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Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Warm Up 1. Find the slope and y-intercept of the line that passes through (4, 20) and (20,

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Presentation on theme: "Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Warm Up 1. Find the slope and y-intercept of the line that passes through (4, 20) and (20,"— Presentation transcript:

1 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Warm Up 1. Find the slope and y-intercept of the line that passes through (4, 20) and (20, 24). The population of a town is decreasing at a rate of 1.8% per year. In 1990, there were 4600 people. 2. Write an exponential decay function to model this situation. 3. Find the population in 2010. y = 4600(0.982) t 3199

2 Holt Algebra 1 9-4 Transforming Quadratic Functions Compare the graph of f(x) = x 2 to the graph of g(x) = –x 2 – 4 The graph of g(x) = -x 2 - 4 is the same width as the graph of f(x) = x 2. The graph of g(x) = -x 2 - 4 opens downward.

3 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Compare linear, quadratic, and exponential models. Given a set of data, decide which type of function models the data and write an equation to describe the function. Objectives

4 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Look at the tables and graphs below. The data show three ways you have learned that variable quantities can be related. The relationships shown are linear, quadratic, and exponential.

5 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Look at the tables and graphs below. The data show three ways you have learned that variable quantities can be related. The relationships shown are linear, quadratic, and exponential.

6 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Look at the tables and graphs below. The data show three ways you have learned that variable quantities can be related. The relationships shown are linear, quadratic, and exponential.

7 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models In the real world, people often gather data and then must decide what kind of relationship (if any) they think best describes their data.

8 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Graph each data set. Which kind of model best describes the data? BoxesReams of paper 110 550 20200 50500

9 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Graph each data set. Which kind of model best describes the data? xy –30.30 –20.44 01 11.5 22.25 33.38

10 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Graph each data set. Which kind of model best describes the data? Time(h)Bacteria 024 196 2384 31536 46144

11 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Another way to decide which kind of relationship (if any) best describes a data set is to use patterns.

12 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Look for a pattern in each data set to determine which kind of model best describes the data. Time (s)Height (ft) 04 168 2100 3 468 Height of golf ball Time (yr)Amount ($) 01000.00 11169.86 21368.67 31601.04 Money in CD

13 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Data (1)Data (2) –210 –11 0–2 11 210

14 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models After deciding which model best fits the data, you can write a function. Recall the general forms of linear, quadratic, and exponential functions.

15 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models Use the data in the table to describe how the number of people changes. Then write a function that models the data. Use your function to predict the number of people who received the e-mail after one week. Time (Days)Number of People Who Received the E-mail 08 156 2392 32744 E-mail forwarding

16 Holt Algebra 1 11-4 Linear, Quadratic, and Exponential Models When the independent variable changes by a constant amount, linear functions have constant first differences. quadratic functions have constant second differences. exponential functions have a constant ratio. Remember! HW pp. 793-795/8-19,23-29,32-40


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