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Marketing Research > Chapter 9 > Flashcards

Chapter 9 Flashcards

1
Q

What is a population?

A

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

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2
Q

What is a census?

A

data is
collected from each
member of a population

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3
Q

What is a parameter?

A

a characteristic or
a measure of a population

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4
Q

What is a statistic?

A

a characteristic or
measure of a sample

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5
Q

What is a sampling error?

A

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

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6
Q

What is the procedure for drawing a sample?

A
  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
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7
Q

What is define the target population?

A

-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

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8
Q

 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?

A

The tires.

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9
Q

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?

A

Albuquerque customers who recieved the poor food quality

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10
Q

What is the sample drawn from?

A

The population.

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11
Q

What does sample statistics allow?

A

Inferences about Population
Parameters

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12
Q

What is step 2 identify the sampling frame?

A

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

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13
Q

What are commonly used sampling frames?

A

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

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14
Q

What is step 3 select a sampling procedure?

A
  1. nonprobability sample
  2. probability sample
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15
Q

What is a non probability sample?

A
  • 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
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16
Q

What are the techniques for non probability sample?

A
  • Convenience
    -Judgment
    o Snowball
  • Quota
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17
Q

What is a probability sample?

A

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

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18
Q

What are the techniques for a probability sample?

A

 Simple Random
 Systematic
 Stratified
 Cluster
o Area

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19
Q

What is a convience sample?

A
  • 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
20
Q

What is an example of an accidental sample?

A

Television news “question of the day” polls

21
Q

What is a judgement sample?

A
  • 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
22
Q

What is an example of a judgement sample?

A

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

23
Q

What is a snowball sample?

A
  • 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
24
Q

What is an example of a snowball sample?

A

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

25
Q

What is a quota sample?

A

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

26
Q

What is an example of a quota sample?

A

-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

27
Q

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

A

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

28
Q

what are the techniques of a probabililty sample?

A

 Simple Random
 Systematic
 Stratified
 Cluster
o Area

29
Q

What is a simple random sample?

A

 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

30
Q

What is an example of a simple random sample?

A

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

31
Q

What is a systematic sample?

A
  • 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
32
Q

What is a systematic sample example?

A

 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.

33
Q

What is the totaling sampling element?

A
34
Q

What are the elemnts in the total sampling element equation?

A

 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.

35
Q

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

A
36
Q

What is a stratified sample?

A

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

37
Q

when is stratfied sample most appropriate?

A

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

38
Q

What is an example of a stratified sample?

A

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

39
Q

What is a cluster sample?

A

 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

40
Q

When is cluster sample most appropriate?

A

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

41
Q

What is area sampling technique?

A

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

42
Q

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

A

No.

43
Q

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

A

yes.

44
Q

What is determine the sample size?

A

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

45
Q

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

A

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

46
Q

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

A

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

47
Q

What are the other considerations in determining the sample size?

A
  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)

Marketing Research (10 decks)

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