Constructing Models (College Board AP® Precalculus): Study Guide
Polynomial models
How can a model be constructed from a contextual scenario?
A model is a function that represents a real-world situation mathematically
A model can be constructed based on restrictions identified in a mathematical or contextual scenario
These restrictions come from the given information, such as
specific data values
initial conditions
or known behaviors of the quantities involved
The general approach is
Identify the appropriate function type
this is covered in the Selecting Polynomial Models study guide
Use the given data or conditions to set up equations involving the unknown constants in the function
Solve the system of equations to find the values of the constants
How do you construct a polynomial model from data points?
If you are given data points and told to use a polynomial model of a specific form (e.g.
)
you can find the unknown constants by substituting each data point into the equation
Each data point
gives you one equation
You need as many data points as there are unknown constants
E.g. a quadratic
has 3 unknowns (
,
,
),
so you need 3 data points to set up 3 equations
A linear model
has 2 unknowns
so you need 2 data points
Once you have the system of equations
solve for the unknown constants
You can solve algebraically (substitution, elimination)
or you can use a graphing calculator to solve the system
How can a model be constructed using transformations?
A model of a data set or a contextual scenario can be constructed using transformations of a parent function
If you recognize that a data set or scenario follows the shape of a known parent function (e.g.
,
), you can apply transformations to fit the data
Vertical and horizontal translations (shifts)
Vertical and horizontal dilations (stretches/compressions)
E.g. if data appears to follow a parabola with its vertex at
, opening upward
you might model it as
and use a data point to find
How can technology be used to construct a model?
A model of a data set can be constructed using technology and regressions
A regression uses an algorithm to find the function of a given type that best fits the data
Available regression types for polynomial models include:
Linear regression
fits a model of the form
Quadratic regression
fits a model of the form
Cubic regression
fits a model of the form
Quartic regression
fits a model of the form
To perform a regression on a graphing calculator
Enter the data into lists
Select the appropriate regression type
The calculator will output the values of the constants
Examiner Tips and Tricks
On the exam, if you are asked to write equations that can be used to find the constants in a model, make sure you show the equations before solving them.
This is often a separate scoring point from actually finding the values of the constants
On a calculator part of the exam, you can use your graphing calculator to solve systems of equations.
So even if you struggle with the algebra, you can still earn the point for finding the correct values
Worked Example
A town's population, in thousands, is recorded at three different times. At time years, the population was 12 thousand. At
years, the population was 15.6 thousand. At
years, the population was 16.8 thousand.
The population can be modeled by the function given by
, where
is the population, in thousands, and
is the number of years since the population was first recorded.
(a) Use the given data to write three equations that can be used to find the values for constants ,
, and
in the expression for
.
Answer:
Substitute each data point into
(b) Find the values for ,
, and
as decimal approximations.
Answer:
From the first equation
Substitute into the other two equations:
Multiplying equation 1 by 2
Subtracting equation 3 from equation 2
Substitute that value of into one of the original equations and solve for
E.g., substituting into equation 1 gives
Those are the three answers you are looking for
Round the answer for
to 3 decimal places, to give the decimal approximation
,
,
Piecewise-defined models
What is a piecewise-defined function model?
A piecewise-defined function model can be constructed through a combination of modeling techniques
A piecewise-defined model is appropriate when a data set or contextual scenario demonstrates different characteristics over different intervals
E.g. a quantity might increase linearly for a period, then remain constant, then decrease
Each 'piece' of the model captures the behavior over one interval
How do you construct a piecewise-defined model?
Identify the intervals where the behavior changes
Look for points where the pattern or trend shifts
Choose an appropriate function type for each interval
One interval might be best modeled by a linear function, another by a quadratic, etc.
Construct each piece separately
Use the techniques for polynomial models, above
I.e. substituting data points, using transformations, or regression
Combine the pieces into a single piecewise-defined function
Be sure to specify the domain for each piece
Make sure the domain intervals do not overlap
Pay attention to whether endpoints use
or
Depending on the context, the pieces may or may not need to connect at the boundary points
In many real-world models, the function value is expected to be the same from both sides at the join point
Worked Example
A city's water reservoir is being filled. For the first 5 hours (), water flows in at a constant rate, and the volume of water in the reservoir, in thousands of gallons, is given by
.
After 5 hours, the flow rate decreases. At ,
, and
, the volumes are 50, 58, and 62 thousand gallons respectively.
(a) Determine a quadratic model of the form for the volume of water in the reservoir for the interval
.
Answer:
Substitute each data point into
:
:
:
Subtracting equation 1 from equation 2 gives
Subtracting equation 2 from equation 3 gives
Equations 4 and 5 are simultaneous equations in and
only
Subtracting equation 4 from equation 5 gives
Substitute that back into equation 4 and solve for
Substitute those values into equation 1 and solve for
Therefore
(b) Write a piecewise-defined function that models the volume of water in the reservoir for
.
Answer:
Put the two pieces together
Be sure to indicate the correct, non-overlapping intervals for the two pieces
Rational models
When is a rational function model appropriate?
Data sets and aspects of contextual scenarios involving quantities that are inversely proportional can often be modeled by rational functions
Two quantities are inversely proportional when
one quantity increases as the other decreases
and their product is constant
If
is inversely proportional to
,
then
for some constant
More generally,
might be inversely proportional to a power of
E.g.
is inversely proportional to
in which case
Examples of inverse proportionality in context:
The time to complete a job is inversely proportional to the number of workers
assuming each worker works at the same rate
The gravitational force between two objects is inversely proportional to the square of the distance between them
The electromagnetic force between two charged particles is also inversely proportional to the square of the distance between them
How do you construct a rational function model?
Identify that the relationship involves inverse proportionality
Look for language like "inversely proportional to"
or data where one quantity decreases as another increases
with their product roughly constant
Set up the general form of the model
E.g.
or
, depending on the relationship
More complex rational models may take the form
(a transformed reciprocal function)
Use given data to find the unknown constant(s)
Substitute a known input-output pair and solve for the constant
Examiner Tips and Tricks
If a question describes a quantity that "varies inversely" with another, this is a direct signal to use a rational function model.
Remember that for an inversely proportional relationship , the product
is constant.
This is a quick way to verify that a data set is inversely proportional
Worked Example
A scientist is studying the intensity of a light source. The intensity , measured in lumens per square meter, at a distance
meters from the source is inversely proportional to the square of the distance. At a distance of 2 meters, the intensity is measured to be 45 lumens per square meter.
(a) Construct a model for the intensity as a function of the distance
.
Answer:
Since is inversely proportional to
, you can write
Use the data point to find
Therefore
(b) Use the model to predict the intensity at a distance of 5 meters from the source.
Answer:
Substitute into the answer from part (a)
The intensity at a distance of 5 meters is 7.2 lumens per square meter
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