In the realm of data analysis, different scales of measurement serve distinct purposes. The ordinal scale is used for ranking items in a comparative manner without quantifying the exact difference between ranks.
ATTRIBUTES-is something that an object either has or has not, Eg: whether you are male or female is an attribute your either female or not female.
VARIABLES-is something that is changeable and can be measured on a numerical scale, Eg: the income of a group of houses or the average height of a group of people.
A RANDOM VARIABLE- is a variable that changes in an unexpected and random way such as the share prices of a stock exchange
CENSUS- a census is a form of information gathering where every element of the population is surveyed.
EXAMPLE: if i wanted to know the average age of a group of 300 students and i surveyed all 300 of them, I can calculate the true average age of the group.
The objective is to collect a complete set of Data the true population parameter can be determined.
Scales of measurement
INTERVAL SCALE- is like ratio scale but the term 0(zero) does not actually imply non-occurrence, Eg: if we were to analyse a companies income for each month of the year and noticed 0 in March then that would imply no sales. but if we were to have 0 on a thermometer it would have just as much purpose as 17 degrees would.
RATIO SCALE- a ratio scale can be used for identification
ranking and for a wide range of mathematical calculations.
ORDINAL SCALE- ordinal scale is a comparative measure
and is usually used for the purpose of ranking.
and is
While the scale can be used to rank high to low
the difference between points cannot be precisely
quantified
NOMINL SCALE- This is similar to a label or a code
to identify and distinguish objects.