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Scatter DiagramsScatter Diagrams
Objectives:
D Grade Draw a scatter diagram by plotting points on a graph
Interpret the scatter graph
Draw a line of best fit
C Grade Interpret the line of best fit
Identify the type and strength of correlation
Scatter DiagramsScatter Diagrams
A scatter graph is a graph using paired data that can be used to find out whether there is a relationship between two variables.
A variable is a piece of information that can change. e.g. test results - these can be any value, but will be a specific value for a particular person's test.
paired data is two separate pieces of data referring to the same thing e.g. the age and value of a car the height and shoe size of a person the marks that a person gained in two separate tests.
Scatter DiagramsScatter Diagrams
This information can then be plotted for each student on a graphwith the height on one axis and the shoe size on the other axis
Hei
ght
Shoe size
each cross represents the shoe size and height of one student
The height and shoe size of students in a class was recorded.
Scatter DiagramsScatter Diagrams
10 pupils sat both a Maths and a Physics exam, here are their scores:
Pupil A B C D E F G H I JMaths 56 24 67 70 71 42 48 32 52 80Physics 65 38 71 72 73 51 56 42 57 82
Plot them as a scatter graph.
Generally the top set of data is used for the x values
XX
XX X
XXXX
X
Scatter DiagramsScatter Diagrams
Correlation:
is a measure of the relationship between two variables;
correlation is measure in terms of type and strength
correlation is assessed by being strong or weak
strong means there is a very strong relationship such as‘the hotter the weather the more ice creams are sold’
weak means there is no relationship between things such as‘the colder the weather the better my exam results will be’
Scatter DiagramsScatter Diagrams
Correlation on a scatter diagram
strong correlation weak correlation
Notice how the crosses are grouped close together along animagined line
The crosses are less closely grouped in the example of weak correlation.
no correlation
Scatter DiagramsScatter Diagrams
Correlation can also be described and positive or negative,Depending on the slope (gradient) of the graph
positive correlation negative correlation
Positive correlation means that as one item increases, so does the other. e.g. as a person’s height increases so does their armspan
Negative correlation means that as one item increases, so does the other. e.g. as a car gets older its value decreases
Scatter DiagramsScatter DiagramsExample:Sketch a diagram to show a possible scatter graph for paired data for the age and value of a computer.Describe the correlation and write a sentence to describe the relationship
age of computer
valu
e of
com
pute
r Strong negative correlation
As a computer gets olderit is worth less
Scatter DiagramsScatter Diagramsp39
Q3 Q4
Worksheet
a. Draw a scatter graph of the resultsb. Describe the type and strength of correlationc. Write a sentence explaining the relationship
between the two sets of data
The table shows the ages and arm spans of seven students in a school. The table shows the ages and second-hand values
of seven cars.
a. Draw a scatter graph of the resultsb. Describe the type and strength of correlationc. Write a sentence explaining the relationship
between the two sets of data
Age of car (years) 2 1 4 7 10 9 8
Value of car (£) 4200 4700 2800 1900 400 1100 2100
Age (years) 16 13 13 10 18 10 15Arm Span (inches) 62 57 59 57 64 55 61
Scatter DiagramsScatter Diagrams
Q5 Q8 refer to book p40
Worksheet
a. Draw a scatter graph of the resultsb. Describe the type and strength of correlationc. Write a sentence explaining the relationship
between the two sets of data
Amount of rainfall (mm) 0 1 2 5 6 9 11
Number of sunbeds sold 380 320 340 210 220 110 60
The table shows the daily rainfall and the number Of sunbeds sold at a resort on the south coast
Scatter DiagramsScatter Diagrams
1 2 3 4 5 6 7 8 9 1110Age of Car (years)
Val
ue o
f ca
r (£
)
1000
2000
3000
4000
68
66
64
62
60
58
56
54
52
50
10 11 12 13 14 15 16 17 18
Age (Years)
Arm
Spa
n (i
nche
s)p39
Q3 Q4
X
X
X
X
X
X
X
X
X
X
X
X
X
X