Me a sure s o f Va ria b ility L E CT URE 4 Ob je c tive s De - - PDF document

me a sure s o f va ria b ility
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Me a sure s o f Va ria b ility L E CT URE 4 Ob je c tive s De - - PDF document

Me a sure s o f Va ria b ility L E CT URE 4 Ob je c tive s De fine te rms. Dia g ra m re la tive diffe re nc e s in c e ntra l te nde nc y a nd va ria b ility. Ca lc ula te the ra ng e , sum o f sq ua re s, va ria nc e , a nd


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Me a sure s o f Va ria b ility

L E CT URE 4

Ob je c tive s

 De fine te rms.  Dia g ra m re la tive diffe re nc e s in c e ntra l te nde nc y

a nd va ria b ility.

 Ca lc ula te the ra ng e , sum o f sq ua re s, va ria nc e , a nd

sta nda rd de via tio n.

 Ca lc ula te the dive rsity o f a sa mple o f no mina l

  • b se rva tio ns.
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Va ria b ility

 A me a sure o f va ria b ility is a n indic a tio n o f the spre a d o f

me a sure me nts a ro und the c e nte r o f the distrib utio n.

Va ria b ility

 Me a sure s o f va ria b ility a re pa ra me te rs o f the po pula tio n.  Sa mple me a sure s tha t e stima te the va ria b ility o f the po pula tio n a re

sta tistic s.

 Ra ng e  Va ria nc e  Sta nda rd de via tio n

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Me a sure s o f c e ntra lity a nd va ria b ility Me a sure s o f c e ntra lity a nd va ria b ility

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Me a sure s o f c e ntra lity a nd va ria b ility Ra ng e

 T

he diffe re nc e b e twe e n the hig he st a nd lo we st me a sure me nts in a g ro up o f da ta .

 Sta tistic a l ra ng e vs. ma the ma tic a l ra ng e

 I

n a da ta a rra y (sma lle st to la rg e st): Sa mple ra ng e = Xn-X1

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Ra ng e

 Give s so me indic a tio n o f the va ria b ility o f da ta , b ut it o nly de pe nds

  • n the e xtre me va lue s o f the da ta a rra y (la rg e st a nd sma lle st).

 I

t is unlike ly tha t the sa mple will c o nta in the e xtre me va lue s o f the po pula tio n so the sa mple ra ng e will c o nsiste ntly unde re stima te the po pula tio n ra ng e (a b ia se d e stima te ).

Bia se d a nd unb ia se d

 A b ia se d e stima to r will c o nsiste ntly unde r- o r o ve r-e stima te the va lue

  • f a pa ra me te r.

 An unb ia se d e stima to r will no t a lwa ys (o r e ve n o fte n) g ive the

c o rre c t va lue o f a pa ra me te r, b ut it will o ve r-e stima te the pa ra me te r a s o fte n a s it unde re stima te s the pa ra me te r.

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Sum o f sq ua re s

 Sinc e the me a n is a use ful me a sure o f c e ntra l te nde nc y, it is po ssib le

to e xpre ss va ria b ility in te rms o f de via tio n fro m the me a n.

Sum o f sq ua re s

 T

he sum o f a ll de via tio ns fro m the me a n will a lwa ys e q ua l ze ro .

 Po sitive de via tio ns a re c a nc e lle d b y ne g a tive de via tio ns.

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Sum o f sq ua re s

 Sq ua ring the de via tio ns fro m the me a n is o ne wa y o f e limina ting the

sig ns fro m the de via tio ns.

 T

he sum o f the sq ua re s o f the de via tio ns fro m the me a n is c a lle d the sum o f sq ua re s (SS).

Sum o f sq ua re s

 Po pula tio n sum o f sq ua re s  Sa mple sum o f sq ua re s

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Va ria nc e

 T

he me a n sum o f sq ua re s is c a lle d the va ria nc e .

 Sq ua re d units

 Po pula tio n va ria nc e

Va ria nc e

 Sa mple va ria nc e

No te diffe re nc e in the de no mina to r

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Sta nda rd de via tio n

 T

he sta nda rd de via tio n is the po sitive sq ua re ro o t o f the va ria nc e .

 Po pula tio n sta nda rd de via tio n

Sta nda rd de via tio n

 Sa mple sta nda rd de via tio n

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Co e ffic ie nt o f va ria tio n

 T

he c o e ffic ie nt o f va ria tio n e xpre sse s sa mple va ria b ility re la tive to the sa mple me a n.

Dive rsity

 F

  • r no mina l sc a le da ta the re is no me a n to se rve a s a re fe re nc e fo r

va ria b ility. I nste a d the c o nc e pt o f dive rsity (the distrib utio n o f

  • b se rva tio ns a mo ng c a te g o rie s) is use d.

 T

he inde x is use d in a re la tive fa shio n (c o mpa riso n no t a b so lute me a sure )

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Dive rsity

 T

a ke s into a c c o unt b o th numb e rs o f spe c ie s a nd the e ve nne ss o f the distrib utio n a mo ng c a te g o rie s.

Dive rsity

 n = numb e r o f individua ls in the sa mple  fi = numb e r o f o b se rva tio ns in c a te g o ry i

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E ve nne ss

 K

= numb e r o f c a te g o rie s (spe c ie s)