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Answer the questions in the docx, complete the excel according to the requirements in the document, and answer the questions.1.Consider the following survey question asked in person.“How many drinks do you typically have when going out?”a.What are some potential sources of respondent errors for this question? (List at least 2) Be specific.b.Which of the listed errors are systematic? Which are random? Why?c.How would you change the phrasing and/or way in which this question is asked to decrease the potential for biases?2.Use the following class survey questions for this question(1) “I wish I spent more time on social media”(2) “I wish I spent less time on social media”a.Transform “I wish I spent more time on social media” using reverse coding (7 becomes 1, 1 becomes 7, etc.).b.Compute the Cronbach’s alpha for the computed reverse coded variable and the second variable (“wish I spend less time”). What is it?c.Do these 2 variables reliably measure the same thing? If so, what would you call this underlying concept, why? If not, why do you think these questions do not measure the same thing?3.Use the following class survey questions for this question(1) “I have acquired a lot of new knowledge in college.”(2) “I have acquired many new marketable skills in college.”(3) “How much do you expect to make a year in your first job after graduation?”a.Compute Cronbach’s alpha for the first 2 variables. What is it?b.Do these 2 variables reliably measure the same thing? Use .6 as a cutoff.c.Assume these 2 variables do measure the same thing, compute an average index of the 2 variables. What would you call the concept this index measures?d.What do you expect to be the relationship between this index and the 3rd variable? Explain.e.Run a regression to test this hypothesis. What did you find?Assignment 5 – Measurement & Survey
Research
1. Consider the following survey question asked in person.
“How many drinks do you typically have when going out?”
a. What are some potential sources of respondent errors for this question? (List at least 2)
Be specific.
b. Which of the listed errors are systematic? Which are random? Why?
c. How would you change the phrasing and/or way in which this question is asked to
decrease the potential for biases?
2. Use the following class survey questions for this question
(1) “I wish I spent more time on social media”
(2) “I wish I spent less time on social media”
a. Transform “I wish I spent more time on social media” using reverse coding (7 becomes
1, 1 becomes 7, etc.).
b. Compute the Cronbach’s alpha for the computed reverse coded variable and the second
variable (“wish I spend less time”). What is it?
c. Do these 2 variables reliably measure the same thing? If so, what would you call this
underlying concept, why? If not, why do you think these questions do not measure the
same thing?
3. Use the following class survey questions for this question
(1) “I have acquired a lot of new knowledge in college.”
(2) “I have acquired many new marketable skills in college.”
(3) “How much do you expect to make a year in your first job after graduation?”
a. Compute Cronbach’s alpha for the first 2 variables. What is it?
b. Do these 2 variables reliably measure the same thing? Use .6 as a cutoff.
c. Assume these 2 variables do measure the same thing, compute an average index of the
2 variables. What would you call the concept this index measures?
d. What do you expect to be the relationship between this index and the 3rd variable?
Explain.
e. Run a regression to test this hypothesis. What did you find?
Reverse coded variable
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How much do you expect to make a year in your first job after graduation?
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Measurement & Attitudes
What is a measure? Why do we need it?
• Def: Measure is the process of describing some property of a
phenomenon of interest usually by assigning numbers in a reliable
and valid way.
• Ex. The concept distance can be measured with a ruler, odometer, etc.
• Why? We need measurements to summarize a population’s position
on some concept
• We measure people’s heights to learn about how tall a group of people are
• We measure marketing variables in a similar way
What are somethings we need to measure in
marketing?
ABC’s of attitude
Affect, behavior, cognition
Constructs
• Generally used interchangeably with
concept
• A term used for concepts that are
measured with multiple variables
• Sometimes a single variable cannot
capture a concept alone
• Using multiple variables to measure
one concept can provide a more
complete account of some concept
than could any single variable
• Satisfaction / Political Identity / Loyalty
etc.
• “fuzzy” concepts that can be
measured in multiple ways
Attribute
• An attribute is a single characteristic or fundamental feature of an object, person, situation,
or issue
• Attribute assessment is common in marketing research
• The measures of attributes are often combined to represent some less concrete concept
• Ex. Satisfaction at a hotel can often be broken down into room, service, cleanliness,
etc.
Variables
• Variables capture different concept/construct/attribute values (i.e. different levels of a
construct)
• Scales capture variance in concepts and as such, the scales provide the researcher’s
variables
• There is little difference between a concept and a variable
• Variable/Scale: customer satisfaction as indicated by answers to question, “how satisfied
are you on a scale from 1-7”
Scale
• A range of values that correspond to different values in the concept being measured
• Correspondence rules that indicate that a certain value on a scale corresponds to some
true value of a concept, hopefully in a truthful way
• Ex. An odometer (measure) can be scaled to miles or kilometers.
Satisfaction
Room satisfaction Service satisfaction
Construct Concept
Attribute
How satisfied are you with the room?
How satisfied are you with the service?
Variable
1-7 rating
Scale
• Nominal
• Ordinal
• Interval
• Ratio
Nominal
• “Nom”: Name
• Identification
• If there are numbers, they are just
labels.
• Ex. What is your group number? What
is your gender?
Ordinal
• Order of scale matters, no interval
• Ex. College Football Rankings, sales
rankings, rank the following social
media platforms from most to least
favorite.
• Has ordinal properties
Interval
• ~Continuous
• Captures quantities but no anchoring
for scale (no preservation of linearity)
• E.g. Fahrenheit temperature 80F is not 2x
40F, so it is an interval scale
• Very commonly used in marketing.
• Likert scales: odd numbered (1-7/ 1-5)
scales
Ratio
• Ratio between intervals is preserved.
• i.e. difference between 5 and 4 and 4
and 3 have consistent meaning.
• Ex. Points scored in a basketball game,
height, \$ profit, etc.
• Zero means the absence of concept.
Summarizing
measures
• Discrete
• Categories
• Mode/count/%
• Continuous
• A scalar value (somewhere on the
real number line)
• Mean/standard deviation/ median
• Beware of ratio vs. interval
measures when interpreting.
• Avg of 5 stars vs. 4 stars doesn’t
mean the same thing as 4 stars
vs. 3 stars in terms of difference
in quality.
Reliability
Measuring reliability
• Multiple measures
• Index/Composite (sum like dow jones or average like daily return)
• Correlation between items can signify internal consistency
• α:
• Split items in half, test correlation
• Average of correlation across all splits = α
• We will talk about Cronbach’s alpha
• Τest / Retest reliability
• Same test under same conditions to the same respondents at different times
• Returns same results?
Chronbach’s alpha
• Chronbach’s alpha
• For “K” components measuring the same construct
• Each component is “Yi”, sum of all components is X, sigma^2: variance
• >.6 suggests there is some internal consistency.

Reliable == valid
Must be representative of the “truth”
Face validity – fits intuition
Criterion validity – correlate with other known
measures
• E.x. Satisfaction scores correlate with Net
Promoter Score
Validity
• Construct validity – gold standard
• Face + criterion validity
• Convergent – similar attributes correlated
• Room/Service/Cleanliness ratings correlate
with satisfaction index
• Discriminant validity – different than other
known constructs
• Lower correlation of satisfaction with
repurchase
• Fit validity – construct predicts outcomes
according to theory
• Satisfaction predicts repurchase intent
Different kinds of scales

Category
Likert
Semantic differential
Constant sum
Graphic rating
Ranking
Paired comparison
• Conjoint
• N(N-1)/2
• Multiattribute scale
Likert Scale
• Odd numbered (so there’s a center/neutral option)
• 1 least agreed…. 7 most agreed
• Treat as continuous interval scale
Semantic differential
Again, a numerical score assigned to each position, treated as continuous
interval scale.
Constant sum
• Respondents asked to allocate a fixed sum of points (usually 100) to
multiple items.
• Ex. Assign the % of your free time spent to the following activities
(must sum to 100)
• Studying
• Partying
• Other
Graphic rating
Again mapped on to some continuous interval scale
Ranking
• Ask respondent to rank order their preferences
• Ex. Rank the following social media platforms from most to least favorite
• Ordinal scale
• Summarize with
• % top choice
• Average ranking
Paired comparison
• Compare side by side alternatives
• Used to measure preferences where alternatives are determined by
underlying attributes of interest
• Used often in new product design research with conjoint studies
• If there are n alternatives, then there will be n(n-1)/2 pairs (large)
• Talk about more in experiments chapter
Multiattribute scale
• Multiple measures of construct
• Use index score

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