Continuous data (Chapter 17) 359Sometimes it is useful to know the number of scores that lie above or below a particular value. In
such situations it is convenient to construct acumulative frequency distribution tableand acumulative
frequency graphto represent the data.The cumulative frequency gives arunning totalof the scores up to a particular value.
It is the total frequency up to a particular value.From a frequency table we can construct a cumulative frequency column and then graph this data on a
cumulative frequency curve. The cumulative frequencies are plotted on the vertical axis.
From the cumulative frequency graph we can find:
² the median Q 2
² the quartiles Q 1 and Q 3
² percentiles¾
These divide the ordered data into quarters.ThemedianQ 2 splits the data into two halves, so it is50%of the way through the data.
Thefirst quartileQ 1 is the score value25%of the way through the data.
Thethird quartileQ 3 is the score value75%of the way through the data.
Thenth percentile Pn is the score valuen%of the way through the data.
So, P 25 =Q 1 ,P 50 =Q 2 and P 75 =Q 3.Example 4 Self Tutor
Weight (w kg) Frequency
656 w< 70 1
706 w< 75 2
756 w< 80 8
806 w< 85 16
856 w< 90 21
906 w< 95 19
956 w< 100 8
1006 w< 105 3
1056 w< 110 1
1106 w< 115 1The data shown gives the weights of 80 male basketball players.
a Construct a cumulative frequency distribution table.
b Represent the data on a cumulative frequency graph.
c Use your graph to estimate the:
i median weight
ii number of men weighing less than 83 kg
iii number of men weighing more than 92 kg
iv 85 th percentile.a Weight (w kg) frequency cumulative frequency
656 w< 70 1 1
706 w< 75 2 3
756 w< 80 8 11
806 w< 85 16 27
856 w< 90 21 48
906 w< 95 19 67
956 w< 100 8 75
1006 w< 105 3 78
1056 w< 110 1 79
1106 w< 115 1 80this is 1+2
this is 1+2+8C CUMULATIVE FREQUENCY [11.7]
this 48 means that there are 48
players who weigh less than 90 kg,
so ( 90 , 48 ) is a point on the
cumulative frequency graph.IGCSE01
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Y:\HAESE\IGCSE01\IG01_17\359IGCSE01_17.CDR Tuesday, 18 November 2008 11:50:37 AM PETER