STATISTICS
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1 Explain the scales of measurement in details , giving examples:
Data has been classified into four scales of measurement so that it can be easily interpreted universally. The scale is chosen depending on the information that the data is intending to represent. The four scales of measurement of data are nominal, ordinal, interval, and ratio. Each plays a different, yet very important role in the world of statistic
a) Nominal scale
Is the lowest level in scales of measurement? Is a way of grouping behavior, where actual numbers are simply labels or identifiers.
-they do not put subjects in any particular order: no logical basis for the answers in each category
Example: - e.g. asking 50 individuals in a room about their marital statues
No Married Single Divorced Other 20 15 25 2
There is no basis to state whether divorced has a higher level than the others or not
b) Ordinal Scale
-In the scale, there is order in form of ranking.
-There is No way of knowing the size of differences in the data sets, only one is higher/greater than the other.
Example: Carrying a research in a given locality on the social economic class
No Low income earners Middle income earners High income earners Other 30 15 5 0
Not only do we not know the differences, we don't know the actual income of anyone.
c) Interval Scale
-Interval scales Keep same rank as ordinal scales but also indicate differences between each data point.
-The interval points between one variable and the next are the same e.g. 2, 4, 6,8,10 – the interval between in between is the same.
-the interval between values is interpretable hence can compute an average of an interval variable
- Ratios don’t make any sense,
-however what a rating of e.g. 2
Example:
Rating Relationships in your organization Rate on a scale of 1-5( 1 High, 5 Low) how important these relationships are Rate on a scale of 1-5( 1 High, 5 Low) how good these relationships are
Customers /
1 Explain the scales of measurement in details , giving examples:
Data has been classified into four scales of measurement so that it can be easily interpreted universally. The scale is chosen depending on the information that the data is intending to represent. The four scales of measurement of data are nominal, ordinal, interval, and ratio. Each plays a different, yet very important role in the world of statistic
a) Nominal scale
Is the lowest level in scales of measurement? Is a way of grouping behavior, where actual numbers are simply labels or identifiers.
-they do not put subjects in any particular order: no logical basis for the answers in each category
Example: - e.g. asking 50 individuals in a room about their marital statues
No Married Single Divorced Other 20 15 25 2
There is no basis to state whether divorced has a higher level than the others or not
b) Ordinal Scale
-In the scale, there is order in form of ranking.
-There is No way of knowing the size of differences in the data sets, only one is higher/greater than the other.
Example: Carrying a research in a given locality on the social economic class
No Low income earners Middle income earners High income earners Other 30 15 5 0
Not only do we not know the differences, we don't know the actual income of anyone.
c) Interval Scale
-Interval scales Keep same rank as ordinal scales but also indicate differences between each data point.
-The interval points between one variable and the next are the same e.g. 2, 4, 6,8,10 – the interval between in between is the same.
-the interval between values is interpretable hence can compute an average of an interval variable
- Ratios don’t make any sense,
-however what a rating of e.g. 2
Example:
Rating Relationships in your organization Rate on a scale of 1-5( 1 High, 5 Low) how important these relationships are Rate on a scale of 1-5( 1 High, 5 Low) how good these relationships are
Customers /