Transcript
Page 1: Modeling with  Linear Functions

Modeling with

Linear Functions

Chapter 2

Page 2: Modeling with  Linear Functions

Using Lines to Model Data

Section 2.1

Page 3: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

The number of Grand Canyon visitors is listed in the table for various years. Describe the data.

Slide 3

Using Lines to Model DataScattergrams

• Let v be the number (in millions) of visitors• Let t be the number of

years since 1960

Example

Solution

Page 4: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

Sketch a line that comes close to (or on) the data points.

Slide 4

Using Lines to Model DataScattergrams

The graph on the left does the best job of this.

Example Continued

Page 5: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

If the points in a scattergram of data lie close to (or on) a line, then we say that the relevant variables are approximately linearly related. For the Grand Canyon situation, variables t and v are approximately linearly related.

A model is a mathematical description of an authentic situation. We say that the description models the situation.

Slide 5

DefinitionsLinear Models

Definition

Page 6: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

A linear model is a linear function, or its graph, that describes the relationship between two quantities for an authentic situation.

• The Grand Canyon model is a linear model• Every linear model is a linear function•Functions are used to describe situations and to describe certain mathematical relationships

Slide 6

DefinitionsLinear Models

Definition

Property

Page 7: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

Use a linear model to predict the number of visitors in 2010.

Slide 7

Using a Linear Model to Make a Prediction and an Estimate

Using a Linear Model to Make Estimates and Predictions

• Year 2010 corresponds to t = 50: 2010 – 1960 = 50• Locate point on linear model for t = 50• The v-coordinate is approximately 5.6• The model estimates 5.6 million visitors in 2010

Example

Solution

Page 8: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

Use a linear model to estimate the year there ware 4 million visitors.

Slide 8

Using a Linear Model to Make a Prediction and an Estimate

Using a Linear Model to Make Estimates and Predictions

• 4 million visitors corresponds to v = 4• The corresponding v-coordinate is approx. t = 32•According to the linear model, there were 4 million visitors in the year 1960 + 32 = 1992

Example

Solution

Page 9: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3ed

whether a linear function would model it well.

•Situation 1 Close to line-describes a linear function•Situation 2 & 3 Points do not lie close to one line•A linear model would not describe these situations

Section 2.1

Consider the scattergrams. Determine

Slide 9

Deciding Whether to Use a Linear Function to Model Data

When to Use a Linear Function to Model Data

Situation 1 Situation 2 Situation 3

Example

Solution

Page 10: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1

The wild Pacific Northwest salmon populations are listed in the table for various years.

1. Let P be the salmon

Slide 10

Intercepts of a Model; Model BreakdownIntercepts of a Model and Model Breakdown

population (in millions) at t years since 1950. Find a linear model that describes the situation.

•Data is described in terms of P and t in a table•Sketch a scattergram (see the next slide)

Example

Solution

Page 11: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1 Slide 11

Intercepts of a Model; Model BreakdownIntercepts of a Model and Model Breakdown

2. Find the P-intercept of the model. What does it mean?

3. Use the model to predict when the salmon will become extinct.

Example Continued

Page 12: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1 Slide 12

Intercepts of a Model; Model BreakdownIntercepts of a Model and Model Breakdown

• P- intercept is (0, 13)• When P = 13, t = 0 (the year 1950)• According to the model, there were 13 million

salmon in 1950• T-intercept is (45, 0)• When P = 0, t = 45 (the year 1950 + 45 = 1995• Salomon are still alive today• Our model is a false prediction

Solution

Page 13: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1 Slide 13

DefinitionIntercepts of a Model and Model Breakdown

For situations that can be modeled by a function whose independent variable is t:

when we part of the model whose t-coordinates are not between the t-coordinates of any two data points.

Definition

We perform interpolation

Page 14: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1 Slide 14

DefinitionIntercepts of a Model and Model Breakdown

We perform extrapolation when we use a part of the model whose t-coordinates are not between the t-coordinates of any two data points.

When a model gives a prediction that does not make sense or an estimate that is not a good approximation, we say that model breakdown has occurred.

Definition

Definition

Page 15: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1 Slide 15

Modifying a ModelIntercepts of a Model and Model Breakdown

In 2002, there were 3 million wild Pacific Northwest salmon. For each of the following scenarios that follow, use the data for 2002 and the data in the table to sketch a model. Let P be the wild Pacific Northwest salmon population (in millions) at t years since 1950.

1. The salmon population levels off at 10 million.

2. The salmon become extinct.

Example

Page 16: Modeling with  Linear Functions

Lehmann, Intermediate Algebra, 3edSection 2.1 Slide 16

Modifying a ModelIntercepts of a Model and Model Breakdown

Solution


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