new footwear manufacturer is trying to compete with the major brands by nvesting heavily in Research and Development (R&D). Their goal is to produce a remium lifestyle sneaker that is more comfortable, longer lasting and more stylish han any of their competitors. Below are some data on dollars spent on R&D and ew customers acquired for the last 5 quarters. Eegression Equation: Y=0.5+1.35X New Customers R&D Dollars Acquired in millions) (in thousands) 12 12 15 13 14 18 18 20 25 ased on looking at the numbers and/or sketching a scatter-plot, what conclusion an we draw about the data? O The variables are negatively correlated O You cannot tell until we perform some calculations O There does not appear to be a strong correlation between the variables O The variables are positively correlated

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A new footwear manufacturer is trying to compete with the major brands by
investing heavily in Research and Development (R&D). Their goal is to produce a
premium lifestyle sneaker that is more comfortable, longer lasting and more stylish
than any of their competitors. Below are some data on dollars spent on R&D and
new customers acquired for the last 5 quarters.
Regression Equation: Y= 0.5 + 1.35X
New Customers
R&D Dollars
Acquired
(in millions)
(in thousands)
8
12
12
15
13
18
14
20
18
25
Based on looking at the numbers and/or sketching a scatter-plot, what conclusion
can we draw about the data?
The variables are negatively correlated
You cannot tell until we perform some calculations
There does not appear to be a strong correlation between the variables
The variables are positively correlated
Transcribed Image Text:A new footwear manufacturer is trying to compete with the major brands by investing heavily in Research and Development (R&D). Their goal is to produce a premium lifestyle sneaker that is more comfortable, longer lasting and more stylish than any of their competitors. Below are some data on dollars spent on R&D and new customers acquired for the last 5 quarters. Regression Equation: Y= 0.5 + 1.35X New Customers R&D Dollars Acquired (in millions) (in thousands) 8 12 12 15 13 18 14 20 18 25 Based on looking at the numbers and/or sketching a scatter-plot, what conclusion can we draw about the data? The variables are negatively correlated You cannot tell until we perform some calculations There does not appear to be a strong correlation between the variables The variables are positively correlated
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