No, the estimates should become more robust and the power of the test should, therefore, increase.
true
The statement is false. For a fixed alpha, an increase in the sample size will cause a decrease in beta (but an increase in the power).
The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.
The standard error increases.
it should decrease
Yes.
true
With probability sampling you have no control over the units that are sampled. So the only way to reduce the margin of error is to increase the size of the sample.
The statement is false. For a fixed alpha, an increase in the sample size will cause a decrease in beta (but an increase in the power).
The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.
The larger the sample, the lower the % error.. so to reduce a % error, increase your sample size.
The standard error increases.
Increase sample size.
Random error and sample size have an inverse relationship...As sample size INCREASES random error DECREASES. There's a good explanation at the related link.
it should decrease
Increase n or sample size.
It increases the accuracy of the estimation and reduces the associated error range.