9 terms

principles of experimental design

1. compare two or more treatments

-> this will control the effects of lurking variables on

the response

2. randomized

-> use impersonal chance to assign experimental

units to treatments

3. repeat each treatment on many units to reduce

chance variation in the results

-> this will control the effects of lurking variables on

the response

2. randomized

-> use impersonal chance to assign experimental

units to treatments

3. repeat each treatment on many units to reduce

chance variation in the results

stratified random sample

to select one, first divide the population into groups of similar individuals, called strata;

then choose a separate SRS in each stratum and combine these SRSs to form the full sample

then choose a separate SRS in each stratum and combine these SRSs to form the full sample

undercoverage

occurs when some groups in the population are left out of the process of choosing the sample

nonresponse

occurs when an individual chosen for the sample can't be contacted or does does

What is the difference between a statistic and a parameter?

a parameter is a number that describes the population while a statistic is a number that describes a sample

sampling distribution

distribution of values taken by the statistic in all possible samples of the same size from the same population

unbiased estimator

a statistic used to estimate a parameter;

-> if the mean of its sampling distribution is equal to the true value of the parameter being estimated

-> if the mean of its sampling distribution is equal to the true value of the parameter being estimated

variability of a statistic

described by the spread of its sampling distribution; this spread is determined by the sampling design and the sample size n;

statistics from larger probability samples have smaller spreads

statistics from larger probability samples have smaller spreads

margin of error

numerical measure of the spread of a sampling distribution;

it can be used to set bounds on the sized of the likely error in using the statistics as an estimator of a population parameter

it can be used to set bounds on the sized of the likely error in using the statistics as an estimator of a population parameter