Parameter vs Statistic & Sample vs Population

Question Answer
population is the entire group of objects you want to study.
ex: scores, people, measurements
sample is a smaller subset chosen from the population and a representative of the population.
parameter is a number which describes a property of only a sample.
random sample every object in the population is equally likely to be picked for the sample.
ex: pick name out of hats.
systematic sample every Kth object is chosen for the sample.
ex: think assembly line pick every 10th computer off the line.
convenience/volunteer/self-selected are non scientific approaches that will not lead to a representative sample.
ex: online surveys, phone polling, restaurant surveys
cluster sample is the method that picks groups randomly from the population instead of pick one object.
Every object in randomly selected groups forms our sample.
stratified sample is the method when we divide the entire population into meaningful groups.
Ex: republican and democrats, male or female
randomly sample to fill each group
1st: randomly pick groups from population.
2nd: sample is every object from the groups
cluster sample
1st: subdivide population with named groups.
2nd: randomly select objects from each group.
stratified sample
quantitative data is numeric data in which you can count.
ex: ages, weight
refers to data type not a level of measurement
categorical (qualitative) data is NOT numeric but instead you break them into categories by labels.
ex: eye color, letter grades
NOT how many people.
ratio level means 0=None
Can not have negative numbers
ex: age, length, weight, measurement of amounts
interval level 0 not equal to NONE. can be negative.
ex: temperature
ordinal level categories have a built in order. reordering would be confusing.
ex: letter grades a,b,c,d
smallest to largest
nominal level categories can be put in any order and not be confusing. can not be arranged in an ordering scheme.
ex: eye color, names, labels, categories.
discrete data data you can count. "number of"
continuous data data you can measure
ex: height, length, age