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Marketing Research > Test #2 > Flashcards

Test #2 Flashcards

1
Q

Selection of descriptive research design is based on 3 factors:

A
  1. Nature of Problem
  2. Research questions
  3. Research objectives
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2
Q

When to use descriptive research design

A
  • When researcher problem is either to describe characteristics of existing market solutions or to evaluate current mktg mix strategies
  • If research question include issues s.a. who, what, where, when, and how for target population or mktg strategies
  • If task is to identify relationships b.t variables or determine whether differences exist bt groups
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3
Q

Goals of descriptive research survey methods

A

Provide facts that can be used to:

  • Make accurate predictions a/b relationships b/t market factors and behaviors
  • Gain insights to understand the relationships & differences
  • Verify or validate existing relationships
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4
Q

2 general approaches used to collect data for descriptive research:

A
  1. Asking questions

2. Observations

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5
Q

Descriptive research designs often result in the use of _____ to collect ____ data from larger groups through question/answer process

A

survey research methods

quantitative

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6
Q

With the emergence of_____, observation is being used more often than question/answer in descriptive designs

A

Scanner data and tracking of Internet behavior

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7
Q

Main goal of quantitative research methods =

A

to provide facts and estimates from a large, representative sample of respondents

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8
Q

5 advantages of quantitative survey research designs

A
  1. Generalizable to target population
  2. Facilitates advanced statistical analysis
  3. Accommodates to large number of people
  4. Concepts and relationships not directly measurable can be studied
  5. Easy to administered and record answers
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9
Q

3 Disadvantages of quantitative survey research designs

A
  1. Questions that accurately measure respondent attitudes and behavior can be challenging to develop
  2. In-depth data difficult to obtain
  3. Low response rates can be a problem
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10
Q

Difference between the findings based on the sample and the true values for a population

A

Sampling errors

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11
Q

Sampling errors are caused by:

A

Method of sampling used

Size of sample (to reduce error, increase size)

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12
Q

Errors that can occur in survey research design not related to sampling

A

Nonsampling errors

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13
Q

4 major sources of nonsampling errors

A
  1. Project administration errors
  2. Respondent errors
  3. Incorrect problem definition
  4. Measurement/questionnaire design errors
    (PRIM)
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14
Q

4 characteristics of nonsampling errors

A
  1. Tend to create “systematic variation” or bias in the data
  2. Unlike random sampling error which can be statistically measured, nonsampling errors cannot be directly measured
  3. Nonsampling errors are controllable (human mishaps in ether design or survey execution)
  4. One sampling error leads to nonsampling errors
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15
Q

Consist of both nonresponse error and response error

A

Respondent errors

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16
Q

Systematic bias that occurs when the final sample differs from planned sample

A

Nonresponse errors

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17
Q

When respondents have impaired memory or do not respond accurately

A

Response errors

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18
Q

4 advantages of person-administered surveys

A
  1. Feedback
  2. Adaptability
  3. Rapport
  4. Response quality
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19
Q

3 disadvantages of person-administered surveys

A
  1. High expense
  2. Interaction errors
  3. Possible recording errors
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20
Q

6 advantages of telephone-administered surveys

A
  1. Callbacks possible
  2. Fast
  3. Interviewers or CATI tech
  4. Suitable for large samples
  5. Geographic Flexibility
  6. Less expensive than face to face methods
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21
Q

4 disadvantages of elephone-administered surveys

A
  1. Change in behavior (vm, caller id, mobile)
  2. Difficult for complex tasks, long surveys, or those using visual aids
  3. Limited to domestic research
  4. Perception of telemarketing
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22
Q

4 types of self-administered surveys

A
  1. Mail survey
  2. mail panel
  3. drop off
  4. internet
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23
Q

4 Advantages of self administered surveys

A
  1. No interviewer response bias
  2. Anonimity in response
  3. Respondent control
  4. Low cost
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24
Q

5 disAdvantages of self administered surveys

A
  1. lack of monitoring
  2. minimal flexibility
  3. potential response errors
  4. high nonresponse rates
  5. slow data acquisitions
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25
Q

3 characteristics in selecting a survey method

A
  1. Situational characteristics
  2. task characteristics
  3. respondent characteristics
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26
Q

6 situational characteristics when selecting a survey method

A
  1. Budget
  2. completion time frame
  3. quality requirements
  4. data completeness
  5. data generalizability
  6. data precision
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27
Q

What is data generalizability

A

projectable to the population represented by sample in a study

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28
Q

degree of exactness of the data in relation to some other possible response

A

data precision

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29
Q

4 task characteristics when selecting a survey method

A
  1. Topic sensitivity
  2. amount of info
  3. difficulty of task
  4. stimuli needed
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30
Q

degree to which a survey ? leads respondent to give a socially acceptable response

A

topic sensitivity

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31
Q

3 response characteristics when selecting a survey method

A
  1. respondent participation
  2. incidence rate
  3. diversity
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32
Q

% of the general population that is the subject of the market search

A

incidence rate

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33
Q

3 things that determine respondent participation

A
  1. Knowledge level
  2. ability to participate
  3. willingness to participate
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34
Q

casual research designs that can identify cause & effect relationships between variables

A

experiments

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35
Q

an observable element or attribute of an item or event that can be measured

A

variable

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36
Q

types of variables in experimental designs

A
  1. independent (values manipulated by researcher)
  2. dependent (measures of effect)
  3. control (conditions that make the design a true experiment)
  4. extraneous (uncontrolled, unmeasurable variable that may affect dependent)
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37
Q

extent to which the research design accurately identifies causal relationships

A

internal validity

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38
Q

extent to which a causal relationship found in a study can be expected to be true for the entire target population

A

external validity

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39
Q

process of selecting a small # of elements from a larger defined target group of elements such that the info gathered from small group will allow judgments to be made about the larger groups

A

sampling

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40
Q

To be more confident during a sampling,

A

you have to increase the margin of error

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41
Q

Identifiable set of elements of interest to the researcher and pertinent to the info problem

A

population

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42
Q

complete set of elements identified for investigation

A

defined target population

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43
Q

target population elements available for the selection during the sampling process

A

sampling unit

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44
Q

list of all eligible sampling units

A

sampling frame

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45
Q

any type of bias that is attributable to mistakes in either drawing a sample or determining the sample size

A

sampling error

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46
Q

random sampling error tends to occur because of

A

chance variations in the selection of sampling units

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47
Q

Sampling errors can be reduced by

A

increasing the size of the sample

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48
Q

bias that occurs in a research study regardless of whether a sample or census is used, such as bias caused by measurement error, response errors, or coding errors

A

nonsampling errors

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49
Q

The more ___ a study, the greater the potential for nonsampling errors

A

extensive

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50
Q

nonsampling error usually related to the ______ whereas sampling errors relate to ___

A

nonsampling error—accuracy of the data

sampling errors—representativeness of the sample to the defined target population

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51
Q

with this ampling method, each sampling unit in the defined target population has a known probability of being selected for the sample

A

probability sampling

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52
Q

Sampling method in which the probability of selection of each sampling unit is not known

A

nonprobability sampling

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53
Q

selection of sampling units is based on:

A

-judgment of the researcher

may or may not be representative

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54
Q

procedure in which every sampling unit has a known and = chance of being selected

A

simple random sampling

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55
Q

4 advantages of simple random sampling

A
  1. produce unbiased estimates of the population’s characteristics
  2. easily understood
  3. results can be generalized to the defined target population with a prespecified margin of error
  4. valid representation of defined target population
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56
Q

2 disadvantages of simple random sampling

A
  1. difficulty of obtaining a complete and accurate listing of the target population elements
  2. requires that all sampling units be identified
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57
Q

when does simple random sampling work best?

A

for small populations where accurate lists are available

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58
Q

procedure in which the defined target population is ordered in some way, usually in the form of a customer list, taxpayer roll or membership roster, and selected systematically

A

systematic random sampling

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59
Q

advantage of systematic random s.

A

relatively easy way to draw a sample while ensuring randomness

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60
Q

2 disadvantages of systematic random sampling

A

of sampling units in the target population must be known

possibility of hidden patterns in the list of names that create bias

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61
Q

steps in drawing a systematic random sampling

A
  1. obtain a list of units that contains an acceptable frame of the target population
  2. determine the # of units in the list and the desired sample size
  3. compute the skip interval
  4. determine a random starting point
  5. beginning at that start point, select the units by choosing each unit that corresponds to the skip interval
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62
Q

separation of the target population into different groups (strata) and the selection of samples from each stratum

A

stratified random sampling

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63
Q

3 steps in drawing a stratified random sample

A
  1. divide the target population into homogeneous subgroups or strata
  2. draw random samples from each stratum
  3. combine the samples from each stratum into a single sample of the target population
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64
Q

2 methods of stratified random sampling

A
  1. proportionately stratified sample

2. disproportionately…

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65
Q

in this s. method, each stratum is dependent on its size relative to the population

A

proportionately stratified sample

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66
Q

in this s. method, each stratum is independent on its size relative to the population

A

disproportionately stratified sample

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67
Q

3 advantages of stratified rs

A
  1. assurance of representativeness in the sample
  2. opportunity to study each stratum and make comparison b/t strata
  3. ability to make estimates for the target population with the expectation of greater precision and less error
68
Q

2 disadvantages of stratified rs

A
  1. determining the basis for stratifying
  2. info relevant to the required stratification factors might not be readily available therefore forcing the researcher to use less desirable criteria as the factors for stratifying the target population
69
Q

method in which sampling units are divided into mutually exclusive and collectively exhaustive subpopulations

A

cluster sampling

70
Q

form of cluster sampling in which the clusters are formed by geo designations

A

area sampling

71
Q

2 advantages of cluster sampling

A

cost effective

easy to implement

72
Q

2 dis. of cluster sampling

A
  1. clusters are often homogeneous

2. appropriateness of the designated cluster factor used to identify the sampling units within clusters

73
Q

4 types of probability sampling

A
  1. simple random s.
  2. systematic rs
  3. stratified rs
  4. cluster sampling
74
Q

Sampling method in which samples are drawn at the convenience of researcher

A

convenience sampling

75
Q

advantage of convenience sampling

A

enables a large 3 of respondents to be interviewed in a relatively short time

76
Q

3 disad of convenience sampling

A
  1. constructs mights be unreliable if used to study a broader target population
  2. data are not generalizable to the defined target population
  3. representativeness of the sample cannot be measured bc sampling error estimates cannot be calc
77
Q

sampling method in which participants are selected according to an experienced individual’s belief that they will meet the requirements of the study

A

judgment sampling

“purposive sampling

78
Q

advantage of judgment sampling

A

if the judgment of the researcher is correct, the sample generated by judgment sampling will be better than one generated by convenience sampling

79
Q

sampling in which participants are selected acc to pre-specified quotas regarding demographics, attitudes, behaviors or some other criteria

A

quota sampling

80
Q

3 advantages of quota sampling

A
  1. sample generated contains specific subgroups in the proportions desired by researchers
  2. appropriate subgroups are identified and included in the survey
  3. reduce selection bias by field workers
81
Q

2 disad of quota s.

A
  1. success of study dependent on subjective decisions made by researchers
  2. representativeness of sample cannot be measured
82
Q

sampling in which set of respondents are chosen and they help researcher identify additional ppl to be included in study

A

snowball sampling

83
Q

Snowball/referral sampling is used when:

A
  1. defined target population is small and unique

2. compiling a complete list of sampling units is very difficult

84
Q

advantages of snowball s.

A
  1. good way to reach members of small, hard-to-reach, uniquely defined target population
  2. most useful in qualitative research
85
Q

2 disad of snowball s.

A
  1. allows bias to enter study

2. ability to generalize the results to members of targett population is limited

86
Q

4 types of nonprobability sampling methods

A
  1. Convenience sampling
  2. judgment s.
  3. Quota s.
  4. Snowball s.
87
Q

7 factors to consider in sample design

A
  1. Research objectives
  2. degree of accuracy
  3. resources
  4. time frame
  5. knowledge of target population
  6. research scope
  7. statistical analysis needs
88
Q

3 factors affecting sample size for probability designs:

A
  1. Level of confidence desired in estimate
  2. variability of the population characteristic under investigation
  3. Degree of precision desired in estimating the population characteristic
89
Q

certainty that the true value of what we are estimating falls within the precision range we have selected

A

confidence

90
Q

acceptable amount of error in sample estimate

A

precision

91
Q

For a particular sample size, there is a trade off between degree of ______ and degree of _____

A

Degree of confidence & degree of precision

92
Q

When the defined target population size in a consumer study is 500 elements or less, the research should consider taking a ____

A

census of the population rather than a sample

93
Q

Blueprint or framework needed to ensure that the data collected are represented of the defined target population

A

sampling plan

94
Q

7 steps to developing a sampling plan

A
  1. define target population
  2. select the data collection method
  3. identify the sampling frame(s) needed
  4. select the appropriate sampling method
  5. determine necessary sample sizes and overall contact rates
  6. create plan for selecting units
  7. execute the operational plan
95
Q

process of assigning intensity (amount) to the info about constructs, concepts and objects

A

measurement

96
Q

Measurement of a sample size consists of 2 tasks

A
  1. Construct development

2. Scale measurement

97
Q

Hypothetical variable made up of a set of component responses or behaviors that are thought to be related

A

construct

98
Q

constructs are made up of a combination of ____

A

several related indicator variable that together define the concept being measured

99
Q

integrative process in which resarchers determine what specific data should be collected for solving the defined research problem

A

construct development

100
Q

process of assigning descriptors to represent the range of possible responses to a question about a particular object or construct

A

scale measurement

101
Q

combination of labels in scale measurement

A

scale descriptors

102
Q

designated degrees of intensity assigned to the responses in a given questioning or observation method

A

scale points

103
Q

all scale measurements can eb classified as 1 of 4 basic levels

A
  1. Nominal scale
  2. ordinal scale
  3. interval scale
  4. ration scale
104
Q

this scale measurement focuses on only requiring respondent to provide some type of descriptor as the raw response (married/single)

A

nominal scale

105
Q

type of scale measurement that allows a respondent to express “relative’ magnitude between the raw responses to a ?

A

ordinal scale

106
Q

this scale measurement demonstrates the absolute difference between each scale point (strongly agree/strongly disagree)

A

interval scale

107
Q

scale measurement that allows for the identification of absolute differences between each scale point and absolute comparisons between raw responses

A

ratio scale

108
Q

Central Tendency & dispersion

A

central tendency –> mode, mean, median

Dispersion –> frequency distribution, range, SD

109
Q

this scale measurement demonstrates the absolute difference between each scale point (strongly agree/strongly disagree)

A

interval scale

110
Q

scale measurement that allows for the identification of absolute differences between each scale point and absolute comparisons between raw responses

A

ratio scale

111
Q

Central Tendency & dispersion

A

central tendency –> mode, mean, median

Dispersion –> frequency distribution, range, SD

112
Q

If a nominal scale is used, analysis of the raw data can only be done using ___ and ____

A

modes & frequency distributions

113
Q

If ordinal scale is used, analysis of raw data can be done using ___ and ____

A

medians & ranges

plus modes and frequency distribution

114
Q

If interval/ratio scales are used, analysis of raw data can be done through the use of ___ and ____

A

sample means & estimated SD (s.a. sample statistic)

115
Q

Construct/scale development process

A
  1. identify and define construct
  2. Create initial pool of attribute statements
  3. Access and select reduced sets of items
  4. Design scales and pretest
  5. Complete statistical analysis
  6. Refine and purify scales
  7. Complete final scale evaluation
116
Q

ordinal scale format that asks respondents to indicate the extent to which they agree or disagree with a series of mental or behavioral belief statements about a given object

A

Likert Scale

117
Q

Unique bipolar ordinal scale format that captures a person’s attitudes and/or feelings about a given object

A

Semantic differential scale

118
Q

with the semantic differential scale, only the ___ of the scale are labeled

A

endpoints

119
Q

Disadvantage of Semantic Differential Scale

A

inappropriate narrative expressions of the scale descriptors

120
Q

special type of rating scale designed to capture the likelihood that people will demonstrate some type of predictable behavior intent toward purchasing an object or service in a future time frame

A

behavioral intentional scale

121
Q

This scale is a good predictor of consumers’ choices of frequently purchased and durable consumer goods

A

Behavioral intentional scale

122
Q

scale that requires a judgment without reference to another object, person or concept

A

noncomparative rating scale

123
Q

Scale that requires a judgment comparing one object person or concept against another on the scale

A

Comparative rating scale

124
Q

This scale uses a scale point format that presents respondent with some type of graphic continuum as the set of possible raw responses to a given question

A

Graphic rating scale

125
Q

4 Scale measurement issues

A
  1. single-item or multiple-item scales
  2. clear wording
  3. Screening questions
  4. skipping questions
126
Q

scale format that collects data about only one attribute of an object or construct

A

single item scale

127
Q

formal framework consisting of a set of questions/scales designed to generate primary data

A

questionnaire

128
Q

This involves using a process that takes established sets of question/scale measurements and formats them into a complete instrument

A

questionnaire construction

129
Q

7 Steps in questionnaire designs

A
  1. Confirm research objectives
  2. select appropriate data collection method
  3. develop ?s and scaling
  4. determine layout and evaluate questionnaire
  5. obtain initial client approval
  6. pretest, revise, and finalize questionnaire
  7. implement survey
130
Q

open-ended format where respondent replies in their own words

A

unstructured questions

131
Q

close ended format where respondents respond from a set of possible responses

A

structured questions

132
Q

3 qualities of bad questions

A
  1. unanswerable
  2. leading or loaded
  3. double barreled questions (asking two things at once)
133
Q

Guidelines for evaluating the adequacy of questions

A
  1. Use simple words (no technical)
  2. avoid qualifying phrases
  3. ensure response categories are mutually exclusive
  4. ensure question and scale statements are meaningful to the respondents
  5. avoid arranging response categories in a manner that may bias responses
  6. do not double-barrel questions
134
Q

Considerations in questionnaire design

A
  • Confirm the research objectives before starting
  • determine data reqs to complete objectives
  • include general description of study in intro
  • ensure instructions are clear
  • arrange ?s in a logical order
  • begin with simple questions and then progress to more difficult ones
  • ask personal/sensitive questions at the end
  • avoid asking questions with diff measurement formats
  • end with thank you
135
Q

separate written communication to prospective respondent designed to enhance that person’s willingness to participate

A

cover letter

136
Q

Guidelines for developing cover letter

A

-personalize
identify sponsoring org
-state purposely and importance clearly
-promise anonymity or confidentiality
-clarify the general time frame of doing study
-reinforce importance of participation
-acknowledge reasons for non participation
-time requirements and any compensation
-explain completion data and where and how to return
-advanced thank you

137
Q

Every set of data collected needs some summary info developed containing: (3)

A
  1. Central tendency and dispersion
  2. Relationship of sample data
  3. Hypothesis testing
138
Q

Measure of central tendency that describes distribution best for nominal, ordinal, interval/ratio data

A

nominal –> mode
ordinal –> median
interval/ratio –> mean

139
Q

describes how close to the mean or other measure of central tendency, the rest of values fall

A

measures of dispersion

140
Q

distance b.t smallest and largest value in setq

A

range

141
Q

avg distance of the distribution values form mean

A

SD

142
Q

two or more groups of responses that are tested as though they may come from different populations

A

independent samples

143
Q

two or more groups of responses that originated from sample population

A

related samples

144
Q

used for 30+ ppl in sample

A

z-test (or unknown #)

145
Q

univariate test of significance is appropriate for this kind of data

A

interval or ratio

146
Q

test to compare charac of two groups or two groups

A

bivariate statistical test

147
Q

3 things bivariate statistical test consists of

A
  1. cross-tabulation with chi-square
  2. t-test to compare two means
  3. analysis of variance (ANOVA) to comapre three or more means
148
Q

enables researcher to test for statistical significance between the frequency distributions of 2 or more nominally scaled variables in a cross tabulation table to determine if there is any association between the variables

A

chi-square analysis

149
Q

Comparing means requires this type of data

A

ratio/interval

150
Q

difference between the means divided by the variability of random means

A

t-test

151
Q

ration of difference between the two sample means and the std error

A

t-test

152
Q

T-test tries to determine if the difference between the two sample means ____

A

occurred by chance

153
Q

statistical technique that determines if three or more means are statistically different form each other

A

Analysis of valiance (ANOVA)

154
Q

In order to perform ANOVA, the dependent variable must be ______ and the independent variable must be ____

A

dependent variable = measurable (interval/ratio scaled)

Independent variable = categorical

155
Q

What is one-way ANOVA?

A

only one independent variable

156
Q

this test is used to statistically evaluate the differences between the ggroup means in ANOVA

A

f-test

157
Q

in ANOVA, total variance in a set of responses can be separated into ___ group and ___ group variance

A

between group and within group

158
Q

the larger the diff in the variance b/t groups, ____ (ANOVA)

A

the larger the f-ratio

159
Q

ANOVA does not tell us____

A

where the significant lies

160
Q

process used to develop maps showing the perceptions of respondents

A

perceptual mapping

161
Q

this test is used to statistically evaluate the differences between the ggroup means in ANOVA

A

f-test

162
Q

in ANOVA, total variance in a set of responses can be separated into ___ group and ___ group variance

A

between group and within group

163
Q

the larger the diff in the variance b/t groups, ____ (ANOVA)

A

the larger the f-ratio

164
Q

ANOVA does not tell us____

A

where the significant lies

165
Q

Quantitative data uses numbers and stats to summarize _______

A

Demographics

Attitudes

Behaviors

165
Q

process used to develop maps showing the perceptions of respondents

A

perceptual mapping

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