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The yield of a grain, Y (/ha), appears to be linearly related to the amount of fertilizer applied, X (kg/ha). An experiment was conducted by applying different amounts of fertilizer (0 to 10 kg/ha) to plots of land and measuring the resulting yields. The following estimated regression line was obtained: yield = 4.85 + .05(fertilizer) Which of the following is not correct? O For every additional kg/ha of fertilizer applied, the yield is estimated to increase 0.05 t/ha.

The yield of a grain, Y (/ha), appears to be linearly related to the amount of fertilizer applied, X (kg/ha). An experiment was conducted by applying different amounts of fertilizer (0 to 10 kg/ha) to plots of land and measuring the resulting yields. The following estimated regression line was obtained: yield = 4.85 + .05(fertilizer) Which of the following is not correct? O For every additional kg/ha of fertilizer applied, the yield is estimated to increase 0.05 t/ha.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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1) The yield of a grain, Y (t/ha), appears to be linearly related to the amount of fertilizer applied, X (kg/ha). An experiment was conducted by applying different amounts of fertilizer (0 to 10 kg/ha) to plots of land and measuring the resulting yields. The following estimated regression line was obtained: yield = 4.85 + .05(fertilizer) Which of the following is not correct? For every additional kg/ha of fertilizer applied, the yield is estimated to increase 0.05 t/ha. If no fertilizer was used, the yield is estimated to be 4.85 uha (note that zero use of fertilizer is within the range of this data). O If the current level of fertilizer is changed from 7.0 to 9.0 kg/ha, the yield is estimated to increase by 0.20 t/ha. To obtain an estimated yield of 5.2 t/ha, you need to apply 7.0 kg/ha of fertilizer. If fertilizer is applied at 10 kg/ha, the estimated yield is 5.35 t/ha. 2) In a cross-sectional study of sales in different cities, the following relationship between sales revenue (S = sales revenue in dollars) and city size as measured by population (POP = population in thousands) was estimated: S = 37.02 + 0.6734(POP). What is the approximate 95 percent prediction interval for sales in a city of 155 thousand people when the regression standard error is 32.7214? (Note: you should use a rule of thumb here) O 75.955 to 206.839. 95.899 to 187.333. O 46.721 to 254.586. 108.676 to 174.118.
Transcribed Image Text:1) The yield of a grain, Y (t/ha), appears to be linearly related to the amount of fertilizer applied, X (kg/ha). An experiment was conducted by applying different amounts of fertilizer (0 to 10 kg/ha) to plots of land and measuring the resulting yields. The following estimated regression line was obtained: yield = 4.85 + .05(fertilizer) Which of the following is not correct? For every additional kg/ha of fertilizer applied, the yield is estimated to increase 0.05 t/ha. If no fertilizer was used, the yield is estimated to be 4.85 uha (note that zero use of fertilizer is within the range of this data). O If the current level of fertilizer is changed from 7.0 to 9.0 kg/ha, the yield is estimated to increase by 0.20 t/ha. To obtain an estimated yield of 5.2 t/ha, you need to apply 7.0 kg/ha of fertilizer. If fertilizer is applied at 10 kg/ha, the estimated yield is 5.35 t/ha. 2) In a cross-sectional study of sales in different cities, the following relationship between sales revenue (S = sales revenue in dollars) and city size as measured by population (POP = population in thousands) was estimated: S = 37.02 + 0.6734(POP). What is the approximate 95 percent prediction interval for sales in a city of 155 thousand people when the regression standard error is 32.7214? (Note: you should use a rule of thumb here) O 75.955 to 206.839. 95.899 to 187.333. O 46.721 to 254.586. 108.676 to 174.118.
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