Dr. Shanti TejwaniAsst. Prof. M.B. Khalsa Institute of Education, Indoreshanti_tejwani@yahoo.com

An attributes/ characteristics of thing ,objects or events which varies (which can different Values) is known as Variable.

Attandence of Students SexReligionBooks in libraryMode of journeyTime durationAggressionAngerAge

Variables

Continuous

Discontinuous

Dichotomy

Polytomy

Nominal

Ordinal

Interval

Ratio

Nominal Scale

1

2

3

4

Categorization of data

Classified into category

Numbers forming a nominal scale are no more than labels used solely to identify different categories of responses

Example:

RELIGION

Hindu –1

Christian--2

Muslim---3

Buddhism----4

The mode is the most frequent category –only statistics applicable to nominal variableNon Parametric Statistics ---- Chi- Square

Secondplace

Firstplace

Thirdplace

An ordinal scale is more powerful than a nominal scale in that the numbers possess the property of rank order

Classification + Order

Examples : To categories people according to level of

Education

Punctuality

Home work

Cleanliness

Mode

Median

Percentile

Rank Difference Correlation (ρ)

5, 8, 10, 11

3, 6, 8, 9

An interval scale has all the properties of an ordinal scale and the differences between the scale values can be meaningfully interpreted

EXAMPLE

Achievement of the students

Creativity of Students

All Psychological Variable

9 | 13

Mode

Median

Arithmetic Mean

Rank Difference correlation

Product Moment Correlation

Variance

Kilogram

Gram

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9 | 16

Ratio scales possess all the properties of an interval scale and the ratios of numbers on these scales have meaningful interpretations

Examples

Length of the Rod

Weight of School Bag

Mode

Median

Arithmetic Mean

Rank Difference correlation

Product Moment Correlation

Variance

Type of

Scale

Data

Characteristics

Numerical

Operation

Descriptive

StatisticsExamples

Nominal Classification but no

order, distance, or

origin

Counting Frequency in each

category

Percent in each

category

Mode

Gender (1=Male,

2=Female)

Ordinal Classification and

order but no

distance or unique

origin

Rank ordering Median

Range

Percentile ranking

Academic status

(1=Professor

2= Associate

Professor

3= Assistant

Professor)

Type of

Scale

Data

Characteristics

Numerical

Operation

Descriptive

StatisticsExamples

Interval Classification, order,

and distance but no

unique origin

Arithmetic

operations that

preserve order and

magnitude

Mean

Standard deviation

Variance

Temperature in

degrees

Ratio Classification, order,

distance and unique

origin

Arithmetic

operations on

actual quantities

Geometric mean

Coefficient of

variation

Age in years

Income

Four levels of Measurements Nominal

◦ Measures categories

Ordinal◦ Categories + rank and order

Interval◦ Equal distance between any two consecutive

measures

Ratio◦ Intervals + meaningful zeros