Assuming a linear function rule when the data is not linear

Oct 13, 2025 by vinooalluri.com 39 views

Which Function Rule Models the Function Over the Domain Specified in the Table Below?

When it comes to modeling functions over a specified domain, understanding the relationship between the input and output values is crucial. In this article, we will explore the concept of function rules and how they can be used to model functions over a given domain. We will examine a table of values and determine which function rule best models the function over the specified domain.

A function rule is a mathematical expression that describes the relationship between the input and output values of a function. It is typically represented as an equation, where the input value (x) is related to the output value (f(x)) through a specific operation or combination of operations. Function rules can be linear, quadratic, polynomial, or even more complex, depending on the nature of the function.

Let's examine the table of values provided below:

x	f(x)
-7	-11
-1	1
3	9
4	11
7	17

To determine which function rule models the function over the specified domain, we need to analyze the data in the table. Let's start by looking at the differences between consecutive output values.

x	f(x)	Δf(x)
-7	-11	-
-1	1	12
3	9	8
4	11	2
7	17	6

From the table above, we can see that the differences between consecutive output values are not constant. However, we can observe some patterns in the data.

The difference between f(-1) and f(-7) is 12, which is a large jump.
The difference between f(3) and f(-1) is 8, which is a smaller jump.
The difference between f(4) and f(3) is 2, which is an even smaller jump.
The difference between f(7) and f(4) is 6, which is another smaller jump.

Based on the patterns observed in the data, we can propose several function rules that may model the function over the specified domain.

Linear Function Rule: f(x) = mx + b, where m is the slope and b is the y-intercept.
Quadratic Function Rule: f(x) = ax^2 + bx + c, where a, b, and c are coefficients.
Polynomial Function Rule: f(x) = a_n x^n + a_(n-1) x^(n-1) + ... + a_1 x + a_0, where a_n, a_(n-1), ..., a_1, and a_0 are coefficients.

To determine which function rule best models the function over the specified domain, we need to test each proposed rule against the data in the table.

Linear Function Rule

Let's assume that the linear function rule f(x) = mx + b models the function over the specified domain. We can use the data in the table to find the values of m and b.

Using the points (-7, -11) and (-1, 1), we can write two equations:

-11 = m(-7) + b 1 = m(-1) + b

Solving these equations simultaneously, we get:

m = 2 b = -9

So, the linear function rule f(x) = 2x - 9 models the function over the specified domain.

Quadratic Function Rule

Let's assume that the quadratic function rule f(x) = ax^2 + bx + c models the function over the specified domain. We can use the data in the table to find the values of a, b, and c.

Using the points (-7, -11), (-1, 1), and (3, 9), we can write three equations:

-11 = a(-7)^2 + b(-7) + c 1 = a(-1)^2 + b(-1) + c 9 = a(3)^2 + b(3) + c

Solving these equations simultaneously, we get:

a = 0.5 b = 2 c = -9

So, the quadratic function rule f(x) = 0.5x^2 + 2x - 9 models the function over the specified domain.

Polynomial Function Rule

Let's assume that the polynomial function rule f(x) = a_n x^n + a_(n-1) x^(n-1) + ... + a_1 x + a_0 models the function over the specified domain. We can use the data in the table to find the values of a_n, a_(n-1), ..., a_1, and a_0.

Using the points (-7, -11), (-1, 1), (3, 9), and (4, 11), we can write four equations:

-11 = a_n (-7)^n + a_(n-1) (-7)^(n-1) + ... + a_1 (-7) + a_0 1 = a_n (-1)^n + a_(n-1) (-1)^(n-1) + ... + a_1 (-1) + a_0 9 = a_n (3)^n + a_(n-1) (3)^(n-1) + ... + a_1 (3) + a_0 11 = a_n (4)^n + a_(n-1) (4)^(n-1) + ... + a_1 (4) + a_0

Solving these equations simultaneously, we get:

a_n = 0.25 a_(n-1) = 1 a_(n-2) = 0 a_(n-3) = 0 a_(n-4) = 0 a_1 = 0 a_0 = -9

So, the polynomial function rule f(x) = 0.25x^4 + x^3 - 9 models the function over the specified domain.

In this article, we explored the concept of function rules and how they can be used to model functions over a given domain. We examined a table of values and determined which function rule best models the function over the specified domain. The linear function rule f(x) = 2x - 9, the quadratic function rule f(x) = 0.5x^2 + 2x - 9, and the polynomial function rule f(x) = 0.25x^4 + x^3 - 9 all model the function over the specified domain. However, the linear function rule f(x) = 2x - 9 is the simplest and most straightforward model, making it the most suitable choice for this particular function.
Q&A: Function Rules and Modeling Functions

In our previous article, we explored the concept of function rules and how they can be used to model functions over a given domain. We examined a table of values and determined which function rule best models the function over the specified domain. In this article, we will answer some frequently asked questions about function rules and modeling functions.

To determine which function rule models a function over a given domain, you need to analyze the data in the table of values. Look for patterns in the differences between consecutive output values. If the differences are constant, a linear function rule may be suitable. If the differences are not constant, a quadratic or polynomial function rule may be more appropriate.

Some common types of function rules include:

Linear Function Rule: f(x) = mx + b, where m is the slope and b is the y-intercept.
Quadratic Function Rule: f(x) = ax^2 + bx + c, where a, b, and c are coefficients.
Polynomial Function Rule: f(x) = a_n x^n + a_(n-1) x^(n-1) + ... + a_1 x + a_0, where a_n, a_(n-1), ..., a_1, and a_0 are coefficients.

To test a function rule against a table of values, substitute the input values from the table into the function rule and calculate the corresponding output values. Compare the calculated output values with the actual output values in the table. If the calculated output values match the actual output values, the function rule is a good model for the function over the given domain.

Some common mistakes to avoid when modeling functions include:

Assuming a linear function rule when the data is not linear: If the differences between consecutive output values are not constant, a linear function rule may not be suitable.
Using a function rule that is too complex: If the function rule is too complex, it may be difficult to interpret and may not provide a good model for the function.
Ignoring outliers or anomalies in the data: Outliers or anomalies in the data can affect the accuracy of the function rule. Make sure to check for and address any outliers or anomalies before modeling the function.

To choose the best function rule for a given function, consider the following factors:

Simplicity: Choose a function rule that is simple and easy to interpret.
Accuracy: Choose a function rule that accurately models the function over the given domain.
Relevance: Choose a function rule that is relevant to the problem or context in which the function is being used.

In this article, we answered some frequently asked questions about function rules and modeling functions. We discussed how to determine which function rule models a function over a given domain, common types of function rules, and how to test a function rule against a table of values. We also highlighted some common mistakes to avoid when modeling functions and provided guidance on how to choose the best function rule for a given function.