Chp. 7 Probability and Samples: The Distribution of Sample Means

Question 1

Sampling Error

Answer 1

Sampling Error is the natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.

Question 2

Distribution of Sample Means

Answer 2

The distribution of sample means is the collection of sample means for all the possible random samples of a particular size (n) that can be obtained from a population.

Question 3

Sampling Distribution

Answer 3

A sampling distribution is a distribution of statistics obtained by selecting all the possible samples of a specific size from a population.

Question 4

Central Limit Theorem

Answer 4

For any population with mean μ and standard deviation σ, the distribution of sample means for sample size n will have a mean of μ and a standard deviation of σ/√͞n and will approach a normal distribution as n approaches infinity.

Question 5

Expected Value of M

Answer 5

The mean of the distribution of sample means is equal to the mean of the population of scores, μ, and is called the expected value of M

Question 6

Standard Error of M

Answer 6

The standard deviation of the distribution of sample means. The standard error provides a measure of how much distance is expected on average between a sample mean (M) and the population (μ).

Question 7

Law of Large Numbers

Answer 7

States that the larger the sample size (n), the more probable it is that the sample mean will be close to the population mean