Transcript Lesson 3.9: Scatter Plots - Rutherford County Schools

Scatter Plots
Standard: 806.5.3 Generalize the
relationship between two sets of data
using scatterplots and lines of best fit.
Scatter Plot
• A scatter plot is a graph of a collection of
ordered pairs (x,y) to show a relationship
between two sets of data.
• A correlation describes the relationship
between two sets of data.
• A line of best fit is a straight line that comes
closest to the points on a scatter plot. You can
use a line of best fit to help you make
predictions from the data.
Positive Correlation
• If the x-coordinates and the
y-coordinates both
increase, then it is
POSITIVE CORRELATION.
• This means that both are
going up, and they are
related.
Positive Correlation
• If you look at the age of a child and the
child’s height, you will find that as the
child gets older, the child gets taller.
Because both are going up, it is
positive correlation.
Age
1
Height 25
2
3
31 34
4
36
5
40
6
41
7
47
8
55
Negative Correlation
• If the x-coordinates and the ycoordinates have one
increasing and one
decreasing, then it is
NEGATIVE CORRELATION.
• This means that 1 is going up
and 1 is going down, making
a downhill graph. This means
the two are related as
opposites.
Negative Correlation
• If you look at the age of your family’s car and
its value, you will find as the car gets older, the
car is worth less. This is negative correlation.
Age 1
of car
2
3
4
5
Value $30,000
$27,000 $23,500 $18,700 $15,350
No Correlation
• If there seems to be
no pattern, and the
points looked
scattered, then it is no
correlation.
• This means the two
are not related.
No Correlation
• If you look at the size shoe
a baseball player wears,
and their batting average,
you will find that the shoe
size does not make the
player better or worse,
then are not related.
Constant Correlation
The relationship is linear, but is
neither positive, nor negative.
Therefore, there is no correlation
between the two.
Scatterplots
Which scatterplots below show a linear trend?
a)
c)
Negative
Correlation
e)
Positive
Correlation
b)
d)
f)
Constant
Correlation
Objective - To plot data points in the
coordinate plane and interpret scatter
plots.
y
Sport Utility Vehicles
(SUVs) Sales in U.S.
1991
1992
1993
1994
1995
1996
1997
1998
1999
0.9
1.1
1.4
1.6
1.7
2.1
2.4
2.7
3.2
Vehicle Sales (Millions)
Year Sales (in Millions)
5
4
3
2
1
1991 1993 1995 1997 1999
1992 1994 1996 1998 2000
Year
x
Scatterplot - a coordinate graph of data points.
y
Trend appears linear.
Year 
SUV Sales 
Positive correlation.
Predict the sales in 2001.
Vehicle Sales (Millions)
Trend is increasing.
5
4
3
2
1
1991 1993 1995 1997 1999
1992 1994 1996 1998 2000
Year
x
Plot the data on the graph such that homework time
is on the y-axis and TV time is on the x-axis..
Time Spent Time Spent
Student Watching TV on Homework
Sam
30 min.
180 min.
Jon
45 min.
150 min.
Lara
120 min.
90 min.
Darren
240 min.
30 min.
Megan
90 min.
90 min.
Pia
150 min.
90 min.
Crystal
180 min.
90 min.
Plot the data on the graph such that homework time
is on the y-axis and TV time is on the x-axis.
TV
Homework
45 min. 150 min.
120 min. 90 min.
240 min. 30 min.
Time on
Homework
30 min. 180 min.
240
210
180
150
120
90
90 min. 120 min.
60
150 min. 120 min.
30
180 min. 90 min.
30
90
150
210
60
120
180
240
Time Watching TV
Describe the relationship between time spent on
homework and time spent watching TV.
Trend appears linear.
Time on
Homework
Trend is decreasing.
240
210
180
150
120
90
Time on TV 
60
Time on HW 
30
Negative correlation.
30
90
150
210
60
120
180
240
Time Watching TV
Now, let’s do pages
506-507 #1-11 for
homework!
