Statistics Terms Flashcards
statistics
study of methods for collecting, summarizing, analyzing, and interpreting data
population
complete collection of all individuals of elements under consideration in statistical study
census
collection of data regarding an entire population
sample
subject of selected elements from population
parameter
numerical summarization about a population
qualitative variable
takes on categories that cannot be averaged (blood type, color, race, name, eye color, zip code)
quantitative data
takes on numerical values to represent a measurement
Discrete data
entries are countable (number of eggs a chicken lays)
continuous data
entries can be continued on a scale
explanatory variable
values generally controllable by experimenter
response variable
causation
levels of some explanatory variables are certain to cause level of response variable to carry characteristics
correlation
suggests that levels of some explanatory variables tend to observe a level of response variable to carry characteristics
does correlation imply causation
NO
observational study
researchers observe characteristics and take measurements as it exists in the world. casual relationships not proven
designed experiment
researchers impose treatments and controls, then observes characteristics and takes measurements. it may be possible to establish casual relationships
lurking variable
explanatory variable that was not considered for the study, but affects value of response variable
census sampling
recording every observable entry in a population possible
representative sampling
sample constructed to most closely reflect population of the study
simple random sample
a random number generator is used to select “n” individuals from entire population of N individuals
cluster sample
separates the population into groups (strata) and use random generator to select groups and all individuals surveyed
stratified random sample
separate population into groups (strata) and use generator to randomly survey some individuals in each group
convenience sample
we survey the individuals that are readily accessible
voluntary response sample
individuals participating in survey go out of their way to respond
voluntary response bias
participants are commonly passionate and may not reflect population
systematic sample
survey every “nth” individual in convenience sample
self interest bias
questions posted by companies about their own product
social acceptability bias
” did you vote”
leading question bias
“are you interested in not paying high taxes…”
non response bias
we selected people but they didnt respond
sample size (n)
count for number of observation
relative frequency
how frequent a type occurs in reference to another
relative frequency formula
frequency/total observations (n)