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Apa itu ISIKHNAS? : What is iSIKHNAS?
FAQ:Pertanyaan Umum : FAQ
ISIKHNAS Kode-Kode : Codes
Pengguna : Users
Pelsa : Village reporters
Dinas : Field Staff
Laboratorium : Laboratory
Koordinator : Coordinators
Pengguna Data : Data Users
Teknis : Technical
Data Dikelola : Data managed
Referensi Teknis : Technical references
Kode-kode : Codes
Tabel Database : Database Tables
Struktur Database : Database ERDs
Fungsi Database : Database Functions
Panduan dan Standar : Guides and Standards
Menggunakan wiki : Using the Wiki
Pelatihan : Training
ISIKHNAS pelatihan pengguna : iSIKHNAS Training
Epidemiologi di lapangan : Field Epidemiology
Surveilans : Surveillance
Advokasi untuk Anggaran : Budget Advocacy
Analisis Epidemiologi data : Epi Data Analysis
GIS untuk kesehatan hewan : GIS for animal health
Excel
Investigasi penyakit untuk paravet : Disease Investigation
Mengenali tanda-tanda penyakit : Recognising Signs of Disease
Panduan fasilitasi : Facilitators Manual
Glosarium : Glossary
Komunikasi : Communication
Sosialisasi ISIKHNAS : Communicating about iSIKHNAS
ISIKHNAS Videos
ISIKHNAS Logos
Pertanyaan : FAQ
Informasi tentang ISIKHNAS : About iSIKHNAS
Menyerahkan data : Submitting data
Menggunakan kode : Using system queries
Terjemahkan
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Statistik bahasa
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Statistik kelompok pesan
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Ekspor
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Terjemahkan
Pengaturan
Kelompok
Terjemahan terkini
Penambahan terkini
Sandbox messages
Animal and Farmer Identification
Animal ID and health reporting
Basic Field Epi: Facilitator Guide
Basic Field Epi: Manual
Budget Advocacy
Budget Advocacy:Outline
Changing location data
Communication
Coordinator Checklist
Course objectives
Disease Investigation
District coordinators
District coordinators - in more detail
Epidemiological Data Analysis
FAQ: Frequently Asked Questions
Field Epidemiology
Field Epidemiology Advanced: Manual
GIS AH Answers
GIS for Animal Health
How can I get involved?
How does it work?
How is it managed?
Human health
Instant Messaging
Introduction
ISIKHNAS Training Resources
ISIKHNAS Training Toolkit
ISIKHNAS User References
Livestock insurance
Main Page
Manage
Manage : Manage Users
Manage Programs
Mangement of the System
Manual for Coordinators
Manually sending individual or bulk SMS messages
Manuals for Data Users
Manuals for Field Data Reporters
Manuals for Laboratory Users
Manuals:Abattoir Reporters
Manuals:Active Surveillance
Manuals:Animal Idenification
Manuals:Farmer Registration
Manuals:Field Staff
Manuals:General Introduction
Manuals:Insemination
Manuals:InstantMessaging
Manuals:Movement
Manuals:Population
Manuals:Priority disease investigation
Manuals:Registration
Manuals:SMS Reports
Manuals:SMS System Trainer's Manual
Manuals:System Coordinator
Manuals:Vaccination
Manuals:Village Reporters
New system features
Operational instructions:BB
Operational instructions:BH
Operational instructions:CKI
Operational instructions:CKJS
Operational instructions:CKL
Operational instructions:CKO
Operational instructions:CKP
Operational instructions:CKT
Operational instructions:CUL
Operational instructions:DH
Operational instructions:DHP
Operational instructions:DKB
Operational instructions:DKL
Operational instructions:DP
Operational instructions:DX
Operational instructions:IB
Operational instructions:IH
Operational instructions:KGG
Operational instructions:KODE
Operational instructions:KOM
Operational instructions:LAB
Operational instructions:LAPD
Operational instructions:LAPK
Operational instructions:LAPSK
Operational instructions:LH
Operational instructions:LTL
Operational instructions:OB
Operational instructions:P
Operational instructions:PK
Operational instructions:PKB
Operational instructions:POP
Operational instructions:R
Operational instructions:RP
Operational instructions:RVAK
Operational instructions:SK
Operational instructions:SLAB
Operational instructions:SLAP
Operational instructions:SP
Operational instructions:SUR
Operational instructions:TK
Operational instructions:TL
Operational instructions:U
Operational instructions:UC
Operational instructions:VAK
Operational instructions:VSK
Operational instructions:Z
Pelsa
Pelsa Facilitator Manual
Queries
Query message formats
Reports
Role of the Coordinators
Role of training facilitator
Roles and responsibilities:District coordinators
Roles and responsibilities:Regional and Provincial coordinators
SMS handler setup
SMS Handler: Step by step example
Spatial data management manual
Spreadsheet data submission manual
Staff Technical Development
Surveillance
Surveillance course facilitator
Surveillance course participant
Technical assistance modules
Training
Training and Facilitation Guide
Training and Facilitation Guide:Code Lists
Training and Facilitation Guide:Scenario Cards
Training and Facilitation Guide:SMS Message Training points
Training your staff
User References
User registration
User registration by email spreadsheet upload
User types
User:Ben
Using Book Creator
Using the data
Website
What are the benefits?
What is iSIKHNAS?
What is it for?
Who is involved?
Wiki Work
Bahasa
aa - Afar
ab - Abkhaz
ace - Aceh
ady - Adygei
ady-cyrl - адыгабзэ
aeb - Arab Tunisia
aeb-arab - تونسي
aeb-latn - Tûnsî
af - Afrikaans
ak - Akan
aln - Gheg Albanian
am - Amharik
an - Aragon
ang - Inggris Kuno
anp - Angika
ar - Arab
arc - Aram
arn - Araukan
arq - Arab Algeria
ary - Arab Maroko
arz - Arab Mesir
as - Assam
ase - Bahasa Isyarat Amerika
ast - Astur
atj - Atikamekw
av - Avar
avk - Kotava
awa - Awadhi
ay - Aymara
az - Azerbaijan
azb - تۆرکجه
ba - Bashkir
ban - Bali
bar - Bavaria
bbc - Batak Toba
bbc-latn - Batak Toba
bcc - Southern Balochi
bcl - Bikol Central
be - Belarusia
be-tarask - Belarusian (Taraškievica orthography)
bg - Bulgaria
bgn - Balochi Barat
bho - Bhojpuri
bi - Bislama
bjn - Banjar
bm - Bambara
bn - Bengali
bo - Tibet
bpy - Bishnupriya
bqi - Bakhtiari
br - Breton
brh - Brahui
bs - Bosnia
bto - Iriga Bicolano
bug - Bugis
bxr - буряад
ca - Katalan
cbk-zam - Chavacano de Zamboanga
cdo - Min Dong Chinese
ce - Chechen
ceb - Sebuano
ch - Chamorro
cho - Koktaw
chr - Cherokee
chy - Cheyenne
ckb - Kurdi Sorani
co - Korsika
cps - Capiznon
cr - Kree
crh - Tatar Krimea
crh-cyrl - Crimean Turkish (Cyrillic script)
crh-latn - Crimean Turkish (Latin script)
cs - Cheska
csb - Kashubia
cu - Bahasa Gereja Slavonia
cv - Chuvash
cy - Welsh
da - Dansk
de - Jerman
de-at - Austrian German
de-ch - Jerman Tinggi (Swiss)
de-formal - German (formal address)
din - Dinka
diq - Zazaki
dsb - Sorbia Rendah
dtp - Central Dusun
dty - डोटेली
dv - Divehi
dz - Dzongkha
ee - Ewe
egl - Emilian
el - Yunani
eml - Emiliano-Romagnolo
en - Inggris
en-ca - Canadian English
en-gb - British English
eo - Esperanto
es - Spanyol
es-formal - español (formal)
et - Esti
eu - Bask
ext - Extremaduran
fa - Persia
ff - Fula
fi - Suomi
fit - Tornedalen Finnish
fj - Fiji
fo - Faro
fr - Prancis
frc - Cajun French
frp - Arpitan
frr - Frisia Utara
fur - Friuli
fy - Frisia Barat
ga - Irlandia
gag - Gagauz
gan - Gan Chinese
gan-hans - Simplified Gan script
gan-hant - Traditional Gan script
gcr - kréyòl gwiyanè
gd - Gaelik Skotlandia
gl - Galisia
glk - Gilaki
gn - Guarani
gom - Goan Konkani
gom-deva - Goan Konkani (Devanagari script)
gom-latn - Goan Konkani (Latin script)
gor - Gorontalo
got - Gothik
grc - Yunani Kuno
gsw - Jerman (Swiss)
gu - Gujarati
gv - Manx
ha - Hausa
hak - Hakka Chinese
haw - Hawaii
he - Ibrani
hi - Hindi
hif - Hindi Fiji
hif-latn - Fiji Hindi (Latin script)
hil - Hiligaynon
ho - Hiri Motu
hr - Kroasia
hrx - Hunsrik
hsb - Sorbia Atas
ht - Haiti
hu - Hungaria
hu-formal - magyar (formal)
hy - Armenia
hz - Herero
ia - Interlingua
id - Bahasa Indonesia
ie - Interlingue
ig - Igbo
ii - Sichuan Yi
ik - Inupiak
ike-cans - Eastern Canadian (Aboriginal syllabics)
ike-latn - Eastern Canadian (Latin script)
ilo - Iloko
inh - Ingushetia
io - Ido
is - Islandia
it - Italia
iu - Inuktitut
ja - Jepang
jam - Jamaican Creole English
jbo - Lojban
jut - Jutish
jv - Jawa
ka - Georgia
kaa - Kara-Kalpak
kab - Kabyle
kbd - Kabardi
kbd-cyrl - Адыгэбзэ
kbp - Kabɩyɛ
kg - Kongo
khw - Khowar
ki - Kikuyu
kiu - Kirmanjki
kj - Kuanyama
kk - Kazakh
kk-arab - Kazakh (Arabic script)
kk-cn - Kazakh (China)
kk-cyrl - Kazakh (Cyrillic script)
kk-kz - Kazakh (Kazakhstan)
kk-latn - Kazakh (Latin script)
kk-tr - Kazakh (Turkey)
kl - Kalaallisut
km - Khmer
kn - Kannada
ko - Korea
ko-kp - 한국어 (조선)
koi - Komi-Permyak
kr - Kanuri
krc - Karachai Balkar
kri - Krio
krj - Kinaray-a
krl - Karelia
ks - Kashmir
ks-arab - Kashmiri (Arabic script)
ks-deva - Kashmiri (Devanagari script)
ksh - Dialek Kolsch
ku - Kurdi
ku-arab - كوردي (عەرەبی)
ku-latn - Kurdish (Latin script)
kum - Kumyk
kv - Komi
kw - Kornish
ky - Kirgiz
la - Latin
lad - Ladino
lb - Luksemburg
lbe - лакку
lez - Lezghia
lfn - Lingua Franca Nova
lg - Ganda
li - Limburgia
lij - Liguria
liv - Livonian
lki - Laki
lmo - Lombard
ln - Lingala
lo - Lao
loz - Lozi
lrc - Luri Utara
lt - Lituavi
ltg - Latgalian
lus - Mizo
luz - Southern Luri
lv - Latvi
lzh - Literary Chinese
lzz - Laz
mai - Maithili
map-bms - Basa Banyumasan
mdf - Moksha
mg - Malagasi
mh - Marshall
mhr - Eastern Mari
mi - Maori
min - Minangkabau
mk - Makedonia
ml - Malayalam
mn - Mongolia
mo - молдовеняскэ
mr - Marathi
mrj - Western Mari
ms - Melayu
mt - Malta
mus - Bahasa Muskogee
mwl - Miranda
my - Myanmar
myv - Eryza
mzn - Mazanderani
na - Nauru
nah - Nāhuatl
nan - Min Nan Chinese
nap - Neapolitan
nb - Bokmål Norwegia
nds - Jerman Rendah
nds-nl - Low Saxon
ne - Nepali
new - Newari
ng - Ndonga
niu - Niuea
nl - Belanda
nl-informal - Nederlands (informeel)
nn - Nynorsk Norwegia
nov - Novial
nrm - Nouormand
nso - Sotho Utara
nv - Navajo
ny - Nyanja
nys - Nyunga
oc - Ositania
olo - Livvi-Karelian
om - Oromo
or - Oriya
os - Ossetia
pa - Punjabi
pag - Pangasina
pam - Pampanga
pap - Papiamento
pcd - Picard
pdc - Jerman Pennsylvania
pdt - Plautdietsch
pfl - Palatine German
pi - Pali
pih - Norfuk / Pitkern
pl - Polski
pms - Piedmontese
pnb - Western Punjabi
pnt - Pontic
prg - Prussian
ps - Pashto
pt - Portugis
pt-br - Brazilian Portuguese
qqq - Dokumentasi pesan
qu - Quechua
qug - Chimborazo Highland Quichua
rgn - Romagnol
rif - Riffian
rm - Reto-Roman
rmy - Romani
rn - Rundi
ro - Rumania
roa-tara - tarandíne
ru - Rusia
rue - Rusyn
rup - Makedo-Rumania
ruq - Megleno-Romanian
ruq-cyrl - Megleno-Romanian (Cyrillic script)
ruq-latn - Megleno-Romanian (Latin script)
rw - Kinyarwanda
sa - Sanskerta
sah - Sakha
sat - Santali
sc - Sardinia
scn - Sisilia
sco - Skotlandia
sd - Sindhi
sdc - Sassarese Sardinian
sdh - Kurdi Selatan
se - Sami Utara
sei - Seri
ses - Koyraboro Senni
sg - Sango
sgs - Samogitian
sh - Serbo-Kroasia
shi - Tachelhit
shi-latn - Tašlḥiyt
shi-tfng - ⵜⴰⵛⵍⵃⵉⵜ
shn - Shan
si - Sinhala
sk - Slovak
skr - سرائیکی
skr-arab - سرائیکی
sl - Sloven
sli - Silesia Bawah
sm - Samoa
sma - Sami Selatan
sn - Shona
so - Somali
sq - Albania
sr - Serb
sr-ec - Serbian (Cyrillic script)
sr-el - Serbian (Latin script)
srn - Sranan Tongo
ss - Swati
st - Sotho Selatan
stq - Saterland Frisian
sty - cебертатар
su - Sunda
sv - Swedia
sw - Swahili
szl - Silesia
ta - Tamil
tay - Tayal
tcy - Tulu
te - Telugu
tet - Tetun
tg - Tajik
tg-cyrl - Tajik (Cyrillic script)
tg-latn - Tajik (Latin script)
th - Thai
ti - Tigrinya
tk - Turkmen
tl - Tagalog
tly - Talysh
tn - Tswana
to - Tonga
tpi - Tok Pisin
tr - Turki
tru - Turoyo
ts - Tsonga
tt - Tatar
tt-cyrl - Tatar (Cyrillic script)
tt-latn - Tatar (Latin script)
tum - Tumbuka
tw - Twi
ty - Tahiti
tyv - Tuvinia
tzm - Tamazight Maroko Tengah
udm - Udmurt
ug - Uyghur
ug-arab - Uyghur (Arabic script)
ug-latn - Uyghur (Latin script)
uk - Ukraina
ur - Urdu
uz - Uzbek
uz-cyrl - ўзбекча
uz-latn - oʻzbekcha
ve - Venda
vec - Venesia
vep - Veps
vi - Vietnam
vls - West Flemish
vmf - Main-Franconian
vo - Volapuk
vot - Votia
vro - Võro
wa - Walloon
war - Warai
wo - Wolof
wuu - Wu Chinese
xal - Kalmuk
xh - Xhosa
xmf - Mingrelian
yi - Yiddish
yo - Yoruba
yue - Kanton
za - Zhuang
zea - Zeelandic
zh - China
zh-cn - Chinese (China)
zh-hans - China (Aksara Sederhana)
zh-hant - China (Aksara Tradisional)
zh-hk - Chinese (Hong Kong)
zh-mo - 中文(澳門)
zh-my - 中文(马来西亚)
zh-sg - Chinese (Singapore)
zh-tw - Chinese (Taiwan)
zu - Zulu
Ekspor untuk terjemahan luring
Ekspor dalam format asli
{{DISPLAYTITLE:Analisis Data Epidemiologis}}<languages/> ==Analisis data menggunakan studi kasus data iSIKHNAS== [[File:Autoship1256.png|120px|left]] === Prasyarat === Pelatihan ini disediakan untuk para dokter hewan yang bekerja dalam sistem pelayanan kesehatan hewan Indonesia. Diasumsikan bahwa para peserta telah menuntaskan modul-modul pelatihan ''Excel'', ''Epidemiologi Lapangan Dasar'', dan ''Surveilans'' sebelum mengikuti pelatihan ini. Apabila Anda telah memahami tentang epidemiologi dan bagaimana menggunakan Excel, modul-modul prasyarat tersebut tak lagi diperlukan. === Objectives of course === [[File:Target colour.jpg|60px|left]] The broader aim of the course is help participants make evidence based animal health policy decisions. This will assist them to improve livestock production and health in Indonesia. To do this, participants need to be able to access, understand and analyse information on animal health in Indonesia. Fortunately, a new initiative in Indonesia means that Indonesian animal health staff has access to one of the best animal health information systems in the world: iSIKHNAS. This provides staff with large amounts of high quality information (data<ref name="ftn1">The Oxford dictionary definition of data is: Facts and statistics collected together for reference or analysis</ref>) that they can use to make good animal health decisions. Therefore, the objectives of this course are to teach participants to download, understand, evaluate, analyse and interpret iSIKHNAS data. === Learning approach === [[File:Nuvola apps edu miscellaneous.png|60px|left]] This course will be taught by analysing real iSIKHNAS data. Three case studies will be presented. During each case study, a question will be asked. Then the question will be answered by participants during practical exercises. Spaces are included after each exercise where you can write your answers. Answers to exercises are provided as Appendix 2. It is generally recommended that you answer the question before reading the answers. Sometimes, notes on core concepts will be presented before or during case studies to support learning. These are backgrounded with grey to enable you to distinguish these notes from the exercises. The course is very applied and relevant to Indonesian animal health staff. The three case studies concentrate on: assessment of veterinary services (staff performance), disease management (diarrhoea in cattle) and livestock production (beef self-sufficiency). The data used in this training course was downloaded in early 2014. This was when iSIKHNAS had been operating for approximately a year in a small part of Indonesia. This early data was used so that we could provide answers to exercises. You may wish to download newer and more complete data to analyse during exercises at the time of your course. Please be aware that if you do, you will not have answers to check your work. The interim nature of the data means that no real conclusions can be made about the results of data-analyses conducted during this course. Instead, we conducted the analyses and made conclusions to demonstrate and teach data analysis. Over time, more complete data will be available. Then Indonesians will be able to conduct more complete and accurate analyses. The course is delivered in Excel. Excel was chosen because it is cheap, available to most Indonesian staff and intuitive. Analyses in Excel will allow staff to make some useful conclusions about iSIKHNAS data. If you intend to do a lot of important statistical work, you will need to learn how to use a complete statistical package instead of Excel. For this reason, we have also included some extension work for those participants who wish to extend their knowledge beyond Excel. This is presented in Appendix 1. Here R, a free online statistical package is introduced. R is one of the most useful software packages in the world. Better still it is free and downloadable from the internet. Appendix 1 repeats case study 1 in R. Many screenshot videos will be used to assist you in understanding how to do exercises during the course. These can be played on several different software platforms including Windows media player. ===[[Data Analysis Facilitator material]]=== [[File:Nuvola apps edu miscellaneous.png|60px|left]] === Overview of data analysis === ==== Relevance of data analysis to animal health policy ==== In order to make good animal health policy, a veterinarian needs to understand the animal health situation where they work. For example, how much disease is present? Or, what is causing disease and how are various interventions working? To gain this understanding a veterinarian could guess at the situation or they could make assumptions based on their own experience. These are generally poor means of making decisions. Decisions made by guessing are made in the absence of information. Decisions made on their own experience can be useful but are generally based on a very small amount of experience. That is, decisions are based on the experience of only one veterinarian, even if that veterinarian is very experienced. A better means of decision making for veterinarians is to make decisions based on information that reflects the broader animal health situation. This information can be received in several ways, such as in animal health data, publications, text books and reports. Fortunately, animal health information (data) is now being collected across much of Indonesia. This data is recorded in iSIKHNAS. This data can assist good decision making if it is analysed and interpreted appropriately. The broad objective of this course is to assist you to do this. Whilst you will learn a lot in the next several days, it is important that soon after completing this course you begin to download and analyse your own iSIKHNAS data. This will ensure that you consolidate your learning, improve your skills and at the same time improve your evidence based decision making. So please, set a day aside next week to do some of your own data analyses using the skills you learn here. Then regularly do some analysis of iSIKHNAS data. Over time your skills will improve. ==== Introduction to the basic steps of data analysis ==== There are several recognised steps to analyse and interpret data. These steps are determining an objective for your analyses, data management, describing data and testing hypotheses. Each of these will be briefly introduced here. Then the rest of the manual uses the four steps in the case studies. ===== Objective ===== It is important to have a clear and concise objective for your analysis. For example, what is the prevalence of diarrhoea in cattle for 2014? This then allows you to be focused in your efforts and to source appropriate data to address the objective. An objective is then translated into a hypothesis and tested. ===== Data management ===== It is important that veterinarians know how to access iSIKHNAS data and use it. We will help you to download iSIKHNAS data. We will also help you to preserve, error check, create and evaluate the iSIKHNAS data. ===== Description of data ===== The next step is to describe the data. One purpose of this step is to further check data for errors. Another purpose is to understand the structure and nature of data and the relationships between different parts of the data. In this step, single variable summaries, summaries of relationships between variables and plots are used. This helps you to start hypothesis testing (step 4). ===== Hypothesis testing ===== In order to comprehensively address an animal health question it is important to develop a testable question (or hypothesis) from your objective. This hypothesis can then be tested using appropriate statistical tests and you can decide whether the data supports your idea. [[Data Analysis:Notes Sampling|'''Notes: Key concepts for Sampling''']] ===Case Studies=== * [[Case Study 1|Case study 1: Performance measures for veterinary services]] * [[Case Study 2|Case study 2: Seasonal prevalence of diarrhoea (Mencret) in cattle]] * [[Case Study 3|Case study 3: Beef self-sufficiency (based on slaughter statistics)]] === Concluding remarks === Data analysis is critical to good animal health management and policy formation. Indonesia is fortunate to have an excellent and newly functional animal health information system, iSIKHNAS. However, it is no use having one of the world's best information systems if no-one uses the data. Hence, this course has focused on helping you to begin to use iSIKHNAs data. These approaches may help you to improve animal health decision making. There are several standard steps to data analysis, including developing a research question of interest (objective), data management, description and hypothesis testing. All of these steps were used in this course. In order to consolidate your new skills it is recommended that you apply these steps to questions of interest to you immediately upon your return to your workplace. For example if you spend a day or two per month for the next several months you will consolidate your new skills. We have only had time to use a fraction of the available statistical approaches (e.g. measures of association and a chi-squared test). You may choose to expand your knowledge beyond what we have learnt in this course. There are a number of useful text books that can assist you in developing your statistical skills. ''Veterinary Epidemiologic Research ''(Dohoo et al., 2009) is a useful text book that covers veterinary epidemiology and presents some statistics in this field. ''Statistics for Veterinary and Animal Science ''(Petrie and Watson, 2006) is a useful text book that applies statistics more generally to veterinary science. If you decide that you really want to learn both R and expand your statistical knowledge you should complete the appendix on R. ''Introductory Statistics with R ''(Dalgaard, 2008) is a very useful text book that introduces both statistics and R. If you start using R, then the statistical world will be at your figure tips! {{fpblock|Appendix 1: Extension work using R.|Nuvola_apps_kig.png|This appendix introduces the reader to R. It is for those course participants who do a substantial amount of statistical analyses (or aim to) and wish to improve their capability beyond what Excel allows. There may not be time to complete this appendix during the course, but it can be completed later. R is a statistical and graphics software environment. It is widely recognised and used throughout the world. R provides a very powerful and flexible environment in which to conduct simple or complex statistics or to produce publication ready graphics. It is also free, and constantly updated. It is widely supported by a range of scientists who are constantly contributing new packages that expand the capability of R.}} {{fpblock|Appendix 2: Answers to Exercises|Themes256.png|This is where you will find the answers to the exercises in this Data Analysis course.}} === References === Dalgaard, P., 2008. Introductory Statistics with R. Springer. Dohoo, I., Martin, W., Stryhn, H., 2009. Veterinary Epidemiologic Research. VER Charlottetown. Petrie, A., Watson, P., 2006. Statistics for Veterinary and Animal Science. Wiley. ---- <references/>