According to the central limit theorem used in inferential statistics,
A)the bigger your sample,the better your results.
B)when drawing many random samples,the samples form a normal curve with the highest point of the distribution equal to the population parameter.
C)the best estimate of population parameters comes when one uses the inverse square of the z-probability distribution.
D)90 percent of all samples drawn in a simple random manner will contain some error.
E)in order to infer from a sample to a population,the sampling error must equal zero.

Question

Quizplus · Accepted Answer

The central limit theorem states that when drawing many random samples, the samples will form a normal curve with the mean of the distribution equal to the population parameter. This means that option B is the correct choice. Option A is a common misconception, as a larger sample size does not always guarantee better results. Option C is incorrect, as the inverse square of the z-probability distribution is not used to estimate population parameters. Option D is also incorrect, as not all samples drawn in a simple random manner will contain error. Option E is incorrect, as sampling error can never be completely eliminated, but it can be reduced through proper sampling techniques.

According to the Central Limit Theorem Used in Inferential Statistics