difference between ordinal and scale

7/30/2019 Difference between ordinal and scale

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Feb 22, 2012

ALL ANSWERS (9)

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for tables and graphs you must define correctly if a variable is ordinal or

scale, and for the usage of labels in ordinal variables you should define

the properties of the variable correctly... it's an "opperative" usage, you

could change the variable type when you need it as ordinal or scale,

depending on which type of analysis you'll do in SPSS

Feb 21, 2012

Aditya Kumar Katragadda

Ordinal.

A variable can be treated as ordinal when its values represent categories

with some intrinsic ranking; for example, levels of service satisfaction

from highly dissatisfied to highly satisfied. Examples of ordinal variables

include attitude scores representing degree of satisfaction or confidence

and preference rating scores.

A variable can be treated as ordinal when its values represent categories

with some intrinsic ranking; for example, levels of service satisfaction

from highly dissatisfied to highly satisfied. Examples of ordinal variables

include attitude scores representing degree of satisfaction or confidence

and preference rating scores.For ordinal string variables, the alphabetic

order of string values is assumed to reflect the true order of the

categories. For example, for a string variable with the values of low,

medium, high, the order of the categories is interpreted as high,low,mediumwhich is not the correct order. In general, it is more reliable to

use numeric codes to represent ordinal data.

Scale.

A variable can be treated as scale when its values represent ordered

categories with a meaningful metric, so that distance comparisons

between values are appropriate. Examples of scale variables include age

in years and income in thousands of dollars.A variable can be treated as

scale when its values represent ordered categories with a meaningful

metric, so that distance comparisons between values are appropriate.

Examples of scale variables include age in years and income inthousands of dollars.

Nominal.

A variable can be treated as nominal when its values represent categories

with no intrinsic ranking; for example, the department of the company in

which an employee works. Examples of nominal variables include region,

zip code, or religious affiliation.A variable can be treated as nominal when

its values represent categories with no intrinsic ranking; for example, the

department of the company in which an employee works. Examples of

rence between ordinal and scale in SPSS http://www.researchgate.net/post/Difference_between_ordinal_an

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nominal variables include region, zip code, or religious affiliation.

(Source: SPSS User Guide)

Feb 21, 2012

Muhammad Ibrahim Govt. Dyal Sing College

You are absolutely right for defining scales in SPSS

Feb 21, 2012

Chris Macintosh University of Utah

In practice, SPSS does not REQUIRE you to make the definition. I've

seen many data sets where no one bothered to define in SPSS if the

variable was ordinal or scale. However, as noted, that means that

improper calculations can sometimes be made. It is up to the researcher

to understand the difference and choose tests appropriately. Defining the

level of measurement does have an advantage sometimes in that SPSSwill not allow some variables to be used incorrectly - particularly in the

case of nominal variables.

Feb 21, 2012

Jason Leung The Chinese University of Hong Kong

Thanks all of you for the comments!

Feb 22, 2012

dr vinod Sen Central university of Gujarat, Gandhinagar

in the SPSS if you want measured Central tendency (mean, Median and

Mode ), than you must have some short of knowledge about nominal,

Ordinal and scale. the Choice of mean, median and mode is restricted by

the level of measurement of a variable you defined. if the level of the

measurement for a variable is nominal, you can calculate only mode, if the

level of measurement of a variable is ordinal then you can calculate mode

or median. if the level of measurement of a variable is interval/ratio, you

can calculate mode and median,

Feb 22, 2012

Reyhaneh Farhadi

ordinal scale:

A rank-ordered scale of measurement in which equal differences between

numbers do not represent equal differences between the things measured.

nominal scale:

scale of measurement in whch numbers are used simply as names and


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not as quantites.

Feb 22, 2012

Shailaja Rego Narsee Monjee Institute of Management Studies

there are total four types of scales, namely Nominal, Ordinal, Interval and

Ratio. Depending on the type of the scales, respective treatment can be

given to those variables. for example nominal variable can only be

counted hence no mean or standard deviation can be calculated on the

same. ordinal variable can be counted and median can be calculated.

Interval and ratio ( combined as scale in SPSS) are quantitative variables.

most quantitative analysis can be performed on these. The basic

difference between qualitative and quantitative variables is the FIXED

Distance. qualitative variables do not have fixed distance. quantitative

variables have fixed distance.

Nominal - Qualitative variable with out order (only categorisation possible)

example : gender, departments, etc.

Ordinal - Qualitative variable with order (categorisation and order)

example Rank, credit rating as High risk, medium risk, Low risk etc.

Interval - Quantitative variable without fixed origin.( has fixed distance but

no fixed origin) example - temperature

Ratio - Quantitative variable with fixed origin. all quantitative variables are

in this category , salary, expenditure, etc.

Feb 22, 2012

subhash Davar Kurukshetra University

scale is simply a measurement of a phenomenon or characteristic,

Working out a figure and saying that it is male or female amounts to

scaling ie.classification popularly termed as nominal scale. It could be

multinomial. and it is not necessary that we have only 0 and 1 scale. The

nominal scale could be 1,2, 3 or more categories in which you place

objects or persons. It depends on the classification one is interested in.

Even continuous data can be translated into categories. For example,

income data may be grouped into four or five categories. For a statistiscal

analysis,, you may require to know number of people or respondents into

particulal category.If one is interested in rank order, it can be ranked from

lowest category to highest category. For example, a trait can be rated as

highest, down to a minimum and not necessarily to a zero level. let me say

that the SPSS will do what you want. Do try to understand the statistics

Feb 22, 2012


1/15/2013

difference between ordinal and scale

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