Question

1. The reported error on a survey is usually the standard error of proportions. Which of the following statements is true?

a. The standard error of proportion is, by definition, the same as the total error.

b. Total error is estimated to be between 1.5 and 2 times higher than reported error.

c. Total error is, by definition, 1.96 times the standard error of proportion.

d. The standard error of proportions only measures non-sampling error.

2.

How can we compute the true variance of a test?

a. Give the test many times and take the variance of all the result

b. Use an algebraic manipulation of Cronbach's alpha formula

c. The variance obtained by giving the test to any sub-population that is large is the true variance

d. You cannot compute the true variance of a test

Answer 1

Below is an absolutely accurate answer.

1) Option A is an absolutely accurate answer.

Explanation:-

The standard blunder of the proportion is characterized as a result of the unfold of the sample proportion concerning the population proportion. All the extra expressly, the quality error is that the gauge of the standard deviation of a activity the quality error of proportion is

2) Option C

Explanation:-

To calculate variance, begin by calculation the mean, or normal of your example. At that point, figure the mean from every information information point, and sq. the distinctions. It embody all of the sq. contrasts.

Thanks