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.
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Pls help me with below homework :
![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.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F59eb438f-2212-4d8e-97cc-caca6c2c4b9b%2F0f11acb5-8dbb-4e9f-ab7e-6fe912381880%2Fbap3py_processed.jpeg&w=3840&q=75)
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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