5.7 predicting with linear models objective : deciding when to use a linear model objective : use a...
TRANSCRIPT
![Page 1: 5.7 Predicting with Linear Models Objective : Deciding when to use a linear model Objective : Use a linear model to make a real life prediction. 1 2 A](https://reader036.vdocument.in/reader036/viewer/2022082612/5697bf721a28abf838c7eb1d/html5/thumbnails/1.jpg)
5.7 Predicting with Linear Models
Objective : Deciding when to use a linear modelObjective : Use a linear model to make a real life prediction.
12
A good way to decide whether data can be representedby a linear model is to draw a scatter plot of the data.
![Page 2: 5.7 Predicting with Linear Models Objective : Deciding when to use a linear model Objective : Use a linear model to make a real life prediction. 1 2 A](https://reader036.vdocument.in/reader036/viewer/2022082612/5697bf721a28abf838c7eb1d/html5/thumbnails/2.jpg)
You are a restaurant owner and are making a menu with new pricing. You wantthe menu to last 3 years. By how much would you increase the prices so that theywill keep up with increases in costs over the next 3 years?
The manager of the restaurant made the following table and scatter plot.
Year Fish Meat
1991
3 .75 2.50
1993
6.15
2.70
1995
5.25 3.00
1997
4.05 3.30
1999
8.75 3.50
Average price per pound.
Average price per pound in
$
0
1
2
3
4
5
6
7
8
9
Year
1991 1993 1995 1997 1999
Fish in blueMeat in red
Draw a line of best fit for meat. There is not a good line for fish
![Page 3: 5.7 Predicting with Linear Models Objective : Deciding when to use a linear model Objective : Use a linear model to make a real life prediction. 1 2 A](https://reader036.vdocument.in/reader036/viewer/2022082612/5697bf721a28abf838c7eb1d/html5/thumbnails/3.jpg)
When you use a linear model to estimate data points thatare not given, you are using linear interpolation or linearextrapolation.
Linear interpolation is a method of estimating the coordinates of a point that lies between two given data points.
Example: Go back to the graph and estimate the price per pound of meat in 1998.
Linear extrapolation is a method of estimating thecoordinates of a point that lies to the right or left of the given data.
Example: Go back to the graph and estimate the price per pound of meat in 2003.
About $3.40 per lb
About $4.00 per lb