scale and tool

7/23/2019 Scale and Tool

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VARIABLES SCALING AND STATI

ANALYSIS IN RESEARCH


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A variableis any entity that can take on different values.

Independent variable is what you (or nature) manipulates(c

Dependent variable is what is affected by the independe

your effects or outcomes. (Effect)

Price of the Egg inNamakkal increases

when the rainincreases in the

Arabian Sea


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The most widely used classifcation o measurement scales ar

1.Nominal Scales

2.Ordinal Scales

3. Interval Scales

4.Ratio Scales


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Assign subjects to groups or categories

No order or distance relationship

No arithmetic origin

Only count numbers in categories

Only present percentages of categories

Chi-square most often used test of

statistical significance

Nominal scale


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Sex Social status

Marital status Days of the week (months)

Geographic location Seasons

Ethnic group Types of restaurants

Brand choice eligion

!o" type# executi$e% technical% clerical

&ther examples

Coded as

Coded as


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Classifies data according to some order or rank; e.g. names

ordered alphabetically

With ordinal data it is fair to say that one response is greater

or less than another.

!.g. if people "ere asked to rate the hotness of # chili

peppers a scale of $hot$ $hotter$ and $hottest$ could be used.

%alues of $&$ for $hot$ $'$ for $hotter$ and $#$ for $hottest$

could be assigned.

Ordinal scale

or e!am"le# a ast ood home delivery sho" may wish to as$ its customers%&ow would you rate the service o our sta'((1) Excellent (2) Very Good (3) Good (4) Poor (5) Worst


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assumes that the measurements are made in equal units.

i.e. gaps bet"een "hole numbers on the scale are equal.

e.g. (ahrenheit and Celsius temperature scales

an inter)al scale does not ha)e to ha)e a true *ero. e.g. A

temperature of $*ero$ does not mean that there is no

temperature...it is just an arbitrary *ero point.

can+t perform full range of arithmetic equations. , degrees is

not t"ice as hot as ' degrees

permissible statistics count/frequencies mode median

mean standard de)iation

Interval scale


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Ratio Scaleis the hi)hest level omeasurement scales. This has the "ro"erties o an

interval scale to)ether with a f!ed *a+solute, -ero "oinThe a+solute -ero "oint allows us to construct ameanin)ul ratio.Ratio scales "ermit the researcher to com"are +othdi'erences in scores and relative ma)nitude o scores.!am"les o ratio scales include wei)hts# len)ths andtimes.or e!am"le# the num+er o customers o a +an$/s 0Tin the lastthree months is a ratio scale. This is +ecause you cancom"are this with "revious three months.or e!am"le# the di'erence +etween 1 and 1 minuteis the same as the di'erence +etween 2 and 3

minutes and 3 minutes is twice as lon) as 1 minutes


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1

2

3

4

5

6

7

Examples

height% weight% age%

length

time

income

market share

1.What is your annual income before

taxes? $ _______

2. How far is your workplace from

home?

_______ kilometres


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Variable escri!ti"eStatistics

Vis#al Presentation $ethod

Nominal Percentages% mode& chi 's(#are

Pie Chart)ar Chart

*rdinal Percentile% median%rank'ordercorrelation &+riedman AN*VA

Pie Chart)ar Chart,inear*gi"e

-nter"al $ean% standardde"iation% !rod#ctmomentcorrelations & t'tests% AN*VA%regression% factoranal.sis

/istogram*gi"e

Ratio eometric andharmonic mean%

Scatter iagram)o2 Plot


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Variable escri!ti"eStatistics

Vis#al Presentation $ethod

Nominal Percentages% mode& chi 's(#are

Pie Chart)ar Chart

*rdinal Percentile% median%rank'ordercorrelation &+riedman AN*VA

Pie Chart)ar Chart,inear*gi"e

-nter"al $ean% standardde"iation% !rod#ctmomentcorrelations & t'tests% AN*VA%regression% factoranal.sis

/istogram*gi"e

Ratio eometric and Scatter iagram

ESCR-P3-VE S3A3-S3-CS


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-nde!endent Variable e!endent Variable 3ools for Anal.sis

Nominal *ender# Native, Nominal 5hi 6s7uare Test

Nominal Ordinal S"earman Ran$ 5oNominal *8ichotomous%Only Two rou"s,

Interval Inde"endent t test

Nominal *ulti )rou", Interval One way 0NO90

Nominal Ratio 8iscriminant 0naly

Inte"endentOneway 0NO90

ann :hitney ; Test


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1

OVERVIEW OF UNIVARIATE DATA ANALYSIS PROCEDURES

Univariate Procedures

What is thescae eve o!

the varia"e#

A$ %ean&$ Standard

deviation

A$ %edian&$ Inter'uartie

ran(e

A$ %ode&$ Reative and

a"soute !re'uenc)

") cate(or)

z test

t test

*o+o(orov,

S+irnov test

Chi,s'uare

test

Interva No+ina

Ordina

-. Descri/tive

a$ Centra

tendenc)

"$ Dis/ersion

0. In!erentia

&IVARIATE DATA ANALYSIS PROCEDURES


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1=

&IVARIATE DATA ANALYSIS PROCEDURES

&ivariate Procedures

What is the

scae eve o!the varia"e#

Linear correation

coe!!icient 1 $Si+/e re(ression

Ran2 correation

coe!!icient3a++a 4 Tau

Contin(enc)

coe!!icientLa+"da

* t test on re(ression

coe!!icient

5 6 test on the di!!erence

"et7een +eans

5 t test on the di!!erence

"et7een +eans

%ann,Whitne)

U test

*a+o(orov ,

S+irnov test

Chi,s'uare

test

T7o interva

varia"es

T7o no+ina

varia"es

T7o ordina

varia"es

-. Descri/tive

0. In!erentia


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1>

%ULTI VARIATE %ET8ODS

INTERDEPENDENCE

%ET8ODS

DEPENDENCE

%ET8ODS

-. Factor Ana)sis

0. Custer Ana)sis

9. %uti, di+ensiona

scain(

De/ends on:

5 Nu+"er o! de/endent

varia"es

5 Nature o! the scae o!

data

Ty"e o Statistical Tests and its 5haracteristics


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Ty"e o Statistical Tests and its 5haracteristics

Hypothesis

Testing

Number of

Smp!es

"esurement

S#!e

Test

Hypotheses

About fre$uen#y

Distribution

%ne Nomin! Chi&s$ure

T'o or more Nomin! Chi&s$ure

Hypothesis

About

mens

%ne (Lrge smp!e Inter)!

%r Rtio

* Test

%ne (sm!!

smp!e

Inter)!

%r Rtio

t Test

T'o (Lrge smp!e Inter)!

%r Rtio

* Test

T'o (Sm!! smp!e Inter)!

%r Rtio

t Test

Three or more(Sm!!

smp!e

Inter)!

%r Rtio

AN%VA

Hypothesis

About

+roportions

%ne (Lrge smp!e Inter)!

%r Rtio

* Test

%ne (sm!!

smp!e

Inter)!

%r Rtio

t Test

T'o (Lrge smp!e Inter)!

%r Rtio

* Test

T'o (Sm!! smp!e Inter)!%r Rtio

t Test

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