stat chapter 10 vocab

Front

Randomize

Back

help reduce bias

help reduce influence of effects out of our control

make chance outcomes seems fair

Front

random values

Back

generate through technology

found using a digit table

place on paper and pulled out of a basket

Front

simulation

Back

a way to model random events so the outcome can come close to matching real world outcomes.

Front

sampling

Back

take a sample from a population, then use the sample to estimate what we would get if we could reach the entire population

Front

sampling variability

Back

the difference results we can get

Front

bias

Back

favor one thing over another, leading to false data

Front

undercoverage

Back

sample that are not a representative sample

Front

random selection

Back

select a random sample from a whole sampling frame to prevent bias

Front

census

Back

measure or observe every member of a population

maybe too expensive

may not be practical

population is always changing

undercount is a problem

Front

Simple random survey (SRS)

Back

requires a sampling frame

every sample of a given size has the same chance of selection

"draw from a hat"