20 terms

Chi Square Assumptions

1. random sample

2. no expected frequencies less than 5 in any given cell

2. no expected frequencies less than 5 in any given cell

Meaning of a t-statistic

the number of standard errors from the mean

Meaning of a Z statistic

the number of standard errors from the mean

Why does sampling matter?

sampling matters to make results general in order to apply to the larger group

Non-Probability Sample

(bad) convenience sample, snowball sample, quota sample, judgment sample

Probability Samples

(good) simple random sample, systematic random sample, cluster sample, stratified random sample

Phrase for Standard Error

average distance of the sample statistic from the population parameter

Z Score for 90% Confidence Level

1.65

Z Score for 95% Confidence Level

1.96

Z Score for 99% Confidence Level

2.58

How to Calculate Confidence Interval

1. calculate standard error

2. calculate confidence interval

2. calculate confidence interval

Phrase for Standard Deviation

the average distance from the mean

Central Limit Theorem

when N>30 or 50 the population curve will always be normal

Confidence Interval

a range of values defined by the confidence level within which the population parameter is estimated to fall

Point Estimate

a sample statistic used to estimate a population parameter

Type 1 Error

our first concern in a court of law, we do not want to convict an innocent person

Type 2 Error

secondary concern, letting guilty person go free, or saying there is no difference when there really is

Degrees of Freedom

the number of scores that are free to vary in calculating each statistic

Sampling Error

the difference between the sample estimate and the population parameter

Sample Bias

the thing you sample from does not represent the entire population