Continuous data

17

Contents:

A The mean of continuous data [11.5]

B Histograms [11.6]

C Cumulative frequency [11.7]

Opening problem

#endboxedheading

Rainfall (rmm) Frequency

506 r< 60 7

606 r< 70 20

706 r< 80 32

806 r< 90 22

906 r< 100 9

Total 90

Andriano collected data for the rainfall from the last month for 90

towns in Argentina. The results are displayed in the frequency table

alongside:

Things to think about:

² Is the data discrete or continuous?

² What does the interval 606 r< 70 actually mean?

² How can the shape of the distribution be described?

² Is it possible to calculate the exact mean of the data?

Examples of continuous numerical variables are:

The height of year

10 students:

the variable can take any value from about 100 cm to 200 cm.

The speed of cars on

a stretch of highway:

the variable can take any value from 0 km/h to the fastest speed that a car can

travel, but is most likely to be in the range 50 km/h to 150 km/h.

In we saw that a can theoretically take any value on part of

the number line. A continuous variable often has to be so that data can be recorded.

Chapter 13 continuous numerical variable

measured

IGCSE01

cyan magenta yellow black

(^05255075950525507595)
100 100
(^05255075950525507595)
100 100
y:\HAESE\IGCSE01\IG01_17\353IGCSE01_17.CDR Wednesday, 8 October 2008 9:31:01 AM PETER