Download presentation

Presentation is loading. Please wait.

Published byEvelyn Phillips Modified over 4 years ago

1
2.4 Using Linear Models 1.Modeling Real-World Data 2.Predicting with Linear Models

2
1) Modeling Real-World Data Big idea… Use linear equations to create graphs of real-world situations. Then use these graphs to make predictions about past and future trends.

3
Example 1: There were 174 words typed in 3 minutes. There were 348 words typed in 6 minutes. How many words were typed in 5 minutes? 1) Modeling Real-World Data

4
x = independent y = dependent (x, y) = (time, words typed ) (x 1, y 1 ) = (3, 174) (x 2, y 2 ) = (6, 348) (x 3, y 3 ) = (5, ?) Solution: Time (minutes) 1 2 3 4 5 6 100 200 300 400

5
Example 2: Suppose an airplane descends at a rate of 300 ft/min from an elevation of 8000ft. Draw a graph and write an equation to model the planes elevation as a function of the time it has been descending. Interpret the vertical intercept. 1) Modeling Real-World Data

6
Time (minutes) (x, y) = (time, height) (x 1, y 1 ) = (0, 8000) (x 2, y 2 ) = (10, ?) (x 3, y 3 ) = (20, ?) 102030 6000 2000 4000 8000

7
1) Modeling Real-World Data Time (minutes) Equation: Remember… y = mx + b 102030 6000 2000 4000 8000

8
2) Predicting with Linear Models You can extrapolate with linear models to make predictions based on trends.

9
Example 1: After 5 months the number of subscribers to a newspaper was 5730. After 7 months the number of subscribers was 6022. Write an equation for the function. How many subscribers will there be after 10 months? 2) Predicting with Linear Models

10
(x, y) = (months, subscribers) (x 1, y 1 ) = (5, 5730) (x 2, y 2 ) = (7, 6022) (x 3, y 3 ) = (10, ?) Equation: y = mx + b Time (months) 2 4 6 8 10 2000 4000 6000 8000

11
2) Predicting with Linear Models (x, y) = (months, subscribers) (x 1, y 1 ) = (5, 5730) (x 2, y 2 ) = (7, 6022) (x 3, y 3 ) = (10, ?) Equation: y = mx + b Time (months) 2 4 6 8 10 2000 4000 6000 8000

12
2) Predicting with Linear Models (x, y) = (months, subscribers) (x 1, y 1 ) = (5, 5730) (x 2, y 2 ) = (7, 6022) (x 3, y 3 ) = (10, ?) Equation: y = mx + b Time (months) 2 4 6 8 10 2000 4000 6000 8000

13
2) Predicting with Linear Models (x, y) = (months, subscribers) (x 1, y 1 ) = (5, 5730) (x 2, y 2 ) = (7, 6022) (x 3, y 3 ) = (10, 7000) Equation: y = mx + b Time (months) 2 4 6 8 10 2000 4000 6000 8000 y-intercept run = 4 rise = 1000

14
Scatter Plots Connect the dots with a trend line to see if there is a trend in the data

15
Types of Scatter Plots Strong, positive correlation Weak, positive correlation

16
Types of Scatter Plots Strong, negative correlation Weak, negative correlation

17
Types of Scatter Plots No correlation

18
Scatter Plots Example 1: The data table below shows the relationship between hours spent studying and student grade. a)Draw a scatter plot. Decide whether a linear model is reasonable. b)Draw a trend line. Write the equation for the line. Hours studying 315416 Grade (%) 653590744587

19
Scatter Plots Hours studying 1 2 3 4 5 6 40 50 70 60 90 80 100 (x, y) = (hours studying, grade) (3, 65) (1, 35) (5, 90) (4, 74) (1, 45) (6, 87) Equation: y = mx + b 30

20
Scatter Plots Hours studying 1 2 3 4 5 6 40 50 70 60 90 80 100 (x, y) = (hours studying, grade) (3, 65) (1, 35) (5, 90) (4, 74) (1, 45) (6, 87) a)Based on the graph, is a linear model reasonable? 30

21
Scatter Plots Hours studying 1 2 3 4 5 6 40 50 70 60 90 80 100 (x, y) = (hours studying, grade) (3, 65) (1, 35) (5, 90) (4, 74) (1, 45) (6, 87) b) Equation: y = mx + b 30 Rise = 20 Run = 2

22
Assignment p.81 #1-3, 8, 11, 12, 13, 19,

Similar presentations

Presentation is loading. Please wait....

OK

Objective: Determine the correlation of a scatter plot

Objective: Determine the correlation of a scatter plot

© 2018 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google

Ppt on simple carburetor operation Ppt on rise of buddhism and jainism Ppt on world diabetes day logo Ppt on bakery business plan Ppt on population census 2011 india Book appt online Ppt on antimicrobial activity of ginger Ppt on heterotrophic mode of nutrition in plants Download ppt on cybercrime in india Ppt on schottky diode symbol