1Operational definition
a universally accepted meaning that is clear to all associated with the analysis
2Categorical Nominal
Name of a Category (Gender (female/male), hair color (blonde, brunette, red , gray…)
3Categorical Ordinal
Has natural ordering (economic status, with three categories (low, medium and high)
and educational experience (with values such as elementary school graduate, high school graduate, some college and college graduate).
4Numerical or Quantitative Discrete
distinct cutoffs between values (Number of friends, number of children, number of courses)
5Numerical or Quantitative Continuous
Height, weight, time
6Population
all items/individuals about which you want to reach conclusions (described by PARAMETERS)
7Sample
items/individuals (from the population) which are selected for analysis (items/individuals about which you collect data) (described by STATISTICS)
8Outliers
Values that seem excessively different from most of the data values
9Missing Values
Values that were not collected (not available to the analysis)
10Mutually Exclusive
Each data value is place in one and only one category
11Collectively Exhaustive
ALL data values must be recoded in the categories created
12Sampling Frame
listing of items/individualsnits from the population used to select the sample
13Probability Sample
select items/individualsnits for the sample based on known probabilities (GOOD!)
14Non-probability sample
select items/individualsnits for the sample without knowing their probabilities of selection (BAD!) Creates BIAS. Cannot be used for statistical inference.
15Judgement
collect a sample that an “expert” thinks is representative of the population
16Convenience
collect the sample that is easiest to access.
17Census
(attempt to) collect data from every individual in the population
18Simple Random Sample (SRS)
sample is chose in such a way that every subject is equally likely to be selected for the study.
19Stratified
divide frame into groups (strata). Take a simple random sample from each strata.
20Systematic
Uses a systematic method k=N/n (i.e. n groups of k items such as, every 10th person) to select the sample
21Cluster
Divide N items in the frame into clusters and take a random sample of the clusters. Study all items in the cluster.