State what is wrong in each of the following scenarios?
a. A sampling distribution describes the distribution of some characteristic in a population.
b. A statistic will have a large amount of bias whenever it has high variability.
c. The variability of a statistic based on a small sample from a population will be the same as the variability of a large sample from the same population.
Please help me with this problem, i have no idea how to solve it. Thanks.
Re: State what is wrong in each of the following scenarios?
Quote:
Originally Posted by
metelskiy 
a. A sampling distribution describes the distribution of some characteristic in a population.
b. A statistic will have a large amount of bias whenever it has high variability.
c. The variability of a statistic based on a small sample from a population will be the same as the variability of a large sample from the same population.
Please help me with this problem, i have no idea how to solve it. Thanks.
You are expected to explain what if anything is wrong with each of these statements. You should start by looking up the definition/s of the key concepts of each of these if you do not already know them.
a. So, what is a "sampling distribution"
b. What are a statistic, bias
CB
