Chapter 11

Question 1

Random sampling

Answer 1

A sequence of equally distributed variables.

Question 2

Simple Random sampling

Answer 2

random group in a population. avoids bias

Question 3

stratified random sampling

Answer 3

Break up the population into groups called strata, then take simple random samples from each. used for specific occurrence. ** cannot have crossover and must include all the population

Question 4

cluster sampling

Answer 4

random clusters from a population. different from stratified because the clusters are chosen randomly

Question 5

cluster random samples

Answer 5

different groups within a population are used as a sample.

cannot have crossover and must include all the population

Question 6

Two-way cluster sampling

Answer 6

Sampling method that involves separating the population into clusters then selecting random samples from the clusters.

** use when population size is unknown

Question 7

Systematic Random samples

Answer 7

requires selecting samples based on a system of intervals in a numbered population. Must still ensure all outcomes are given equal chance of getting selected.

** best if population is homogenous or of the same sub group.

Question 8

The Law of Large Numbers

Answer 8

Theorem states that the larger your sample size, the closer the sample mean will be to the mean of the population.

the more often that an experiment is repeated, the difference between the theoretical mean and the expected probability is closer to 0.

Question 9

Central limit theorem

Answer 9

if you run a random experiment enough times the results will follow a normal distribution.

Question 10

Standard error

Answer 10

divide the standard deviation of the sample set by the square root of the sample size