Number 20

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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Number 20
**Regression and Predictions.**

Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-2. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5.
Transcribed Image Text:**Regression and Predictions.** Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-2. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5.
**20. Diamond Prices** 

Not included in the table below is a diamond with a weight of 1.50 carats. Find the best predicted price for this diamond. Is the result close to the actual price of $16,097? What is wrong with predicting the price of a 1.50-carat diamond?

| Weight | 0.3  | 0.4  | 0.5  | 0.5  | 1.0  | 0.7  |
|--------|------|------|------|------|------|------|
| Price  | 510  | 1151 | 1343 | 1410 | 5669 | 2277 |

**Explanation:**

This table shows the price of diamonds measured at different weights in carats. The prices increase with weight, but not linearly. For example, a 1.0-carat diamond costs significantly more than a 0.7-carat diamond. To predict the price of a 1.50-carat diamond, one would need to consider the non-linear relationship, as the increase in price isn't consistent with simple doubling or direct scaling from the weights and prices given. The challenge is in the sharp increase in price per carat, especially past the 1.0-carat mark.
Transcribed Image Text:**20. Diamond Prices** Not included in the table below is a diamond with a weight of 1.50 carats. Find the best predicted price for this diamond. Is the result close to the actual price of $16,097? What is wrong with predicting the price of a 1.50-carat diamond? | Weight | 0.3 | 0.4 | 0.5 | 0.5 | 1.0 | 0.7 | |--------|------|------|------|------|------|------| | Price | 510 | 1151 | 1343 | 1410 | 5669 | 2277 | **Explanation:** This table shows the price of diamonds measured at different weights in carats. The prices increase with weight, but not linearly. For example, a 1.0-carat diamond costs significantly more than a 0.7-carat diamond. To predict the price of a 1.50-carat diamond, one would need to consider the non-linear relationship, as the increase in price isn't consistent with simple doubling or direct scaling from the weights and prices given. The challenge is in the sharp increase in price per carat, especially past the 1.0-carat mark.
Expert Solution
Step 1

The data is given as:

 

Weight Price
0.3 510
0.4 1151
0.5 1343
0.5 1410
1 5669
0.7 2277

Independent variable: Weight (x)

Dependent variable: Price(y)

 

 

Step 2

The results of the regression of y on x is obtained as : 

Statistics homework question answer, step 2, image 1

 

The regression equation is given as : 


Price = - 2007 + 7177 × Weight

 

 

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