Foundations Flashcards
Nominal/Categorical data
A type of quantitative data such as hair color or favorite sport. For data entry, each category is assigned a number.
Ordinal data
Show order but not magnitude between orders. Ex: place order of race completers. Data entry: each participant receives the number of their place in the order.
Interval data
True score data: know the score of the individual and the magnitude of difference between scores. No true zero. Ex: temperature, psychological measure (IQ) Data entry: enter actual score of each participant
Ratio data
True score data with true zero. Can calculate score ratios. Ex: height, weight, raw test score. Data entry: enter actual score
Can interval and ratio data be transformed into nominal or ordinal? Why would you want or not want to do this?
Yes:
- you could establish categories for nominal ie 65in and taller/64in and shorter
- make up ranks based on score for ordinal ie rank participants by height
- you likely would not want to do this, since interval and ratio data are more precise than nominal or ordinal.
How do we do random sampling?
- Every member has an equal chance of being chosen
- List of all members in population
- Gold standard but not always feasible
Stratified Random Sample
Use when you don’t want to take chances on the random sampling getting you the cross-section of characteristics you want/need.
-Select participants from population based on performance on one known characteristic ie college classification: sample spread of freshman, sophomores, juniors, seniors to match true population
Systematic Random Sample
Every nth person is selected for sample.
Use when population is too large to collect a true random sample.
Convenience Sample
Select participants who are available and close in proximity. Not ideal, but convenient.
snowball sampling: drug user who gets other drug users to participate
Discrete numbers
Whole numbers
Continuous numbers
Decimal numbers
