0% found this document useful (0 votes)
50 views73 pages

Bio Statistics

1. Statistics can be used to summarize collected data from a sample population and make inferences about the larger population. 2. Common statistical measures include the mean, median, mode, range, and standard deviation which describe the central tendency and variation in a dataset. 3. The steps of a statistical study include developing a research question, designing a study, collecting data, analyzing results, and presenting findings.

Uploaded by

Shivani Rathor
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
0% found this document useful (0 votes)
50 views73 pages

Bio Statistics

1. Statistics can be used to summarize collected data from a sample population and make inferences about the larger population. 2. Common statistical measures include the mean, median, mode, range, and standard deviation which describe the central tendency and variation in a dataset. 3. The steps of a statistical study include developing a research question, designing a study, collecting data, analyzing results, and presenting findings.

Uploaded by

Shivani Rathor
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
You are on page 1/ 73

Bio -

Statistics
May 3031
siii÷%•↳ →
statistics
-
→ inferential
collection
[
Auston
↳ 1hpm Mdot
-

Doty → sinan - Dohm

Numerical output from

the inborn

¥→ population
→ sample → statistics .
Sample → Porta population
Variables
-

-
subgroup.ms 2 Dataset

which dots will

*"""•*
on

111
be collected

|E÷÷→÷
Researehseuestim
Burden

prev-olene -bm⇐-ñnuom⑥is→gega#_1ntewnR①
smua.ycatagon.co.in#reans. →BYtitohh-g

btw group

→ndi±i
&÷¥÷ad
-

Intend
→-
N nominate → forerunners :*
-

'll .

Relight
"" " →
¥£%%→ ""

I - interior
→hM•8)
R ,
-

Ratios →
TuneIn
/ Ratio
meaningfulis

Lezsudwirscole

Age ,
wt
→ An meti.ie
?⃝
population-TP_3?Som①→sTuDy_
Technion
(
Questionnaire
↳ validate
Representing
YIN C
Pretesting
↳ Final questionnaire
RI> Sample
↳ Data collection
=/ study design
a-
nmrysy Coding / cleaning
# ¥5m =
-Desxe

(
-
Total Number
-

all measures of Analysis


association
-w%- ← / frezncsareharaelei#
tinware
- %

www.mE-M-WM/IEEI,1mgdfenuyy-0R/HR/
RR

Presentiments People

Beushopedlaausin.cm#(evo1utioi)
I
:÷÷

-ispersinn#utodatd

¥

Range Cmax -
min )

→ Quinte
→ SD
.

÷÷
comin wtf variance
'

→ IQR
-
mean =
§ re
,

central
lending
-

median anonyedrtn
a-
-

Take middle Blake

→ h is ODD
→ middle
-
-

valm→¥¥
↳ even → 2 middle

Mode →
Frequencymost)

ÉÉ→É
III → 2 / €512s'D

E4
-

Degreeof freedom

H"•mmmmTsrasl
D0①

nttehs
from nineties thee to change e- out

Freedom of changing blues .


Ban-diazronsm@simple-TTpp-EI.n
|
_D¥↳$
s{ "
-

component
① -
Continues Tables
Ilium } .im/.. . . T?# -
Multiple/ LMD
grouped

④ g,an,gyp ummmm,

③ -

BMDiazrom-catezom.CI/-tlistoJnom-
continuous
Proportion
⑤ -

Piechonh_ →

ChhunMatusek
exclusive > ( Not shared
⑥ Xiolenep
(FENCE) %É?
/ BI → 6 -11.5¥

/
⑦ 75
Honest
BET
-1

-12 SD

Aspersion
* Dota ) *

:#II"•
- 27s

g- -
ZID

man ,, ,
y, ,

,,
,ypg
is

Botnsi←
cute Connel density
[ violence plot
?⃝
?⃝
Staton →

- Mex 8 Words
iionsfglensmm
↳ No space

Neumeier
-

Flot > ✗
-

→ length of memory
→ ( 20 Bite

string
not Mumba
-

lobeu@
-

→ Bly
-

Tob -
Category Canon guard
I
aye Doby
↳ mean , sp

↳ Max , min
StA
Time
webuzeaqto.dk
→ "" "
"" NUMr__
Float
→ codebook
← Double

( missing value → ☐ 0743 Integer


Byte

Sumlcariosk ,

I
-

Skewness → displacement
µ towards -

Rtlt

UP Down
1 KURTOSIS → on

plots -
Flat
Emi
-

Tobwb@ → only ton 2b€


Toby Vani
id Vaz
-

N Tob He

→ Tab V2
?⃝
idiesoubk-%8a.ro#

|
t
8mm ⑦ vain
began • Wadhwa
decimal >

② bn . ( Browse]
-

Wetsuit bpw :#e. to

⑦ Dobie
,HY9

?÷÷
Dotes

÷÷÷
"

Probability z

Total movements possible

÷Éplos§
✓ CErea.vn 'D
1100 f- -

100 ""

Mathematicians
.. Do

&
YE.FI#r.j-PmmB;;:---easmsns
cares
followup

:÷÷j"" µ;u
.im

t.ae
y

# o

5- (a)
/
PCA) AND PCB>→ PCA> xp (B)
P (A) PCA> OR PCB)=P(A) + PLEA
mutually

e×p%É →n→x
9
Iefmutuollb
¥i÷i¥ .

④③
-Biusm ① two possibility
31¥ /
PYI.IE??LnpufitP%1be1w@coueeths
\
§ - - - -
-

n
large Number
geum
-

ÉÉ
?'mem cn*
'
-

wormy Continuous
✗ Genuine>
-

, →
n(P)(tD

poissondistnitntim
When his very large

nap see -1

NPL lolsmouriwdsa)

b- variance
-
- up

= nltp) P

③ Peace ↳ so (1-11)=1]

-duiak
÷÷
*
Nokmnrbistnibution
5- in =
1- ✗ e- 24¥12
"
fmmmlsrm
6ft
internet
FE :D :

¥¥÷A÷÷¥
68.27%

SD
.
I

7-

ynpnmlf

"Euu=ieemti¥e÷c÷ on-BKslim.niii.
o# pipin.ii.im
STANDARD → k=o

NORMAL → s D= 6=1

cur -
-

i. sD=G=sE=
.

=
e-
kid

ai i i -ui.is#istomdars@distnibutim-U--o I

{ ③ %-)
° "

⑧ Distribution -_
u SE =

É÷u
a
Number

Pj¥ →;y±tai
h=
armies
-2


mLi÷÷:
@ - Distribution neon

Std Norman >hibutin


?⃝
?⃝
?⃝
heady
Central limit ther

|
→ SE =
÷ SIII-mnit.nu time
n-sm-EI.ae
ahem Lions Bootstrapping
the Number
or
meat melon I
Cheong
b
-

PoPUatimMbmED
Ict ) rise To capture

C. : sample mean I Population Means


@ I
> ¢-4b

caleulafim-htfg-M.ir
Noon ( Jackknife .

-
Mean of Means I 2 5. E. will contain

population mean

SDNDisptgbuhmnmesm-sr.hr
- SE =

µ
means
ñmmñ*ib÷::TIm↳se very limited

1-
Distribution

not
min

CPM
/ PERT

ggthsdfoms-iex-ecni.us
( cmitica Path (Program Biealuatth
DDtnibulimaamma-J.EU
,
:( In Markov
Modelling
sittin

⇐ =: ① shape
☒÷
÷m
¥ÉH¥m
dirt

:÷÷:
hypothesis
alternate →
A>BA

II-ism-sim.sn what is Reality


.

A- =
Beevers

mi:÷ PEN FAN


* Wd

hEfY→DRUhTm^m→pk yap
dignity
stntitto
f.
Reset A- i¥÷w ,
Input

P-x→ ¥ tu des

resutbjustbygme-9f-Tnraetciy.tn/
Pao bob hits of finding the

samenesuT
€Éir→☒
/
AFB D > o ( two tailed s
HA
[
A >B

AAB > A
D

dove
④we
}&iwpetoi¥

÷÷÷÷÷÷•=÷
too times ,
-58times

Atget BycHAME_@@
\ .

FIEHTIE.nu
-
lent

change
mea@ :# most

chords
Il-sung

Q-Q-plot-yn.mn
÷.
e-
plot
Naruse
di> timbal v4

Quitter

÷÷
→÷÷÷÷ → Symmetric .
-

→ histogram Vario① ,
frequency normal

→ @ -2 -
plot)

JFK

-

Was to convert in @ Distributor

P
UNI 7 (
Nonnus
-

Non - Normality Can't be


Ruled out

④ Swivel

G- surest
-
Relationship b/w 2- continuous

BOBBI vamssu

→ Ploliyoteoen nonissue
another vamssre

in a
continuous dataset

by sont Kay : sum


VMI,

t-estkq.mf.by Gina
-

- Histogram var
, ,
frequency normal

11th't Varian
y

Scatter Yan ,
Harz
Regression

mean.tn

Independent

Thi; internet →
Correlation Krissy
constant .
*
changes depart
-

→ scatter * ix. variable


a-
regress Yu
PREDKT1Ñ②


÷

↳ logistic XY
-

continuous g. neon

vmio@
→ .

Dependant →
→ Hastie
→ categorical >
-
S.N. Dwivedi

NM-noumotdistnibuti-fscentnss.dk
]
-

endemics →
Medlar

pmy.g.my, ,
mug
,

-
Geometric men

Zayn
inrush,
-
-

hyperion .


|f expmatm

⇐ ve
seemed
102
,
ya risk? T
,
to know the

gladly →

requiredthorns tarot
2nd class Dale -0411/21
Test or significance
e-
test
Wheater there are any

difference btw -
2
Jumpy credits
(0^05)

/
95%
✓ -
-

✗ -
To Zenon (1-2) significance
-

Could dem
p Ts I earn

YETI
- -

↳ 20%
I - B) = Power

→ 80%

Tgpe errors tummy study


-

95%CI&@
IH6¥
Pop .
mean

| §
n - so SE =
is there .

S D= 2

→µ 2et)
run the test too
G- =
-1-1.96 ( sr you
will
time 9s times you
I
1.96€
,
=

the same result -


-
.

sE_→ ( population]
Mean

:#
r isapontion =¥- P¥ =

d- war :#on
=

¥t¥
dittmar satin
-_P¥÷I
?⃝
Luohitortiue If
\ -1
Quantitative
±④uÉ_É* 42

÷÷: Matched
" """" """
"

/
waived
ta
Jhowp ( Paired) .
simkont
eat

" Test -

" """
Two way -
Chisum
""
Repeated Mearns
( m pggneyy
RMAN.ua
test
-

Ronusum
c.
manner - sizumlnswu
<20%Ñ? Test
onerous CMWUT)
f. Exact : .

e. ÷¥
group Matches
- → cochroufe-fniedm.nu
> 2 > men # Test
,
-
Unprofor -
cnisi KRUSKAL

1m¥
¥

?⃝
H&m - Normal /Nonpmomoh.§ Parametric
InHisYpptio
^

ordinal
^

.
Nominal
- Uh

chisgff .su Wilcoxon


-
Random Paired -1 / 2-

28oupsilhw.ms?II-
( MW UT )
test


s.in#McNemonileoxanRannsi@nPoinedt/z
Matches
test
n

yzgnoc.iq#--Unmat-hedihisifi--mtk~sbtwon
matched c. crane

> McMann
Friedman
→¥I¥mµ
→¥÷¥
measure
!
N

"
( Il RD > 2. group)
AN0VA_

(£milm
vvcinhsvssle resn-bs.sn
hommes

Singhelneasmeonontndlvorianu blockhouses simians


rgnemms

depending Mone variable b



BARNET
Test
→ overlap b/w eachother

dim
-

onesfthesmnp is significantly

( cont specify

www.nmn#iIi:..E.:E-ei-!I
-

{ s ? Chi D
.im#iantsomit(ws )intnazrup
- ¥1s


/
variability

? variance (k=2hshp)
is -

Ch D= dt n= number in

|
-

N Inter 2h04> dit b1WNedI


energize .

D- e- ingroup air


my fF→statisie¥ ,
ChiSqTest_ nominal data
( frequency
, Percentage
%
vaccine

±
Expedience
2_
add

?÷¥÷÷f÷÷÷÷÷
36
:*
* At • • is in

90 86 ☒6 71.6 "

68,4
2
✗ =
{ (0-E =
f@bseaue-Eraai_fE.x
pecks
= ÷÷"+¥•-¥÷+ +

⇐%:÷
= Or 70 0 74
+ .
+ 0 -
19 0 . I 9 = Ii 82

f-
Vmn µ
.

= him = how Maram

C- =
Colum Marina .

Po f- @-17×4-11 =

-
I

www.ismwnm
2 '

✗ DE
'

I o.se#--P-volue--
118 5 3.89
Chun hypothesis]
I
accepted
Mrtsinihbrt
p-value
.


-

dt=2 ; 5.99
Onewas
-
-
ANNA I
-

Barletltest → variance -

dithering
(pi)→ Hull Hypothesis
Tires
ANOVA can't be

applied
=

ANovA_ Interpretation
difference in somegroup
I
can't specify

1
① P•stHot
-
Bon beronie Test

t¥¥mt) Cone way ×, vie,


Bon
live correbhhlabbiwht

et↳a-sq-dvartosl-si.org
.

Anshe coming
)
try explored by others
vanish .

oh = or 6
; HE 0.36 ;38

BIwsmmpsumof.IE ,
Total sumn S2
-

( Tss Between -1 e- in
-
?⃝
|
"

zq2754-31.ie#-X9+@.s4-2-osxn)
( ↳ .
54 ✗ 29 , 6 2) ✗ I 6 + (9-54-28.4)

÷¥⇐÷÷÷÷÷÷÷: + (1.6832 ×
967) + 783T¥
?⃝
"

yoz "2"yoÉÉ
"
"

-
label define Harsh 1
-

-
label
Volney YI
Aff
-
clonevar V
,
=L

Fba twill be preserved

↳ To adjust-l
Correction

{ >
t.hr
Multiple
22mg
.
.

÷
compmismarmeom-gou-HRGHAsorsimih.com
)
means
condone
→ student t-test

- 2- test .

-ANoM-Ir€
¥pñmm
17 ① FIXED prescribe
mean

poputottm ↳ www.ismrmemfthe

±s☒mn¥→=⇐ÉÉÉ%IÉ
SD LPnt
Iot knot
↳ biwtwodiwsmnpv

Pretorius


Normal distribution
independent / Random
-

-
datnisu

IimumeeruoÉ→ There is no difference


* → Null Hypothesis →

Parameters statism
population sample
M

o SD .

02 sD~
÷i÷i

|

÷F÷
1 = Pre 2= Post

L-ft-estvmbbs.ae#
,

.
-

2
t →
test van I ==v or

TYIE.IE?t#mim-inm-equol;(pso. s)(t- st;p-


value D)
it " minimum

d- error T
LEVINE 'S Tests


problem von 1 = = van .

P>oo*5_ → uneven
various
I
ttestvar2-varzunei.ua
Mody WE

AN0VA_ → ④ > 2 Snap


AndwioR_U
wsts-Y.IE ,
square
vt
-
THIRD CLASS

Correlation →

it oneroniobhe is moving,
other
should bethe
where
ikari Nb Me .

Variable
hubs he dlt change in one

-
change in other

storearlinearbeotoit
A€→ correlation
c. -
etoiient
to
C- 1

K -0
E o
k
v MBK
Reardon → unit cohoyeih Ee .

in than Hr
↳ Change 0 van .

mrthemenzolcoknlahh.it#--pn-.ennm(P-eoe-raiu '

at
=⑨E¥€
f- mx -11C

nm=a|"7÷mdda
Ccotnsonilollvahiobk (continuous
variable

( Product moment

÷÷÷ ¥#
dependent y ,
independents
categorical /m( Binomia
%In¥FE$÷_
toakiergreniy-p.n.i-pzm-t.KZ/ny=Qpm+p.m-i. -. -

¥DDÑo.
E

may 9-L.kz
-
Regress •
?
T ki

Dependent
vanish
( 3- D- AMY

¥Ñ IF
•*?#,n
' ( OED
+ pint - . - + ←•

'L¥¥"I'D
,

-
Deeendht
↳ ios as Ratio
?⃝
wait ask
logistic foreign mP2_

errors

coeboicient of defter mm ahh


-
R' =

Cronkite)

explnies sOtnerrxn-skR2o.yo.5@CR-crelbicientnrc.net
be
one can
% Change of

aepybo odmodd-LR-DDiamosti stid.ba#DPnobab7i


Presence
Bothering
thedis eons ibtutest
112*3 → =

or Dixon
pm↳wi-bnÑhb
the dis een it # test

absence -14 is
Lr t →

tenobablity.hr host having the


±
diseoeiothethAtesi
(R¥xt•T Probables → hovis th
disease it the test is
Ratibor
( Éclat A) includes
>
95% CI
⑧ssizitiu①
Thot

- Continuous ED
vwiosu-syosy.cz >

linesurgremm includes Zero

-
④ 20h É
h -
'
d
÷÷÷÷÷÷÷÷
:
"

¥2656

ZB 10% 1.282
°
/
24.2 2241
n=so

÷i 55170
CI /
Dotes 11121

3ndNi"mÉ?É
-

[DE=1+p(m
3 months
-

why

pop ?
-

⇐ CP
(1-125)/120-12,7
"

h = (ZqztZp) [Roll -
RD -1N ,

=
(1.28-1.96)%[2.5×0.570.714.7]=1
=

(3.2+9)^-1%101742
n÷÷ñ[o*;÷I
=
262.44 (0.2275+0.2475)
0.475
= 262.94 ✗

= 124.659
DE it Plm -
1)
= 4. o 62s

e- ÷÷
Or
0625×0*5

C. =
¥j2¥÷ [025*+0.49]×40623
,

=
'

15.8

=§÷Éa6s+ o.si/o.4-Dxa.oiy

=
10.13
⇐ a
"É÷÷*
357
( it Tho 0 .

=
I 7 . 1
0.50)
= 12 •
3 ( it to =

n=(Zm+z•¥¥?+""_
T
Population
in
each
arm
0.35 )
125 ( it to =

In

( if no = o -
5)
I 192
) in the
Tho
True proportion (Population
12 , ,
of
Presence and absence
intervention ,
respectively
clusters required per
→ C =
number of arm

Population in each cluster


in =

coebricicnt Anemia
tin
→ he =
-
F- Y÷,
Design effect It p (m D DE
-

C
Cp.t.FI#(RltA7-PzU-PzD--r-
-

g)
%" "
"
"
" + °
=
=\ "

k = 0 . 25
M = 5 o
,
,

P = 4.0625 ,

gp, ay ,
g.

The = 0 .
-5

Intro cluster correlation


p =

individuals per cluster


m =

number of clusters
C =

in absence of
intervention
The Proportion
_@→mm-④

-


T±tr¥=

6- seeded
1-
Saison
3- ☒ fun texted:( an

Eschete
RIT -

types
-
Don't write bun sentences

only Ys →

HI
- HIV -
Malawi
Polices of (window Period
-

dilbenmt-itatentf-eooat.in put impact


-

output

⑧ → statistical - sperms

-
accepting → selts① /

p↳,ibil →

→ tomes to implement .hwWkelw@


→ contamination
|i÷
Power 88%
-

④ Boencoecrtoled -

÷

-
faith than ethel- Outcome

↳ independently
elveotoutcrn
↳ Randomly distributed .

⑧ → Reference .
-

¥,
15€

14 =

Or 099

14 ✗ 0.04=11.96-17 # (0.005-1.0092
+
0.09625)

• 1%1%-5=146 -14T¥ .ua

10^0991005
=

-3.1779-1-96
=
=

evolnrtimheolthpryram.EE?pu.cpehin#
6m¥
→ Direct cat, indirect

↳ 1- opportunistic
momma ,

cat .

-

-
¥±i¥÷÷
PN-hscA-fs.si
-
-

India → ACT -

ron①
(
→flow-2mm- -
calculating

Conrad

-

www.lndea-lbonehm
→toms]→
j⑥ → docnwiedotn then
soo

⑧ → Not much tittering


☒ s ADD s albums
les und 7 71
litanyLAD .

# mean Grabs :D
geometer
clustering
- -

É
= k =
£ =

Howtocdwbh-④ = or
I 3

L
Fidelity
m-

-

Heard a set dialed


THIS →
in
mobilisation
ED > community &tris study

↳ vertical distribution
Kaiiae
disirosV①
=
-

Social diehm its bias -

Socially

A
in reality _-

they are outdoing it ;

Bias _ts①
-

⑧ → Blind wound - PmI_


c.nl# Date →
17/11/2011
Diagnsstictest Prevalence =a
-

✗tbt Ltd

É÷É÷¥÷:÷+ ¥÷ñ=-¥

µiña
hold std test T

÷÷i÷

|
I¥z¥÷
,
+e*:÷÷t÷
pprlnonizm ppv
=

NP " =
¥÷Tn =

likelihood Ratio →

LR ⑦ → *
'
in the pnrboblityofthediseoneisttest
test-0
I ' , ,

LR -0
,
" i s ,

- ,

Ratio
{R,-
Dor - ( Diagnostic ODDS
=

iR④=÷*=¥
-s÷
'
LRG =
=
-
Sn T FN I

-
Spin FP I

ftp.?ETnT-TBg-
test
-
→ Highly specific
theDisease
mirror it ① Rules in

[ Highly Sn test it
→ Rules
out

the disease

TPI-ptFNLR-O-I-p-FF.fr?-+---FP/fp+Tn *

ls (÷÷×÷-÷)
::::÷:*¥::i::+÷①
LRO =
=
✗ *P→#=EY,%
TN

:÷÷::÷÷÷÷÷①
.

for

=
son

DOR
→ Range (0-10100)


LR

LR .
-0 <<
>> I
① ↳" →
Test
'

.µq*DioonoÑ£µq°""?§p÷¥÷+ N )

÷÷p÷÷;÷÷÷:•± windy
:
→ Perpendicular missile
to carnie
target

÷÷÷E¥
g- Younden'S Index (Panama to
maximum Y-axis)

}
= Sm - 4- SD
µ
" "
=&n+sp D
:*:*
-

men
mm

"TwYÉm
opTmumcuT°

Stftliyhen ( 100%3 ⑨ dmin


Jmax

|Ra→cm×esmo_
"
Dmiy Jinx
i
÷ i. s#
Blood glucose -7 point .

d min
optimum cutoff point ↳
Imax

www..E ?I m-ew-ie-,s$ph-sbet@-(AUc)on(sn Diagnostic studs


samplesize

BayésThe0be# conmtioNA-probb.br
Prevalence

{
Pretest probability
=

pEÉ =¥¥?É¥+ñ×xñ
-
Post test Probability
=
N
PPV =
⇐?¥mIIF¥%→.p!÷÷¥
pre ✗ Post

T⑦÷Éz

i÷P(µ•④↳
-
-
=

=PE4Ñ✗P
Ma

iñzIñÉ¥i if pus ,
-

PET / g) xplñ)+PHD×
-
-

i. - - -
-
-
-
-

pciD-Bayebionsto-i.li#-it-sP=-estdEi -s/-npv--
¥¥¥¥→ñ
Prsbohistie

{ "
-

Theohitild -

Number -
Detent "
Approach
-
Prim ,
- Boysen
conditional

proboblitg-ggremhrt tnolb.gg# Cohen's Kappa =


aggrement

too -
assonant
home

aggrement
by chance

aggrement aggrement

D-I =•÷;÷EIE¥
expected

T.FI#.E.!-iBychonu/exPut Pe- lrmY-)F.


④ =L:÷)

Poz @ to
at
'
-
① Test, for Yali deity → Chambrun

( Internal consistency

_diagtioo17l14#
↳ diagnostic test → SP
Sn

→ ¥1 → ⑧ ppv
Npv

AMIE
÷ :☒{÷:÷÷☒:
p -

-
t.ba#
eif Date -

22/11/21
Day -8
-

Survival analysis

÷¥%•si④ Time to event


-

µ
outcome →
- - - - - -

+
- - -


- - -

]
slt )
→ longitudinal
Romaine '
cohort studies
zsII → Prospective
°
Time → Trials

l o ssto.t / - ~di w i Kd*#mi ta t i m NbyDota -~


't

÷ →d

UY / § ->Ri2h÷

/
g. ma ,

← period

intend - Don't have outcome


Data ~
""" ""
"
"" '" tomah""
Finite'd
" "
"
Don't " "
" to "NM-
*
Data of and outcome
Both exposure

ef.FI?I-.mpato-uotggoi1obkofHlv
es >
poticmtqye_→
Sx -¥ .IE#mevencame
Patient

Time event hnoup


-
⑧ lost to Followup
- asNoeye€→iuthat Timeiutayoy


-

Dichotomous
① ⑥

E¥①t¥
?⃝
South
North
,
no +s;gmWcmtDiwevn#
y

f- f
sit . - - - -
- - - -

Nlt) Sct

time


Mediomsmvivaltimeo 5
of the
↳ length of at which
-

time -

survives
study population
outliers
→ mean is affected by

weusemedhs-sl.DZ

r - . .
-

.q→ so, attueendohthestndb


Porta the population is alive
t
↳ Survivor
one

time is not adenine

É¥Éz•-
: 80%
so
÷
L von Laar .

:¥÷s:
L 20 IF

→ I B-
¥1 ✗
60¥
¥ .

I 7- E.
?⃝
{ ÷÷÷ñ÷÷÷}→"T"""÷÷÷:

i.im#wIw,0DDsR-atfo=inmeznoup-
merion

;¥÷÷¥1m
HazmdRN→
↳ shown in another
i group

i. -
- - - -

Sunita function → s( b)
Cox →

bunch 'm → h (f)


↳ hazan#

{zn-EEFF.si#:-ET
-
confounder

mummy
-
Adjustment
USE__

§ -
Allen's edit've
model

:* -
§ -
stset van
e-

-
Stum

-
Sts graph by 12m£
test Jump lrzranu .

-
Sts ,
-

↳ pirates Chih
Date -71/12/204

÷÷ f.
any somplesize.cat#alm-
CASE CONTROL Cotto RT RCT
CROSS SECTIONAL
-

categoria
variables -
Proportion outcome-7-exp-wept-yposme-outcome-n.pl
" → Proponlimrfexposureiu Care ,
Prspontimotoutcomeiuexposured -

pz
^
" PM "
1%1 i N "E✗P "

ppgpo° (P ,
-

"
Pz)
-

control
.
-
on
i.
-

→ ,

-

or Relative Risk -

¥µ p
-

/ ZB
-

→ Population
1 ? M

p-=PiII÷
in 2-
)
( I :b
-

I
%
exp none xp -

- m

-
% care :
control
i
Frequency t
is -1172pA P) ( 71+3+2-1 %)

"¥É¥÷Én÷÷÷
-

Fi
"

IñiÉ:E P=
f÷¥¥9
SD N
pilot study

µNTÑ↳ p
"
÷:
2 "
""
"

ñ¥
T

Diagnostic studies

n=Z4÷z
B

sñhgonyone
Sp
margin Gerson
=z2%f
1 : h

Intervention : Control

?÷aionibtm#

÷÷:÷÷÷i:÷÷
( Intervention)

no

( earth)
=

⇐Y;¥g
lnbehiohi-s-n.hn
-
Equiyalen e-nioyn-t a-Z.g ?f.gIo#no=(Zx+Ztk
)Y-
( S HD2
-
+

*÷iiñ>÷*÷ .

You might also like