What if you've plotted some data points, with the coordinates of the points representing the number of years a teacher has been teaching at a school and the coordinates representing his salary? Suppose that you've found the line of best fit to be . If the teacher has been teaching at the school for 8 years, could you use the line of best fit to predict how much his salary will be after he's taught for 12 years? How would you do it? In this Concept, you'll learn how to answer realworld questions like these by using a linear model.
Guidance
The previous lessons have focused on writing equations and determining lines of best fit. When we fit a line to data using interpolation, extrapolation, or linear regression, it is called linear modeling.
A model is an equation that best describes the data graphed in the scatter plot.
Example A
Dana heard something very interesting at school. Her teacher told her that if you divide the circumference of a circle by its diameter you always get the same number. She tested this statement by measuring the circumference and diameter of several circular objects. The following table shows her results.
From this data, estimate the circumference of a circle whose diameter is 12 inches.
Solution:
Begin by creating a scatter plot and drawing the line of best fit.
Object  Diameter (inches)  Circumference (inches) 

Table  53  170 
Soda can  2.25  7.1 
Cocoa tin  4.2  12.6 
Plate  8  25.5 
Straw  0.25  1.2 
Propane tank  13.3  39.6 
Hula hoop  34.25  115 
Find the equation of the line of best fit using points (0.25, 1.2) and (8, 25.5).
In this problem, the . This number should be very familiar to you—it is the number pi rounded to the hundredths place. Theoretically, the circumference of a circle divided by its diameter is always the same and it equals 3.14 or .
Example B
Using Dana's data from Example A, estimate the circumference of a circle whose diameter is 25 inches.
Solution:
The equation of the relationship between diameter and circumference from Example A applies here.
A circle with a diameter of 25 inches will have a circumference that is approximately 78.92 inches.
Example C
Using Dana's data from Example A, estimate the circumference of a circle whose diameter is 60 inches.
Solution:
The equation of the relationship between diameter and circumference from Example A applies here.
A circle with a diameter of 60 inches will have a circumference that is approximately 188.82 inches.
Video Review
Guided Practice
A cylinder is filled with water to a height of 73 centimeters. The water is drained through a hole in the bottom of the cylinder and measurements are taken at twosecond intervals. The table below shows the height of the water level in the cylinder at different times.
Time (seconds)  Water level (cm) 

0.0  73 
2.0  63.9 
4.0  55.5 
6.0  47.2 
8.0  40.0 
10.0  33.4 
12.0  27.4 
14.0  21.9 
16.0  17.1 
18.0  12.9 
20.0  9.4 
22.0  6.3 
24.0  3.9 
26.0  2.0 
28.0  0.7 
30.0  0.1 
Find the water level at 15 seconds.
Solution:
Begin by graphing the scatter plot. As you can see below, a straight line does not fit the majority of this data. Therefore, there is no line of best fit. Instead, use interpolation.
To find the value at 15 seconds, connect points (14, 21.9) and (16, 17.1) and find the equation of the straight line.
Equation
Substitute and obtain .
Practice
Sample explanations for some of the practice exercises below are available by viewing the following video. Note that there is not always a match between the number of the practice exercise in the video and the number of the practice exercise listed in the following exercise set. However, the practice exercise is the same in both. CK12 Basic Algebra: Using a Linear Model (12:14)
 What is a mathematical model?
 What is linear modeling ? What are the options to determine a linear model?
 Using the Water Level data, use interpolation to determine the height of the water at 17 seconds.
Use the Life Expectancy table below to answer the questions.
 Make a scatter plot of the data.
 Use a line of best fit to estimate the life expectancy of a person born in 1955.
 Use linear interpolation to estimate the life expectancy of a person born in 1955.
 Use a line of best fit to estimate the life expectancy of a person born in 1976.
 Use linear interpolation to estimate the life expectancy of a person born in 1976.
 Use a line of best fit to estimate the life expectancy of a person born in 2012.
 Use linear extrapolation to estimate the life expectancy of a person born in 2012.
 Which method gives better estimates for this data set? Why?
Birth Year  Life expectancy in years 

1930  59.7 
1940  62.9 
1950  68.2 
1960  69.7 
1970  70.8 
1980  73.7 
1990  75.4 
2000  77 
The table below lists the high temperature for the first day of each month in 2006 in San Diego, California (Weather Underground). Use this table to answer the questions.
 Draw a scatter plot of the data.
 Use a line of best fit to estimate the temperature in the middle of the month (month 4.5).
 Use linear interpolation to estimate the temperature in the middle of the month (month 4.5).
 Use a line of best fit to estimate the temperature for month 13 (January 2007).
 Use linear extrapolation to estimate the temperature for month 13 (January 2007).
 Which method gives better estimates for this data set? Why?
Month number  Temperature 

1  63 
2  66 
3  61 
4  64 
5  71 
6  78 
7  88 
8  78 
9  81 
10  75 
11  68 
12  69 
Mixed Review
 Simplify .
 Solve for .
 Determine the final cost. Original cost of jacket: $45.00; 15% markup; and 8% sales tax.
 Write as a fraction: 0.096.
 Is this function an example of direct variation? . Explain your answer.

The following data shows the number of youthaged homicides at school during various years (source:
http://nces.ed.gov/programs/crimeindicators/crimeindicators2009/tables/table_01_1.asp
).
 Graph this data and connect the data points.
 What conclusions can you make regarding this data?
 There seems to be a large drop in school homicides between 1999 and 2001. What could have happened to cause such a large gap?
 Make a prediction about 2009 using this data.