Distributions
This rule states that for a Normal distribution, approximately 68%, 95%, and 99.7% of data fall within 1, 2, and 3 standard deviations of the mean.
The Empirical Rule
Measure of center that represents the average of the data points
Mean
Everyone has an equal chance of being selected
Simple Random Sample-SRS
Goodness of Fit
When groups of people cannot be reached in the survey
Nonresponse bias
A point is an outlier if its more than 1.5(IQR) above this value
The Third Quartile
Describes how much the statistic varies from sample to sample
Standard Error
Dividing the population into groups and then taking a SRS from every group
Stratified Random Sample
Compares the distribution of one categorical variable across at least two independent groups
Test for Homogenity
When the wording or behavior of the interviewer influences you to give a certain answer
Response bias
This value represents the number of standard deviations a data point is above or below the mean.
Z-Score
Describes a population statistic
Parameter
Dividing the population and surveying all of some groups and none of others
Cluster
Determines if there is a relationship between two categorical variables from one sample
Test for independence
Rejecting the null hypothesis but the null was actually true
What measure of center is not strongly affected by extreme outliers
Median
The percent of data that is less than or equal to a given value
Percentile
Selecting every nth
Systematic
To do a Chi-Squared Test this value has to be at least 5 for every cell in the table
Expected Counts
When you fail to reject the null hypothesis, but the null was actually false.
Type Two Error
If a distribution is strongly skewed to the right, which measure of center will be greater than the median
The mean
Measures strength and direction between two variables
Correlation Coefficient(r)
Bias
(r-1)(c-1)
Probability of committing a Type 1 Error
Alpha