



To measure the time
it takes to run the 100
yard dash
To measure the
weight of a
refrigerator
To measure the
distance from C.S. to
Denver
To measure the
dining room table

Seconds

Pounds

Miles

Feet
SWBAT represent data on a scatter plot
and construct a line of best fit and make
predictions. (3.1.b.ii)

Given 2 multiple choice problems and 1
constructed response problems (with 4
parts), students will represent data on a
scatter plot, construct a line of best fit,
and make predictions with 80% accuracy.
DOL
Objective

Why? Used in business to make decisions about products
to sell or discontinue.

What do I need to study most about
scatter plots and writing equations to be
successful on the quiz tomorrow?

Positive – as the independent
variable increases, the
dependent variable increases

Negative – as the independent
variable increases, the
dependent variable decreases

Sketch a positive and negative
correlation in your notes:
A - Positive
 B - Negative
 C - No Correlation

A - Positive
 B - Negative
 C - No Correlation


The size of the car and its fuel efficiency
Independent – size of car
 Dependent – fuel efficiency
 Correlation – Negative; as the size of the
car gets bigger, the fuel efficiency
becomes less.


Your score on a test compared to hours
spent studying
Independent – hours studying
 Dependent – test score
 Correlation – Positive; as the hours
studying increase, the test scores go up.


Time spent on treadmill and calories
burned
Independent – time on treadmill
 Dependent – calories burned
 Correlation – Positive; The more time
spent on the treadmill, the more calories
that will be burned


City
Using the table, write a prediction
equation for a line of best fit going
through Paris, France and Bucharest,
Romania.
London, England
Elevati Average
on
Precipitat
(feet)
ion

(inches)

171
21

190
23

203
30
Paris, France*
213
26
26 – 23
3 –
First
things first
213 - 298 the -85
identify
m = -.04
Independent
and
26 = -.04(213) + b
dependent
 variable
26 = -8.52 + b
Bucharest, Romania*
298
23

34.52 = b
Budapest, Hungary
456
20
Toronto, Canada
567
31

y = .04x + 34.52
Stockholm, Sweden
Berlin, Germany

y = -0.04x + 34.52

y = -.04(279) + 34.52
y = -11.16 + 34.52
y = 23.36







Now using your
prediction equation,
predict the average
annual precipitation
for Dublin, Ireland,
which has an
elevation of 279 feet.
1) 25 inches
2) 23 inches
3) 1844 inches
4) 203 inches
Year
1980
People
(millons)
29.3
1985
33.1
1990
33.6
1995
36.4
1998
34.5
2012
??

Write a prediction equation using
(1980, 29.3) and (1990, 33.6)
 29.3
– 33.6first – -4.3
First
things
 1980-1990
-10
identify
the
 m = .43
Independent
and
 29.3 = .43(1980) + b
dependent
 29.3 = 851.4 + b
variable

-822.1 = b

y = 0.43x – 822.1
Year
1980
People
(millons)
29.3
1985
33.1
1990
33.6
1995
36.4
1998
34.5
2012
??

y = 0.43x – 822.1

y = 0.43(2012) – 822.1
y = 865.16 – 822.1
y = 43.06



Approximately 43.06
people are predicted
to be below the
poverty level in 2012.
Year
Earnings ($)
1985
343
1990
412
1995
479
1999
549
2012
??
Write an equation
using (1990, 412) and
First things first –
(1985, 343)

identify the
Independent and
 y = 13.8x – 27050
dependent
variable
 2012, 715.6
Work on the problem marked on your
paper on your own.
 Find the person with the same problem
and color as you.
 Compare your work on the first problem
and make changes.
 Complete the second problem together.


(19, 126) and (26, 173)


126 – 173
-47
19 – 26
-7
m = 6.7
126 = 6.7(19) + b
126 = 127.3 + b
-1.3 = b

y = 6.7x – 1.3





(5.1, 56) and (9.0, 40)


56 – 40
16
5.1 – 9.0
-3.9
m = -4.1
40 = -4.1(9) + b
40 = -36.9 + b
76.9 = b

y = -4.1x + 76.9





(17, 24) and (75, 52)


24 – 52
-28
17 – 75
-58
m = .48
24 = .48(17) + b
24 = 8.16 + b
15.84 = b

y = .48x + 15.84





(9, 6.0) and (41, 1.2)


6.0 – 1.2
4.8
9 – 41
-32
m = -.15
6.0 = -.15(9) + b
6.0 = -1.35 + b
7.35 = b

y = -.15x + 7.35




Years
6
Sales ($)
9000
5
6000
3
4000
1
3000
4
6000
3
5000
6
8000
2
2000

Create a scatter plot.
Drawthings
a line offirst
best–fit.
First
identify the
 Write a prediction
Independent
and
equation.
dependent
 variable
Predict the sales for a

representative with 8
years of experience.

What do I need to study most about
scatter plots and writing equations to be
successful on the quiz tomorrow?

Determine correlation

Determine correlation
Year Homes w/
Internet (in
millions)
1995 10.1
1998 50.6
2001 87.2
2004 129.1
2007 171.6
2010 208.6
•Create a scatter plot.
•Use the fourth and sixth set of points to write
a prediction equation
•Draw a line of best fit
•How many homes will have internet in
2020? Make a prediction. Explain how you
determined your prediction.

Determine correlation
B

Determine correlation
B
Year Homes w/
Internet (in
millions)
1995 10.1
1998 50.6
2001 87.2
2004 129.1
2007 171.6
2010 208.6

y = 13.25x – 26423.9


Prediction: 341.1 million
homes

Research will not be true









Grading scale:
1 – axes correctly
labeled
1 – points plotted
2 – line of best fit
1 – slope of line
1 – y-intercept
1 – equation of line
1 – plugging in for
correct variable
1 – correct prediction
1 – correct explantation