**Analysis of Online Auction Data Using Regression** This section explores predicting the number of bids an item will receive based on its list price, using data from online auctions. ### Regression Analysis The table presents list prices and the corresponding number of bids received for five randomly selected items. The regression line equation is given by: \[ \hat{y} = b_0 + b_1 x \] This equation is used to predict the number of bids (\(\hat{y}\)) based on the list price (\(x\)). Note that the correlation coefficient derived may not always be statistically significant for the data provided. In practice, avoid using the regression line for predictions if the correlation coefficient does not demonstrate statistical significance. ### Data Table | Price in Dollars (\(x\)) | Number of Bids (\(y\)) | |--------------------------|------------------------| | 21 | 1 | | 23 | 2 | | 29 | 4 | | 43 | 5 | | 50 | 7 | ### Summation Table This table contains calculations necessary for determining the regression line and correlation coefficient. | Bid | \(x\) | \(y\) | \(xy\) | \(x^2\) | \(y^2\) | |-----|-------|-------|--------|---------|---------| | 1 | 21 | 1 | 21 | 441 | 1 | | 2 | 23 | 2 | 46 | 529 | 4 | | 3 | 29 | 4 | 116 | 841 | 16 | | 4 | 43 | 5 | 215 | 1849 | 25 | | 5 | 50 | 7 | 350 | 2500 | 49 | The summation table provides the variables needed for calculations in regression analysis, such as the sums of \(x\), \(y\), \(xy\), \(x^2\), and \(y^2\). These variables aid in determining the slope (\(b_1\)) and intercept (\(b_0\)) for the regression line and in assessing the correlation between the list price and the number of bids.
**Analysis of Online Auction Data Using Regression** This section explores predicting the number of bids an item will receive based on its list price, using data from online auctions. ### Regression Analysis The table presents list prices and the corresponding number of bids received for five randomly selected items. The regression line equation is given by: \[ \hat{y} = b_0 + b_1 x \] This equation is used to predict the number of bids (\(\hat{y}\)) based on the list price (\(x\)). Note that the correlation coefficient derived may not always be statistically significant for the data provided. In practice, avoid using the regression line for predictions if the correlation coefficient does not demonstrate statistical significance. ### Data Table | Price in Dollars (\(x\)) | Number of Bids (\(y\)) | |--------------------------|------------------------| | 21 | 1 | | 23 | 2 | | 29 | 4 | | 43 | 5 | | 50 | 7 | ### Summation Table This table contains calculations necessary for determining the regression line and correlation coefficient. | Bid | \(x\) | \(y\) | \(xy\) | \(x^2\) | \(y^2\) | |-----|-------|-------|--------|---------|---------| | 1 | 21 | 1 | 21 | 441 | 1 | | 2 | 23 | 2 | 46 | 529 | 4 | | 3 | 29 | 4 | 116 | 841 | 16 | | 4 | 43 | 5 | 215 | 1849 | 25 | | 5 | 50 | 7 | 350 | 2500 | 49 | The summation table provides the variables needed for calculations in regression analysis, such as the sums of \(x\), \(y\), \(xy\), \(x^2\), and \(y^2\). These variables aid in determining the slope (\(b_1\)) and intercept (\(b_0\)) for the regression line and in assessing the correlation between the list price and the number of bids.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
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![**Analysis of Online Auction Data Using Regression**
This section explores predicting the number of bids an item will receive based on its list price, using data from online auctions.
### Regression Analysis
The table presents list prices and the corresponding number of bids received for five randomly selected items. The regression line equation is given by:
\[
\hat{y} = b_0 + b_1 x
\]
This equation is used to predict the number of bids (\(\hat{y}\)) based on the list price (\(x\)). Note that the correlation coefficient derived may not always be statistically significant for the data provided. In practice, avoid using the regression line for predictions if the correlation coefficient does not demonstrate statistical significance.
### Data Table
| Price in Dollars (\(x\)) | Number of Bids (\(y\)) |
|--------------------------|------------------------|
| 21 | 1 |
| 23 | 2 |
| 29 | 4 |
| 43 | 5 |
| 50 | 7 |
### Summation Table
This table contains calculations necessary for determining the regression line and correlation coefficient.
| Bid | \(x\) | \(y\) | \(xy\) | \(x^2\) | \(y^2\) |
|-----|-------|-------|--------|---------|---------|
| 1 | 21 | 1 | 21 | 441 | 1 |
| 2 | 23 | 2 | 46 | 529 | 4 |
| 3 | 29 | 4 | 116 | 841 | 16 |
| 4 | 43 | 5 | 215 | 1849 | 25 |
| 5 | 50 | 7 | 350 | 2500 | 49 |
The summation table provides the variables needed for calculations in regression analysis, such as the sums of \(x\), \(y\), \(xy\), \(x^2\), and \(y^2\). These variables aid in determining the slope (\(b_1\)) and intercept (\(b_0\)) for the regression line and in assessing the correlation between the list price and the number of bids.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F791b4276-9ad4-4af3-a4a1-ba0c7f33553b%2F17181b27-eeb3-4008-8e12-29905b3948ea%2Fmcdx6x.jpeg&w=3840&q=75)
Transcribed Image Text:**Analysis of Online Auction Data Using Regression**
This section explores predicting the number of bids an item will receive based on its list price, using data from online auctions.
### Regression Analysis
The table presents list prices and the corresponding number of bids received for five randomly selected items. The regression line equation is given by:
\[
\hat{y} = b_0 + b_1 x
\]
This equation is used to predict the number of bids (\(\hat{y}\)) based on the list price (\(x\)). Note that the correlation coefficient derived may not always be statistically significant for the data provided. In practice, avoid using the regression line for predictions if the correlation coefficient does not demonstrate statistical significance.
### Data Table
| Price in Dollars (\(x\)) | Number of Bids (\(y\)) |
|--------------------------|------------------------|
| 21 | 1 |
| 23 | 2 |
| 29 | 4 |
| 43 | 5 |
| 50 | 7 |
### Summation Table
This table contains calculations necessary for determining the regression line and correlation coefficient.
| Bid | \(x\) | \(y\) | \(xy\) | \(x^2\) | \(y^2\) |
|-----|-------|-------|--------|---------|---------|
| 1 | 21 | 1 | 21 | 441 | 1 |
| 2 | 23 | 2 | 46 | 529 | 4 |
| 3 | 29 | 4 | 116 | 841 | 16 |
| 4 | 43 | 5 | 215 | 1849 | 25 |
| 5 | 50 | 7 | 350 | 2500 | 49 |
The summation table provides the variables needed for calculations in regression analysis, such as the sums of \(x\), \(y\), \(xy\), \(x^2\), and \(y^2\). These variables aid in determining the slope (\(b_1\)) and intercept (\(b_0\)) for the regression line and in assessing the correlation between the list price and the number of bids.
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