Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. x 10 y 7.75 6.88 12 8 13.17 7.16 11 7.46 13 8.89 5 6.35 4 5.47 13 8.23 6 6.59 6 5.53 Create a scatterplot of the data. Choose the correct graph below. OA. OB. В. Oc. OD. 25 Ay 25- 25 20 25- 20 20 20 15 15 155 10 155 10 10 10 5- 0 5 10 15 20 25 05 10 15 20 25 0- O 5 10 15 20 25s 05 10 15 20 25 Find the equation of the regression line. (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. There is no trend in the data. O B. There is no characteristic of the data that is ignored by the regression line. O c. The data has a pattern that is not a straight line. OD. There is an influential point that strongly affects the graph of the regression line.

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Chapter1: Starting With Matlab
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**Finding the Equation of a Regression Line and Analyzing Scatterplots**

The task involves using the given data to find the equation of the regression line, creating a scatterplot, and identifying a characteristic of the data ignored by the regression line.

### Data Table
\[
\begin{array}{|c|c|}
\hline
x & y \\
\hline
10 & 7.75 \\
7 & 6.88 \\
12 & 13.17 \\
8 & 7.16 \\
11 & 7.46 \\
13 & 8.89 \\
4 & 6.53 \\
7 & 5.47 \\
9 & 8.3 \\
6 & 6.69 \\
9 & 5.53 \\
\hline
\end{array}
\]

### Creating a Scatterplot
The objective is to choose the correct scatterplot that represents the data points. Four scatterplot options are available, labeled A, B, C, and D. Each plot displays data points on an XY plane with axes labeled from 0 to 25.

### Finding the Equation of the Regression Line
Input fields are provided to compute:
- **y-intercept** (round to two decimal places)
- **slope** (round to three decimal places)

The regression line equation is expressed as \( \hat{y} = \).

### Identifying Data Characteristics Ignored by the Regression Line
Choose the correct option to describe a feature of the data that the regression line does not account for:
- **A.** There is no trend in the data.
- **B.** There is no characteristic of the data that is ignored by the regression line.
- **C.** The data has a pattern that is not a straight line.
- **D.** There is an influential point that strongly affects the graph of the regression line.

**Note:** The task involves identifying patterns or anomalies in the scatterplot that the regression line might overlook, such as a curved trend or outliers.
Transcribed Image Text:**Finding the Equation of a Regression Line and Analyzing Scatterplots** The task involves using the given data to find the equation of the regression line, creating a scatterplot, and identifying a characteristic of the data ignored by the regression line. ### Data Table \[ \begin{array}{|c|c|} \hline x & y \\ \hline 10 & 7.75 \\ 7 & 6.88 \\ 12 & 13.17 \\ 8 & 7.16 \\ 11 & 7.46 \\ 13 & 8.89 \\ 4 & 6.53 \\ 7 & 5.47 \\ 9 & 8.3 \\ 6 & 6.69 \\ 9 & 5.53 \\ \hline \end{array} \] ### Creating a Scatterplot The objective is to choose the correct scatterplot that represents the data points. Four scatterplot options are available, labeled A, B, C, and D. Each plot displays data points on an XY plane with axes labeled from 0 to 25. ### Finding the Equation of the Regression Line Input fields are provided to compute: - **y-intercept** (round to two decimal places) - **slope** (round to three decimal places) The regression line equation is expressed as \( \hat{y} = \). ### Identifying Data Characteristics Ignored by the Regression Line Choose the correct option to describe a feature of the data that the regression line does not account for: - **A.** There is no trend in the data. - **B.** There is no characteristic of the data that is ignored by the regression line. - **C.** The data has a pattern that is not a straight line. - **D.** There is an influential point that strongly affects the graph of the regression line. **Note:** The task involves identifying patterns or anomalies in the scatterplot that the regression line might overlook, such as a curved trend or outliers.
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