The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line. ŷ = bo + bịx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 2 2.5 3 4 5 Overall Grades 100 98 97 87 86 74 62 Table Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.

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The table below provides data on the number of hours spent unsupervised each day and the overall grade averages for seven randomly chosen middle school students. Using this data, we consider the equation of the regression line, \(\hat{y} = b_0 + b_1 x\), to predict the overall grade average for a middle school student based on the number of hours spent unsupervised each day. It's important to note that the correlation coefficient may or may not be statistically significant for the provided data. In practice, using the regression line to make predictions is inappropriate if the correlation coefficient lacks statistical significance.

| Hours Unsupervised | 0  | 2  | 2.5 | 3  | 4  | 5  | 6  |
|--------------------|----|----|-----|----|----|----|----|
| Overall Grades     | 100| 98 | 97  | 87 | 86 | 74 | 62 |

**Step 1 of 6:** Find the estimated slope. Round your answer to three decimal places. 

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This section asks students to calculate the estimated slope (\(b_1\)) of the regression line based on the provided data points, which is a key step in regression analysis to understand the relationship between the variables.
Transcribed Image Text:The table below provides data on the number of hours spent unsupervised each day and the overall grade averages for seven randomly chosen middle school students. Using this data, we consider the equation of the regression line, \(\hat{y} = b_0 + b_1 x\), to predict the overall grade average for a middle school student based on the number of hours spent unsupervised each day. It's important to note that the correlation coefficient may or may not be statistically significant for the provided data. In practice, using the regression line to make predictions is inappropriate if the correlation coefficient lacks statistical significance. | Hours Unsupervised | 0 | 2 | 2.5 | 3 | 4 | 5 | 6 | |--------------------|----|----|-----|----|----|----|----| | Overall Grades | 100| 98 | 97 | 87 | 86 | 74 | 62 | **Step 1 of 6:** Find the estimated slope. Round your answer to three decimal places. --- This section asks students to calculate the estimated slope (\(b_1\)) of the regression line based on the provided data points, which is a key step in regression analysis to understand the relationship between the variables.
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