Chapter 3: Organisation of DataClass 11 Economics — summary, notes, extra questions & MCQ quiz

Summary

Once data are collected they are raw and disorganised, so the next step is to classify them to bring order and make further analysis possible. Classification means arranging data into groups or classes on the basis of some criterion. Data may be classified chronologically (by time, such as years — a time series), spatially (by place), qualitatively (by an attribute like gender or literacy that cannot be measured) or quantitatively (by a measurable characteristic like income). Variables are of two types: a continuous variable, like height, can take any value including fractions within a range, while a discrete variable, like the number of students, changes only by finite jumps. A frequency distribution shows how the values of a quantitative variable are distributed across classes with their frequencies. Each class has a lower and an upper limit; the class interval is their difference and the class mark or mid-point their average, \((\text{Upper limit}+\text{Lower limit})/2\). Classes may be formed by the inclusive method (both limits counted) or the exclusive method (one limit excluded and placed in the next class); for continuous data an adjustment restores continuity between gaps. Frequencies are counted using tally marks. Classifying data causes a loss of information, because individual observations are replaced by the class mark in later calculations. A discrete variable's data are shown as a frequency array, while the joint distribution of two variables forms a bivariate frequency distribution.

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