulic deseelic enblic ferlic gearlic hacenglic infulic jilolic lecablic macablic nelalic ocpalrlic pealic qllic rastilic sanmacelic talic ulnataclic valic wartipilic

***ous**
abfsious banious caapenious dahilious ecdiadaous facious ganerous hacious iarepsious jacerous kelrerous laiwhacous madious nacelous oaperous pactious qarerous ralous saarous tabelious uagensious vaashious waberous xoodous yasious zowerlrous

***ric**
abmaric camric dacric ecjaaric faeric gesteric hararic icoeric juric leric mameric necric oncaric paric qoric ragburic sadeuric talric unisteric varic wanric xefric

***ry**
afpomery bikykury caary danery eipiry faary gaary hacry icary jeary kovary lantry magery naiwory obsery paegry qaulary raadry sadry tacuory uanabry vacalry waary xeary yincalry

***ty**
ablanty bamty cagnty dastimty eadnty faaciwty gakaty harty ilnpatty jerenty kagity labpinty maghenty nanty oblenty paduevaty qearty racternty sacty tamtonty uanaty vaaty wacherlaty xinty yolety zonturty

My cover design for Hola Mundo by Hannah Fry. Published by Blackie Books.

Curious how the design was created? Read the full details.

*You can look back there to explain things,
but the explanation disappears.
You'll never find it there.
Things are not explained by the past.
They're explained by what happens now.
—Alan Watts*

A Markov chain is a probabilistic model that is used to model how a system changes over time as a series of transitions between states. Each transition is assigned a probability that defines the chance of the system changing from one state to another.

Together with the states, these transitions probabilities define a stochastic model with the Markov property: transition probabilities only depend on the current state—the future is independent of the past if the present is known.

Once the transition probabilities are defined in matrix form, it is easy to predict the distribution of future states of the system. We cover concepts of aperiodicity, irreducibility, limiting and stationary distributions and absorption.

This column is the first part of a series and pairs particularly well with Alan Watts and Blond:ish.

Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Markov Chains. *Nature Methods* **16**:663–664.

*Places to go and nobody to see.*

Exquisitely detailed maps of places on the Moon, comets and asteroids in the Solar System and stars, deep-sky objects and exoplanets in the northern and southern sky. All maps are zoomable.

Quantile regression explores the effect of one or more predictors on quantiles of the response. It can answer questions such as "What is the weight of 90% of individuals of a given height?"

Unlike in traditional mean regression methods, no assumptions about the distribution of the response are required, which makes it practical, robust and amenable to skewed distributions.

Quantile regression is also very useful when extremes are interesting or when the response variance varies with the predictors.

Das, K., Krzywinski, M. & Altman, N. (2019) Points of significance: Quantile regression. *Nature Methods* **16**:451–452.

Altman, N. & Krzywinski, M. (2015) Points of significance: Simple linear regression. *Nature Methods* **12**:999–1000.

Outliers can degrade the fit of linear regression models when the estimation is performed using the ordinary least squares. The impact of outliers can be mitigated with methods that provide robust inference and greater reliability in the presence of anomalous values.

We discuss MM-estimation and show how it can be used to keep your fitting sane and reliable.

Greco, L., Luta, G., Krzywinski, M. & Altman, N. (2019) Points of significance: Analyzing outliers: Robust methods to the rescue. *Nature Methods* **16**:275–276.

Altman, N. & Krzywinski, M. (2016) Points of significance: Analyzing outliers: Influential or nuisance. Nature Methods 13:281–282.

Two-level factorial experiments, in which all combinations of multiple factor levels are used, efficiently estimate factor effects and detect interactions—desirable statistical qualities that can provide deep insight into a system.

They offer two benefits over the widely used one-factor-at-a-time (OFAT) experiments: efficiency and ability to detect interactions.

Since the number of factor combinations can quickly increase, one approach is to model only some of the factorial effects using empirically-validated assumptions of effect sparsity and effect hierarchy. Effect sparsity tells us that in factorial experiments most of the factorial terms are likely to be unimportant. Effect hierarchy tells us that low-order terms (e.g. main effects) tend to be larger than higher-order terms (e.g. two-factor or three-factor interactions).

Smucker, B., Krzywinski, M. & Altman, N. (2019) Points of significance: Two-level factorial experiments *Nature Methods* **16**:211–212.

Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments.. Nature Methods 11:597–598.