Question 1
For the following scatterplot, what effect would the outlier have on the slope of the regression equation?
Explain your reasoning.
Question 2
The data in the table represent the amount of pressure (psi) exerted by a stamping machine (
x), and the amount of scrap brass shavings (in pounds) that are collected from the machine each hour (
y). Also shown below are the outputs from two different statistical technologies (TI-83/84 Calculator and Excel). A scatterplot of the data confirms that there is a linear association. Report the equation for predicting scrap brass shavings using words such as scrap, not
x and
y. State the slope and intercept of the prediction equation. Round all calculations to the nearest thousandth.
◦ scrap = 2.134 - 2.019(pressure); slope = 2.134 and the intercept is -2.019.
◦ scrap = -2.019 + 2.134(pressure); slope = -2.019 and the intercept is 2.134.
◦ scrap = 2.134 - 2.019(pressure); slope = -2.019 and the intercept is 2.134.
◦ scrap = -2.019 + 2.134(pressure); slope = 2.134 and the intercept is -2.019.
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