Question 38. You have performed a linear regression analysis to explore sunflowers' growth (in meters per month) depending on the watering (in litres per day). You have estimated the regression coefficient to be B = 1.6. What can you conclude? a) There is a signifieat correlation between watering and growth. b) An average sunflower growths 1.6 meters per month. e) If you give it an additional litre of water per day, there will be an additional average growth of 1.6 meters per month. d) According to the model assumptions, an aditional litre of water per day will result in additional 19.2 meters of growth after one year. e) You should consider further influencing quantities.

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Question 38. You have performed a linear regression analysis to explore sunflowers' growth (in meters per month)
depending on the watering (in litres per day). You have estimated the regression coefficient to be ß = 1.6. What
can you conclude?
a) There is a signifleant correlation between watering and growth.
b) An average sunflower growths 1.6 meters per month.
c) If you give it an additional litre of water per day, there will be an additional average growth of 1.6 meters per
month.
d) According to the model assumptions, an additional litre of water per day will result in additional 19.2 meters
of growth after one year.
e) You should consider further influencing quantities.
Transcribed Image Text:Question 38. You have performed a linear regression analysis to explore sunflowers' growth (in meters per month) depending on the watering (in litres per day). You have estimated the regression coefficient to be ß = 1.6. What can you conclude? a) There is a signifleant correlation between watering and growth. b) An average sunflower growths 1.6 meters per month. c) If you give it an additional litre of water per day, there will be an additional average growth of 1.6 meters per month. d) According to the model assumptions, an additional litre of water per day will result in additional 19.2 meters of growth after one year. e) You should consider further influencing quantities.
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