A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.6667, s, =2.2509, y = 4.2667, s, = 1.5397, and r= -0.9156, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 1 4 4 5.1 6.5 4.9 3.9 2.4 2.8 (a) Choose the correct graph below. O A. OB. Oc. OD. 7- There appears to be relationship. (b) ý =x+O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. OB. OC. OD.

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## Analyzing a Data Set Using Scatter Diagrams and Regression

A data set is given below, consisting of the variables \( x \) and \( y \):

\[
\begin{array}{c|cccccc}
x & 1 & 1 & 4 & 4 & 6 & 6 \\
\hline
y & 5.1 & 6.5 & 4.9 & 3.9 & 2.4 & 2.8 \\
\end{array}
\]

### Tasks:

**(a) Draw a Scatter Diagram**

Select the correct graph that represents the scatter plot of the provided data set. The options are labeled A, B, C, and D.

- **Progression of Points:** Review the placement of the data points on each graph to identify patterns in the relationship between \( x \) and \( y \).

**Determine Relationship:**

Identify if the relationship appears to be linear, quadratic, or another form from the visual analysis. The options for the relationship type will usually include terms like "positive linear," "negative linear,” or "non-linear."

**(b) Calculate Least-Squares Regression Line**

Given data: \( \bar{x} = 3.8667, \, s_x = 2.2509, \, \bar{y} = 4.2667, \, s_y = 1.5397, \, r = -0.9156 \).

Calculate the line of best fit using the least-squares regression formula:

\[
y' = \text{(slope)} \times x + \text{(intercept)}
\]

Round the slope and intercept to three decimal places.

**(c) Graph the Least-Squares Regression Line**

Choose the correct graph that depicts the scatter plot with the regression line superimposed. The options are labeled A, B, C, and D:

- **Line Representation:** Ensure the line accurately reflects the calculated regression equation and visually fits the data points.

By following these steps, you can effectively represent the relationship between \( x \) and \( y \) using scatter diagrams and regression analysis. This process helps identify trends and make predictions based on the data.
Transcribed Image Text:## Analyzing a Data Set Using Scatter Diagrams and Regression A data set is given below, consisting of the variables \( x \) and \( y \): \[ \begin{array}{c|cccccc} x & 1 & 1 & 4 & 4 & 6 & 6 \\ \hline y & 5.1 & 6.5 & 4.9 & 3.9 & 2.4 & 2.8 \\ \end{array} \] ### Tasks: **(a) Draw a Scatter Diagram** Select the correct graph that represents the scatter plot of the provided data set. The options are labeled A, B, C, and D. - **Progression of Points:** Review the placement of the data points on each graph to identify patterns in the relationship between \( x \) and \( y \). **Determine Relationship:** Identify if the relationship appears to be linear, quadratic, or another form from the visual analysis. The options for the relationship type will usually include terms like "positive linear," "negative linear,” or "non-linear." **(b) Calculate Least-Squares Regression Line** Given data: \( \bar{x} = 3.8667, \, s_x = 2.2509, \, \bar{y} = 4.2667, \, s_y = 1.5397, \, r = -0.9156 \). Calculate the line of best fit using the least-squares regression formula: \[ y' = \text{(slope)} \times x + \text{(intercept)} \] Round the slope and intercept to three decimal places. **(c) Graph the Least-Squares Regression Line** Choose the correct graph that depicts the scatter plot with the regression line superimposed. The options are labeled A, B, C, and D: - **Line Representation:** Ensure the line accurately reflects the calculated regression equation and visually fits the data points. By following these steps, you can effectively represent the relationship between \( x \) and \( y \) using scatter diagrams and regression analysis. This process helps identify trends and make predictions based on the data.
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