Warm Up
On your whiteboards…
Draw a coordinate plane, then graph and label each point.
1. A(3, 2)
2. B(–3, 3)
4. D(0, –3)
3. C(–2, –1)
6. F(3, –2)
5. E(1, 0)
Scatter Plots
SWBAT use scatter plots to determine the strength of relationship
between two data sets and distinguish between correlation and
causation. 3.1.b.ii
D.O.L. Given 4 CR questions, students will use scatter plots to
determine the strength of relationship between two data sets and
distinguish between correlation and causation with 75% accuracy.
Why : Scatter plots let us see how one variable can have an impact
or relationship on another variable. This relationship also allows us
to identify trends and make predictions about relationships.
Essential Question

How do we describe real-life data displayed in
graphs?
Think – Pair - Share
Suppose you worked at a
video store. The number of
videos you sold in a five
year period is shown on
the graph.
1. Explain the trend you
see.
2. Estimate the number of
movies sold on video
sold in 2003.
Scatter plots
Scatter plot – A graph of plotted points that shows the
relationship between two sets of data.
• In a scatter plot, the two sets of data are graphed as
ordered pairs (x, y) on a coordinate system.
Scatter plots let us the see a
correlation in the data,
establish trends, and make
predictions about future
events.
Correlations: How do the data relate?
Correlation – The relationship between two variables
As x increase, y
_______.
increase.
As
As xx increase,
increase, yy
decrease.
_______.
Say it together…
Describe Correlations from Scatter
Plots

Describe the correlation illustrated by the scatter
plot. (as x increase, y ________)
As the average daily
temperature increased,
the number of visitors
increased.
There is a positive
correlation between the
two data sets.
Describe Correlations from Scatter
Plots

Describe the correlation illustrated by the
scatter plot. (as x increase, y ________)
As the years increased, the
number of participants in
the snowboarding
competition increased.
There is a positive
correlation between the
two data sets.
Describe Correlations from Two Data
Sets

Choose the correct correlation:
the average temperature in a city and the number of
speeding tickets given in the city
A) As the temperature increases, the number of
speeding tickets increases.
B) As the temperature increases, the number of
speeding tickets increases.
C) As the temperature decreases, the number of
speeding tickets increases.
D) The number of speeding tickets has nothing to do
with the temperature.
Describe Correlations from Two Data
Sets
Choose the correct correlation:
Ticket sales and the number of people in an
audience.

A) As ticket sales increase, the number of people in an
audience increases.
B) As ticket sales increase, the number of people in an
audience decreases.
C) As ticket sales decrease, the number of people in
an audience increases.
D) The number of ticket sales has nothing to do with
the number of people in an audience.
Your turn!

Explain the correlation you would expect to see
between the pair of data sets.
a runner’s time and the distance to the finish line
You would expect to see a negative correlation. As a
runner’s time increases, the distance to the finish
line decreases.
Your turn!

Explain the correlation you would expect to see
between the pair of data sets.
the number of times you sharpen your pencil and the
length of your pencil
You would expect to see a negative correlation. As
the number of times you sharpen your pencil
increases, the length of your pencil decreases.
Your turn!

Explain the correlation you would expect to see
between the pair of data sets.
the temperature in Houston and the number of cars
sold in Boston
You would expect to see no correlation. The temperature in
Houston has nothing to do with the number of cars sold in
Boston.
Your turn!

Explain the correlation you would expect to see
between the pair of data sets.
the number of members in a family and the size of the
family’s grocery bill
You would expect to see positive correlation. As the
number of members in a family increases, the size of
the grocery bill increases.
Correlation vs. Causation

Causal relationship – A relationship in which
one thing causes another


Causal – When the temperature goes up, the
amount of clothes people wear goes down
A strong correlation between two data sets
doesn’t mean they have a causal relationship
Correlation is not causation!
Correlation is not causation!
Correlation is not causation!
What’s wrong with this logic?
Think-Pair-Share

What’s an example of two things that
might have correlation, but not
causation?
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the
relationship between the age of a car and the amount of
money spent each year on repairs. Explain.
Graph A
Graph B
Graph C
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the
relationship between the age of a car and the amount of
money spent each year on repairs. Explain.
Graph A
The age of the car cannot be
negative.
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the
relationship between the age of a car and the amount of
money spent each year on repairs. Explain.
Graph B
This graph shows all positive
values and a positive correlation,
so it could represent the data set.
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the
relationship between the age of a car and the amount of
money spent each year on repairs. Explain.
Graph C
There will be a positive correlation
between the amount spent on
repairs and the age of the car.
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the
relationship between the age of a car and the amount of
money spent each year on repairs. Explain.
Graph A
Graph B
Graph A shows negative values, so
it is incorrect. Graph C shows
negative correlation, so it is
incorrect. Graph B is the correct
scatter plot.
Graph C
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the relationship
between the number of minutes since a pie has been taken
out of the oven and the temperature of the pie. Explain.
Graph A
Graph B
Graph C
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the relationship
between the number of minutes since a pie has been taken
out of the oven and the temperature of the pie. Explain.
Graph
A
The pie is cooling steadily
after it is take from the oven.
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the relationship
between the number of minutes since a pie has been taken
out of the oven and the temperature of the pie. Explain.
Graph B
The pie has started cooling before it is
taken from the oven.
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the relationship
between the number of minutes since a pie has been taken
out of the oven and the temperature of the pie. Explain.
Graph C
The temperature of the pie is
increasing after it is taken from
the oven.
Matching Scatter Plots to Situations

Choose the scatter plot that best represents the relationship
between the number of minutes since a pie has been taken
out of the oven and the temperature of the pie. Explain.
Graph A
Graph B
Graph C
Graph B shows the pie cooling while
it is in the oven, so it is incorrect.
Graph C shows the temperature of
the pie increasing, so it is incorrect.
Graph A is the correct answer.
Looking at a table

Explain the correlation:
Time pooper scoopers clean
the park vs. number of dogs in As the number of dogs in
the park
the park increases, the
Dogs
Hours
number of hours it takes
10
2
pooper scoopers to clean
20
2.5
the park increases: Positive
Correlation
30
4
40
5
Looking at a table

Explain the correlation:
Number of squirrels in park vs.
number of dogs in park
Dogs
Squirrels
10
200
20
30
40
158
140
100
As the number of
dogs in the park
increases, the
number squirrels
decreases: Negative
Correlation
Essential Question

How do we describe real-life data displayed in
graphs?
D.O.L.
1A. Explain the correlation illustrated by the scatter plot.
1B. If there’s a correlation, justify whether the data sets
might have a causal or non-causal relationship.
There is a positive
correlation between the two
data sets.
As the number of fat grams
increased, the number of
calories also increased.
Fat and calories have a causal
relationships, because the amount
of fat directly impacts the amount
of calories in food.
D.O.L.
2A. Explain the correlation illustrated by the scatter plot.
2B. If there’s a correlation, justify whether the data sets
might have a causal or non-causal relationship.
There is a negative
correlation between the two
data sets.
As the weight of the vehicle
increased, the gas mileage
decreased.
Weight and mpg have a causal
relationships, because the weight
of a car directly impacts its gas
mileage.
D.O.L.
3A. Explain the correlation illustrated by the scatter plot.
3B. If there’s a correlation, justify whether the data sets
might have a causal or non-causal relationship.
There is a no correlation
between the two data sets.
The year has no impact on the
number of hurricanes that may
or may not appear
D.O.L.
4. Explain the correlation you would expect to see
between each pair of data sets. Explain.
a. The outside temperature in the summer and the cost of the
electric bill
Positive correlation; as the outside temperature increases, the
electric bill increases because of the use of the air conditioner.
b. The price of a car and the number of passengers it seats
No correlation; a very expensive car could seat only 2
passengers.