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ORGANISING DATA
Present this data in a frequency distribution table.
A tally mark is placed in the appropriate row in the table as the data are read from left to right. The first result is a ‘1’, so a tally mark is placed in the row where 1 appears in the ‘number of cars’ column in the table. The next result is a ‘2’, so a tally mark is placed in the row where 2 appears in the ‘number of cars’ column, and so on. The fifth tally mark is drawn through the preceding four marks to make final calculations of frequency easier. Thus, it can be seen that the number of households with no car is 4, the number of households with 1 car is 6 and so on. CLASS INTERVALS When a variable takes a large number of values it is easier to present and handle the data by grouping the values in class intervals. Continuous variables are always presented in class intervals; discrete variables can also be grouped and presented in class intervals. In the example below, we set out age ranges for a study of young people, but allow that some older people may fall in-scope for our study. The frequency of a class interval is the number of observations that occur in a particular pre-defined interval. If 20 people aged 5-9 appear in our result, the frequency is 20 for this interval. The end-points of a class interval are the lowest and highest values that a variable can take. Therefore, if the intervals are 0-4 years, 5-9, 10-14, 15-19, 20-24, and 25+; the end-points of the first interval are 0 and 4 if the variable is discrete, and 0 and 4.999 if continuous. Class interval width is the difference between lower end-point of the interval and lower end-point of the next interval. If the intervals (continuous) are 0-4, 5-9, .... , etc.; the width of the first 5 intervals is 5, and the last interval is open. The intervals could also be written as 0-<5, 5-<10, 10-<15, 15-<20, 20-<25, and 25+. The basic rules to follow when constructing a frequency distribution table for a data set containing a large number of observations are:
EXAMPLE
Construct a frequency distribution table. The lowest value is 363 and the highest value is 431.
RELATIVE AND PERCENTAGE FREQUENCY Analysts studying this data may not be only interested in how long batteries last, but also what proportion fall in each class interval. The relative frequency of a particular observation or class interval is found by dividing the frequency (f) by the number of observations (n): that is, (f/n). Thus: RELATIVE FREQUENCY = FREQUENCY ÷ NUMBER OF OBSERVATIONS The percentage frequency is found by multiplying each relative frequency value by 100. Thus: PERCENTAGE FREQUENCY = f/n x 100 EXAMPLE
The analyst might now be able to say that:
Note: these statements assume a representative sample has been drawn. For completeness, an estimate of variability should be referred to as well (see section Measures of Spread - Range) Nevertheless, in summary, frequency distribution tables are important in providing information about the population from which the sample is drawn.
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