Chapter 9

Question 1

What is a population?

Answer 1

collection
of individuals (or items)
that is the main focus of
the research

Question 2

What is a census?

Answer 2

data is
collected from each
member of a population

Question 3

What is a parameter?

Answer 3

a characteristic or
a measure of a population

Question 4

What is a statistic?

Answer 4

a characteristic or
measure of a sample

Question 5

What is a sampling error?

Answer 5

the difference between
results obtained from a
sample and those that
would have been
obtained from the
population

Question 6

What is the procedure for drawing a sample?

Answer 6

1. define the target population.
2. identify the sampling frame
3. select a sampling procedure
4. determine the sample size
5. select the sampling elements
6. collect the data from the designated elements

Question 7

What is define the target population?

Answer 7

-A population (N) is all cases that meet designated
specifications for membership in the group
-Researchers must be very clear and precise in defining
the target population

Question 8

 Brenda is the quality control manager at a factory that
manufactures car tires.
 She suspects that the latest batch of tires includes items
of the wrong size and decides to investigate the issue.
What is the target population?

Answer 8

The tires.

Question 9

Imagine that Chipotle has received several complaints
about food quality from customers in Albuquerque. The
firm decides to send a team to Albuquerque to investigate
the problem.

What is the target population?

Answer 9

Albuquerque customers who recieved the poor food quality

Question 10

What is the sample drawn from?

Answer 10

The population.

Question 11

What does sample statistics allow?

Answer 11

Inferences about Population
Parameters

Question 12

What is step 2 identify the sampling frame?

Answer 12

A sampling frame is a list of the population elements from
which a sample (n) will be drawn

Question 13

What are commonly used sampling frames?

Answer 13

 Customer databases
 Telephone directories
 Lists developed by data compilers

Question 14

What is step 3 select a sampling procedure?

Answer 14

1. nonprobability sample
2. probability sample

Question 15

What is a non probability sample?

Answer 15

• A sample that relies on
  personal judgment in the
  element selection process
  -Sampling error cannot be
  estimated or calculated
  -Results should not be used to
  make inferences about the
  population

Question 16

What are the techniques for non probability sample?

Answer 16

• Convenience
  -Judgment
  o Snowball
• Quota

Question 17

What is a probability sample?

Answer 17

A sample in which each
target population element
has a known, nonzero
chance of being included in
the sample

Question 18

What are the techniques for a probability sample?

Answer 18

 Simple Random
 Systematic
 Stratified
 Cluster
o Area

Question 19

What is a convience sample?

Answer 19

• Population elements are sampled simply because they are in
  the right place at the right time
  -In almost all cases, the sample is NOT representative of the
  target population
  -Can be used for exploratory research
• Also called “Accidental” Sample

Question 20

What is an example of an accidental sample?

Answer 20

Television news “question of the day” polls

Question 21

What is a judgement sample?

Answer 21

• Population elements are handpicked by the researcher because
  they are expected to serve the research purpose
  -Appropriate in exploratory research when new ideas are
  sought

Question 22

What is an example of a judgement sample?

Answer 22

Using interviews to hire panelists who are knowledgeable
about the issue being researched rather than selecting them at
random

Question 23

What is a snowball sample?

Answer 23

• Also considered a judgment sample
  -Used for populations that are difficult to find and identify
• Initial sample chosen by a probability or nonprobability technique then
  the population elements are asked for referrals of others they know
  who might be interested in participation

Question 24

What is an example of a snowball sample?

Answer 24

A demand study for a new product where initial respondents
know people with a high interest level within the product category

Question 25

What is a quota sample?

Answer 25

certain important characteristics of the population are represented proportionately in the sample

Question 26

What is an example of a quota sample?

Answer 26

-Example – Research Problem: Investigate 100 undergraduate student attitudes toward a controversial new technology fee -Known Population Parameters: Class (30% Freshman, 20% Sophomores, 30% Juniors, 20% Seniors) and Gender (50% Female, 50% Male) -Approach: 10 students will interview 10 friends each for a total of 100 responses

Question 27

What should be the composition (by Class and Gender) of those 100 students? -30 freshman -20 sophmores -30 juniors -20 seniors

Answer 27

Class (30% Freshman, 20% Sophomores, 30% Juniors, 20% Seniors) Gender (50% Female, 50% Male)

Question 28

what are the techniques of a probabililty sample?

Answer 28

 Simple Random  Systematic  Stratified  Cluster o Area

Question 29

What is a simple random sample?

Answer 29

 Each member of the population has an equal chance of being selected  Walking down the street and passing out surveys to unknown people “at random” is “random” in the everyday sense, but not random in a scientific sample sense

Question 30

What is an example of a simple random sample?

Answer 30

Sample is drawn by a computer or from a physical list using a random number table

Question 31

What is a systematic sample?

Answer 31

- Sample in which every kth element (k = sampling interval) in the population is selected for the sample pool after a random start -This method is considered random because the first element is randomly selected, and every other element is a function of the first

Question 32

What is a systematic sample example?

Answer 32

 Research Problem: Investigate 250 undergraduate student attitudes toward controversial new technology fee  Known Population: 5000 students published in the campus directory  Approach: Compute sampling interval o Compute k = 5000/250 = 20 or 1 out of every 20 students on campus will be surveyed. o Randomly select the first name then count down 20 names. Select that person to be surveyed and then count down 20 names again. Select that person and so on until you get 250 names.

Question 33

What is the totaling sampling element?

Answer 33

Question 34

What are the elemnts in the total sampling element equation?

Answer 34

 BCI = estimated proportion of bad contact information (e.g., wrong email addresses, wrong telephone numbers…),  I = estimated proportion of ineligible elements in the sampling frame (i.e., people that don’t meet the criteria but were included in the sampling frame anyway),  R = estimated proportion of refusals,  NC = estimated proportion of elements that cannot be contacted after repeated attempts.

Question 35

Assume that a researcher needs to interview 250 students who are currently at UNM. She estimates that:  15% of students would have changed their telephone numbers  BCI = 0.15  2% have either graduated or dropped out of college  I = 0.02  20% will refuse to participate in the survey  R = 0.20  She won’t be able to reach 30% of the students she contacts  NC = .30

Answer 35

Question 36

What is a stratified sample?

Answer 36

Sample in which (1) the population is divided into mutually exclusive and exhaustive subsets and (2) a simple random sample of elements is chosen independently from each group/subset

Question 37

when is stratfied sample most appropriate?

Answer 37

Most appropriate when subsets (or strata) are homogeneous within but heterogeneous between with respect to key variables

Question 38

What is an example of a stratified sample?

Answer 38

Phoenix is one subset, Tucson is a second subset, and all other residents within the state of Arizona constitute a third subset

Question 39

What is a cluster sample?

Answer 39

 Like stratified sampling, (1) the population is divided into mutually exclusive and exhaustive subsets  Unlike stratified sampling, (2) a simple random sample of subsets (i.e., clusters) is chosen

Question 40

When is cluster sample most appropriate?

Answer 40

Most appropriate when subsets (or strata) are heterogeneous within but homogeneous between with respect to key variables

Question 41

What is area sampling technique?

Answer 41

A form of cluster sampling that uses geographic areas (i.e., blocks, neighborhoods, etc..) as sampling units

Question 42

are results generalizable from the sample to the population in a nonprobability sample?

Answer 42

No.

Question 43

Are results generalizable from the sample to the population in a probabilty sample?

Answer 43

yes.

Question 44

What is determine the sample size?

Answer 44

Three basic factors affect the size of sample needed when working with a probability sample 1. amount of diversity or variation 2. degree of precision 3. degree of confidence

Question 45

What effect does the size of the population have on the sample?

Answer 45

Size of the population has no bearing on the size of the sample

Question 46

The more similar the population elements the _____ people neeeded regardless of how large the population is.

Answer 46

The more similar the population elements, the fewer people needed regardless of how large the population is

Question 47

What are the other considerations in determining the sample size?

Answer 47

1. costs/ available research budget (Larger sample sizes can cost more to recruit) 2. type of analysis to be conducted (Minimum requirements of statistical techniques must be met) 3. past research (Historical evidence of sample sizes in similar studies can be a good guide)