# Project #36827 - self check 22

1. Useful prediction intervals for y can be obtained from a regression analysis.

 True False

2.  The mean response uy serves as the point estimate for estimating both the mean and the individual prediction of y given x.

 False True

3.

The residual sum of the squares is the numerator portion of the formula for the variance of y about the regression line.

 True False

4.

To conduct a valid regression analysis, both x and y must be approximately normally distributed.

 True False

5.

One concern about the depletion of the ozone layer is that the increase in UV light will decrease crop yields. An experiment was conducted in a green house where soybean plants were exposed to varying levels of UV levels - measured in Dobson units. At the end of the experiment the yield (kg) was measured. A regression analysis was performed with the following results.

Which of the following is correct?

 If the UV reading is increased by 1 Dobson unit, the yield is expected to increase by .0463 kg. The t-ratios are used to test if the estimated slope are different from zero. The estimated yield is 3.98 kg when the UV reading is 0 Dobson units. If the yield increases by 1 kg, the UV reading is expected to decline by .0463 Dobson units. The predicted yield is 4.3 kg when the UV reading is 20 Dobson units.

6.

One concern about the depletion of the ozone layer is that the increase in UV light will decrease crop yields. An experiment was conducted in a green house where soybean plants were exposed to varying levels of UV levels - measured in Dobson units. At the end of the experiment the yield (kg) was measured. A regression analysis was performed with the following results.

The least squares regression line is the line:

which minimizes the total variation in the data.
which minimizes the sum of the squared residuals between the actual yield and the predicted yield.
which minimizes the sum of the squared differences between the actual UV values and the predicted UV values.
which minimizes the sum the squared differences between the actual yield and the predicted UV.

7.  There are n - 3 degrees of freedom involved with the inferences about the regression line.

 True False

8.

If X and Y are uncorrelated in the population, the expected value of the estimated linear regression coefficient (slope) is 0.

 True False

9.

Rejecting the null hypothesis of no linear regression implies that changes in x cause changes in y.

 False True

10.

One concern about the depletion of the ozone layer is that the increase in UV light will decrease crop yields. An experiment was conducted in a green house where soybean plants were exposed to varying levels of UV levels - measured in Dobson units. At the end of the experiment the yield (kg) was measured. A regression analysis was performed with the following results:

Here is some output:

A 95% confidence interval for the slope will be centered on the estimated slope and:

 ± 0.046 ± 0.108 ± 0.054 ± 0.021 ± 0.011

11.

One concern about the depletion of the ozone layer is that the increase in UV light will decrease crop yields. An experiment was conducted in a green house where soybean plants were exposed to varying levels of UV levels - measured in Dobson units. At the end of the experiment the yield (kg) was measured. A regression analysis was performed with the following results:

Here is some output:

A 95% confidence interval for the mean yield when the UV reading is 20 Dobson units is:

 3.3 ± 0.40 3.3 ± 0.71 3.3 ± 0.98 3.3 ± 0.86 3.3 ± 2.12

12.

One concern about the depletion of the ozone layer is that the increase in UV light will decrease crop yields. An experiment was conducted in a green house where soybean plants were exposed to varying levels of UV levels - measured in Dobson units. At the end of the experiment the yield (kg) was measured. A regression analysis was performed with the following results:

Here is some output:

The null and alternate hypothesis for a test of the slope, the test statistic, and the p- value are:

 Ho: β=0 Ha: β0<0 T* = -74.01 p-value less than .0001. Ho: b1=0 Ha: b1 0 T* = -4.31 p-value = .0008 Ho: b1=0 Ha: b1<0 T* = -4.31 p-value = .0004 Ho: β1=0 Ha: β1 0 T*=-4.31 p-value = .0008 Ho: β1=0 Ha: β1<0 T* = -4.31 p-value = .0004

which minimizes the sum of the squared residuals between the actual UV reading and the predicted UV reading.

 Subject Mathematics Due By (Pacific Time) 07/31/2014 05:00 pm
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