This document discusses bias in sampling and surveys. It defines random sampling as giving every population element an equal chance of being selected, making it an unbiased sample. Bias can occur if the sample is not representative, the survey is ambiguous or subjective, or factors influence responses. Types of bias include sampling bias, non-response bias, response bias, household bias, and measurement bias. Examples are given to illustrate each type of bias.

1. BIAS

2. Random Sampling means every
element of the population has an
equal probability of being chosen.
When a sample is selected at
random from a population, it is
said to be an unbiased sample.
However, if the sample is
selected incorrectly it may result
in a biased sample.

3. BIAS
 If the sample is not representative of the population, then
the results may be inaccurate.
 If a survey is ambiguous, subjective, or biased, then the
results may be inaccurate.
 Bias is any factor that favours certain outcomes or
responses, or influences an individual’s responses.
 Bias may be unintentional (accidental), or intentional (to
achieve certain results).

4. FORMS OF BIAS
Sampling Bias
The sample does not
accurately represent the
population.
Example:
Attendees at a Star Trek
convention may report that
their favourite genre is a
science fiction.
While this may be
representative of the
population at the convention, it
might not reflect the general
population’s opinion.

5. FORMS OF BIAS
Non-Response Bias
Certain groups are under-
represented because they
elect not to participate.
Example:
A restaurant may give each table a
“customer satisfaction: survey with
their bill.
Generally, there are two types of
people that respond to these
surveys: those that really enjoy the
service, or those that hate it. Those
whose opinions are somewhere in
between are not well represented.

6. FORMS OF BIAS
Response Bias
Factors in the sampling
method influence the data
obtained.
Example:
A respondent may answer
questions in the way she
thinks the questioner wants
her to answer or a man may
respond differently to a woman
when asked questions about
domestic violence.

7. FORMS OF BIAS
Household Bias
When one type of
respondent it
overrepresented because
groupings (strata) of
different sizes are polled
equally.
Example:
A survey to determine the
average speed on a highway
would be biased if taken only
during rush hour, other strata
need to be included (i.e. late
evenings)

8. FORMS OF BIAS
Measurement Bias
An inappropriate data-
collection method results
in a consistent over- or
underestimation of some
characteristic of the
population.
Example:
A principal might want to get
an estimate of the number of
students who use cell phones
in the hallways, by using
teachers to tally.
Since many students hide their
phones when they see a
teacher, this may not be an
accurate data-collection
method.

9. Identify the type of bias in each scenario:
a) You hand out surveys to your classmates to be returned to you
next week.
b) On its website, a band asks its fans to list their favourite artists.
c) A mall employee asks random walkers-by to participate in a brief
survey about shopping habits.
d) You take a random sample of students during the second lunch
hour to determine their attitudes toward the new school
attendance policy.

10. Identify the type of bias in each scenario:
a) You hand out surveys to your classmates to be returned to you
next week – non-response bias
b) On its website, a band asks its fans to list their favourite artists –
sampling bias
c) A mall employee asks random walkers-by to participate in a brief
survey about shopping habits – non-response bias
d) You take a random sample of students during the second lunch
hour to determine their attitudes toward the new school
attendance policy – sampling bias