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Home Q & A Board Science-Related Homework Help Mathematics Statistics and Probability
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AsadQ1 AsadQ1
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3 months ago
Use the following to answer the questions below:

A biologist collected data on a sample of 20 porcupines. She wants to be able to predict the body mass of a porcupine (in grams) based on the length of the porcupine (in cm).
Her least squares regression equation is   where M is the mass.


A scatterplot of the biologist's data, with the least squares regression line, is provided. There is a clear outlier in the lower left corner of the plot. How would removing this point from the dataset most likely affect the correlation between body length (cm) and body mass (g)?

A scatterplot with a regression line shows the relationship between length and mass. The horizontal axis is labeled length (centimeters) and has markings from 30 to 60 in increments of 5.  The vertical axis is labeled mass (grams) and has markings from 1000 to 8000 in increments of 1000. A regression line starts from (33, 2500), increases toward the right, and ends at (59, 7000). The dots are randomly scattered across the regression line, such that a few dots lie above the regression line, a few dots lie below the regression line, and a few dots lie on the regression line. The concentration of the dots is more between the points 47 and 60 on the horizontal axis and between the points, 5000 and 7500 on the vertical axis. The dots are plotted as follows: (33.5, 1500), (45, 6700), (46, 6500), (46, 5500), (46.5, 3000), (50, 7000), (51, 5000), (52.5, 7100), (53.5, 5100), (54, 6100), (54, 6200), (54, 6500), (55, 6000), (55, 6100), (56, 6300), (56, 6600), (59, 6200), (59, 6300), and (59, 7200). All values are approximate.


▸ It would make the correlation weaker.

▸ It would make the correlation stronger.

▸ It would have no impact on the correlation between body length and body mass.
Textbook 
Statistics: Unlocking the Power of Data

Statistics: Unlocking the Power of Data


Edition: 3rd
Authors:
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bryrdanbryrdan
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AsadQ1 Author
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3 months ago
Thank you, thank you, thank you!
annakc
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Yesterday
Correct Slight Smile TY
fxinternational
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2 hours ago
Brilliant ツ
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