Bivariate data for the quantitative variables x and y are given in the table below. These data are plotted in the scatter plot shown next to the table. In the scatter plot, sketch an approximation of the least-squares regression line for the data. y 3.3 8.2 11+ 5.9 4.8 7.6 2.8 10+ 8.6 1.4 ? 8.8 1.3 7.2 6.0 4.1 7.9 4.4 6.8 6+ 3.3 9.2 5+ 5.2 7.8 7.2 2.7 4+ 3.6 9.8 2.8 10.0 5.4 6.1 2+ Xx 5.7 4.7 6.5 5.8 + 1 + 6.5 3.9 5 6 10 11 7.7 3.2

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**Bivariate Data Analysis**

Bivariate data for the quantitative variables \( x \) and \( y \) are given in the table below. These data are plotted in the scatter plot shown next to the table. In the scatter plot, sketch an approximation of the least-squares regression line for the data.

**Data Table**

| \( x \) | \( y \) |
|--------|--------|
| 3.3    | 8.2    |
| 5.9    | 4.8    |
| 7.6    | 2.8    |
| 8.6    | 1.4    |
| 8.8    | 1.3    |
| 7.2    | 6.0    |
| 4.1    | 7.9    |
| 4.4    | 6.8    |
| 3.3    | 9.2    |
| 5.2    | 7.8    |
| 7.2    | 2.7    |
| 3.6    | 9.8    |
| 2.8    | 10.0   |
| 5.4    | 6.1    |
| 5.7    | 4.7    |
| 6.5    | 5.8    |
| 6.5    | 3.9    |
| 7.7    | 3.2    |

**Scatter Plot Explanation**

The scatter plot visually represents the data points from the table on a graph, with \( x \)-values on the horizontal axis and \( y \)-values on the vertical axis. Each point corresponds to a pair of \( x \) and \( y \) values from the table.

There is a clear trend observed in the scatter plot, where the points somewhat follow a downward trend, suggesting a potential negative correlation between \( x \) and \( y \). To better understand this relationship, you can sketch an approximation of the least-squares regression line, which aims to minimize the distance between the line and all of the points in the dataset.
Transcribed Image Text:**Bivariate Data Analysis** Bivariate data for the quantitative variables \( x \) and \( y \) are given in the table below. These data are plotted in the scatter plot shown next to the table. In the scatter plot, sketch an approximation of the least-squares regression line for the data. **Data Table** | \( x \) | \( y \) | |--------|--------| | 3.3 | 8.2 | | 5.9 | 4.8 | | 7.6 | 2.8 | | 8.6 | 1.4 | | 8.8 | 1.3 | | 7.2 | 6.0 | | 4.1 | 7.9 | | 4.4 | 6.8 | | 3.3 | 9.2 | | 5.2 | 7.8 | | 7.2 | 2.7 | | 3.6 | 9.8 | | 2.8 | 10.0 | | 5.4 | 6.1 | | 5.7 | 4.7 | | 6.5 | 5.8 | | 6.5 | 3.9 | | 7.7 | 3.2 | **Scatter Plot Explanation** The scatter plot visually represents the data points from the table on a graph, with \( x \)-values on the horizontal axis and \( y \)-values on the vertical axis. Each point corresponds to a pair of \( x \) and \( y \) values from the table. There is a clear trend observed in the scatter plot, where the points somewhat follow a downward trend, suggesting a potential negative correlation between \( x \) and \( y \). To better understand this relationship, you can sketch an approximation of the least-squares regression line, which aims to minimize the distance between the line and all of the points in the dataset.
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