Sampling and Bias

Question 1

Simple Random

Answer 1

randomly choose a specific number of people. e.g. Put all the names in a population into a hat and
draw one or several names. Each person has an
equal chance of being chosen.

Question 2

Systematic

Answer 2

put the population in an ordered list and choose people at
regular intervals. e.g. Order all the patients of a doctor in some way
(e.g., alphabetically) and choose one randomly.
Select the rest of the data at regular intervals
from the original starting point (e.g., every tenth
name after the original).

Question 3

Stratified

Answer 3

divide the sample into groups with the same proportions as
those groups in the population -
* time- and cost-efficient to conduct e.g. Survey factory employees about new safety
initiatives. There are 1000 employees in the
factory, of which 633 are women and 367 are
men. Randomly select 63 women and 37 men to
take the survey.

Question 4

Cluster

Answer 4

divide the population into groups, randomly choose a number
of the groups, and sample each member of the chosen groups

e.g. Survey Little League Canada baseball players.
Randomly select five districts in each province
and give the survey to every player in those
districts.

Question 5

Multistage

Answer 5

divide the population into a hierarchy and choose a random
sample at each level

e.g. Conduct an employee wellness survey by
randomly selecting 10 stores. Randomly
select three departments in each store, and
randomly select 10 employees in each of those
departments.

Question 6

Convenience

Answer 6

choose individuals from the population who are easy to access
* can yield unreliable results since it inadvertently omits large
pqrtions of the population
* often very inexpensive to conduct

e.g. To get the public’s input on a new pet by-law,
a local politician goes to a local park and asks
people their opinion.

Question 7

Voluntary

Answer 7

allow participants to choose whether or not to participate
* often the only people who respond are either heavily in favour
or heavily against what the survey is about

e.g. Conduct an online poll asking people whether
banning junk food in schools will fight obesity.

Question 8

Sampling Bias

Answer 8

Occurs if the sample doesn’t represent the population.

Question 9

Non-Response Bias

Answer 9

Results when the sampling technique likely leads to non-responses

Question 10

Measurement Bias

Answer 10

Arises from problems with the way data is measured, not the sample.
Often caused by leading or loaded questions in surveys

Question 11

Response Bias

Answer 11

Results from respondents providing answers they believe are expected or socially acceptable rather than their true feelings or behaviors

Question 12

Misinterpretation of Data

Answer 12

Occurs even if data is collected in a bias-free manner but is misinterpreted during analysis.

Question 13

Misrepresentation of Data

Answer 13

Happens when data, although collected bias-free, is misrepresented in reports or presentations

Question 14

Binomial

Answer 14

• Trials are independent
• Multiple trials
• Success/failure for each trial
• x = # of successes

Question 15

Hypergeometric

Answer 15

• Trials are dependent
• Multiple trials
• Success/failure for each trial
• x = # of successes