"Research is done in the grey areas (area where nothing is established). It is the work of the researcher to identify the grey area".
TYPE OF SCALES
Nominal
Nominal scales label variables. These scales are to be used when the purpose of the question is just identification and grouping of variables into categories. In nominal data only counting operations work. Example:
Example 1. What is your gender?
(a) Male
(b) Female
Example 2. What is the color of your eyes?
(a) Black
(b) Brown
(c) Green
(d) Blue
Example 1. What is your gender?
(a) Male
(b) Female
Example 2. What is the color of your eyes?
(a) Black
(b) Brown
(c) Green
(d) Blue
Ordinal
Ordinal scales order observations. There is some kind of logical ordering in the observations and average of observation has no meaning. In ordinal scale variables don't have an equal distance between each value. Example:
Example 1.. What is the level of your job satisfaction?
(1) High
(2) Average
(3) Low
we know 'high' is more than 'average' but by how much is not exact.
Example 2. How was your day at work today?
(1) Excellent
(2) Good
. (3) Ok
(4) Bad
(5) worst
we cannot tell the exact difference between values i.e. how much 'Ok' is better than 'bad' or 'good' is better than 'Ok'
Example 1.. What is the level of your job satisfaction?
(1) High
(2) Average
(3) Low
we know 'high' is more than 'average' but by how much is not exact.
Example 2. How was your day at work today?
(1) Excellent
(2) Good
. (3) Ok
(4) Bad
(5) worst
we cannot tell the exact difference between values i.e. how much 'Ok' is better than 'bad' or 'good' is better than 'Ok'
Interval
Interval scales are numeric scales with exact differences between the values. Like there is an exact difference of 60 minutes in between 2 PM- 3 PM and 4 PM- 5 PM or the difference between a temperature of 10 and 20 degree centigrade is always same as the difference between 48 and 58 degree centigrade. In case of Interval scales true zero is not there.
Example 1. How likely are you to consider purchasing a mobile phone online?
Extremely unlikely 1 - 2 - 3 - 4 - 5 Extremely likely
Example 1. How likely are you to consider purchasing a mobile phone online?
Extremely unlikely 1 - 2 - 3 - 4 - 5 Extremely likely
Ratio
Ratio scale have an absolute zero and offers application of many statistical techniques.
Example 1. What is your weight?
A person can give the answer like 50Kg or 60 Kg or something. But in this case the base value is absolute zero.
Example 2.
What is your age?
Example 3.
How many hours a day do you spend using a mobile phone?
Example 1. What is your weight?
A person can give the answer like 50Kg or 60 Kg or something. But in this case the base value is absolute zero.
Example 2.
What is your age?
Example 3.
How many hours a day do you spend using a mobile phone?
