To determine the least squares regression line from a set of points, you typically need the data points (x, y) themselves. However, since I don't have access to the data table you mentioned, I can guide you on how to calculate the least squares regression line.
Generally, the least squares regression line equation has the form:
\[ y = mx + b \]
Where:
- \( m \) is the slope of the line.
- \( b \) is the y-intercept.
You can use a calculator or spreadsheet software (like Microsoft Excel or Google Sheets) to plot the data points and calculate the regression line. Here’s how you can do that:
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Input your data: Enter your x values in one column and your corresponding y values in another column.
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Use the regression tool:
- In Excel:
- Select your data points, go to the "Insert" tab, choose "Scatter," and then select "Scatter with Straight Lines."
- After plotting, click on the data points on the chart, then select "Add Trendline."
- Choose "Linear" and ensure "Display Equation on chart" is checked.
- In Google Sheets:
- Create a scatter plot from the data.
- Click on the chart and hit the "three dots" in the upper-right corner, then choose "Edit chart."
- In the "Customize" tab, find the "Series" section and check "Trendline" to add a linear trendline. You can also display the equation.
- In Excel:
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Extract the coefficients: The slope \( m \) and intercept \( b \) will be given in the equation displayed on your chart.
From what you've written, it seems you have some options for the least squares regression equation:
- \( y = 0.25x - 5.55 \)
- \( y = 5.55x + 0.25 \)
- \( y = 5.55x - 0.25 \)
- \( y = 0.25x + 5.55 \)
Without the data, it is difficult to determine which option is correct. You would need to compare these options against the calculated regression line from your data.
If you can provide the data, I can help you more specifically. Otherwise, you can follow the above steps to determine the correct least squares regression line from your points.