sample, population , bias, proportional, cluster, extrapolate, cluster sampling, self selective
sampling, systematic
sampling, simple
random sampling, stratified random sampling, convenience sampling
Interactive Component Under Construction

Learning Outcomes:
The student will:
Biases Affecting Information Processing
Sampling
population  eligible people for a data collection
investigation
sample  part of a population selected so as to give
information about the population as a whole
biased sample  sample is not representative of the
population from which it is taken because the method used to collect the data contains
unwanted influence(s).
unbiased sample  sample is representative of the
population from which it is taken
Biased Samples 
Unbiased Samples 
convenience sampling  an easily
accessible group of people is chosen, and everyone in that group is surveyed. For
example, the Pizzatime owners might survey all of the people who go to a nearby grocery
store from 5PM to 6PM on September 6th.
Advantages
Disadvantages
 there is no guarantee that
the behaviors of these people represent behaviors of other groups.

systematic sampling  every nth member
of the population is sampled. The list being sampled may be ordered (alphabetical,
seniority, street number, etc). Question : Is it equivalent to simple random sampling?
Strictly speaking the answer is No!, unless the list itself is in random order, which it
never is (alphabetical, seniority, street number, etc).
Advantages
 easier to draw, without mistakes (cards in file)
 more precise than simple random sampling as more evenly spread over population
Disadvantages
 if list has periodic arrangement then sample collected may not be an accurate
representation of the entire population

selfselective sampling  a population
provides information by volunteering their opinions. Advantages
Disadvantages
 there is no guarantee that
the behaviors of these people represent behaviors of other groups.

simple random sampling  the sample is chosen randomly
from the population. Here each sample of size n from the population
of size N has an equal chance of selection. In practice "each unit in the
population is numbered 1 to N and n units are randomly drawn from the N''.
Advantages
 simple to apply
 analysis of data is reasonably easy and has a sound mathematical basis
Disadvantages
 if population heterogeneous estimates have large variance

cluster sampling  a particular segment of
the population is sampled using existing lists (Constituencies, Wards, Households, ...). Advantages
 reduced field costs
 applicable where no complete list of units is available (special lists only need be
formed for clusters).
Disadvantages
 clusters may not be representative of whole population but may be too alike
 analysis more complicated than for simple random sampling.

stratified random sampling  the population is divided
into groups (strata) and the data is collected from the strata by simple random sampling.
Advantages
 If data of known precision is wanted for certain subdivisions of the population, then
each subdivision or strata can be
treated as a population.
 Administrative convenience may dictate its use, so that each field office can supervise
one strata.
 Sampling problems may differ markedly within a population (e.g. people in prisons and
people outside).
 Stratification will almost certainly produce a gain in precision in the estimates of the
whole population, because a heterogeneous population is split into fairly homogeneous
strata.
Disadvantages
 problems if strata not clearly defined.
 analysis is (or can be) quite complicated.

