Chapter 7 Flashcards
Simple Random Sample
every member of the population has an equal chance of being selected
1/N
Stratified Random Sample
divide the population into mutually exclusive groups and randomly sample from each group
-bigger group, bigger sample from that group
Systematic Sampling
selecting every kth member of the population
K= N/n Take every 10th student
Cluster Sampling
randomly selecting clusters as samples
- states
- mini snapshots
Sampling Error
difference between the statistic and parameter
x ̅ - μ
-control by increasing sampling size
Coverage Error
error in sampling frame
Non-Response Error
failure to obtain responses from samples
Measurement Error
error in responses of the samples
Sampling Distribution: If the sample drawn is normal
the sample mean will also follow a normal distribution. x ̅~normal (μ=μ_x ̅ ,σ_x ̅ =σ/√n)
Sampling Distribution: If the sample drawn has an unknown distribution
use the central limit theorem
Central Limit Theorem
the sample mean will be approximately normal for n ≥ 30
x ̅~approximately normal(μ=μx ̅ ,σx ̅ =σ/√n)
P(x ̅<(a-μx ̅ )/σx ̅ )