# SPAN 101 Chapter Notes - Chapter 3: Sampling Frame, Stratified Sampling, Simple Random Sample

by OC2168805

Department

SpanishCourse Code

SPAN 101Professor

Enrique ManchonChapter

3This

**preview**shows half of the first page. to view the full**3 pages of the document.**CH 3 SURVEYS AND SAMPLING

Sample survey: designed to ask questions of a small group of people in the hope of

learning something about the entire population

Idea 1: Examine a part of the whole

• a sample selected form the population

Idea 1: Randomize

• on average the sample looks like the rest of the population

• nobody can guess the outcome before it happens

• underlying set of outcomes will be equally likely

• variability from sample to sample is called sampling error

Idea 3: The sample size is what matters

• the size of the sample determines the data regardless of the size of the

population

• what fraction of the population you sample doesn’t matter

A Census:

• difficult to complete a census

• Hard to Locate or hard to measure

• Population we’re studying may change

• Census can be a cumbersome multiple addresses or none

Parameters: key numbers in models of reality

Statistic: any summary found form the data estimate

Population: all Canadian households

Parameter: mean household income of population

Sample: 1000 households contacted by researchers

Statistic/ Estimate: mean household income of the 1000 households

Simple Random Sample: combination of individuals has an equal chance of being

selected

Stratified Sampling: slice the population into homogeneous groups and then use

simple random sampling within each stratum, coming the results. Reduces sample

to sample variability. Are homogeneous but differ form one another

Cluster and Multistage Sampling: splitting the population into parts or clusters that

each represent the population can make sampling more practical. Heterogeneous

and resembling the overall population

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