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ADV 344k Exam 3
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Terms in this set (124)
Dependent variable
measure of effect; what changes as a result of manipulation
Independent variable
what is changed by researchers
Descriptive
Survey research is always
Split/AB Testing
Half the sample gets one stimuli and half gets the other
Deductive approach
this approach begins with a hypothesis
inductive approach
this approach uses research questions to narrow the scope of the research.
qualitative
the inductive approach is associated with this type of research
in person, telephone, self
3 ways to administer surveys
Online
These surveys are the fastest and cheapest to administer
In-person interviews
This is the slowest type of data collection
Response Rate
Percentage of valid sample who provide a valid, completed interview
How to calculate response rate
Divide number of respondents completing survey by total number of respondents in the valid sample
Sampling Error
Error caused by method of sampling used and the size of the sample
How to reduce sampling error?
increase sample size and use appropriate sampling method.
Non Sampling Error
Error that is the result of human mishap in either design or survey execution.
directly measured
Non sampling errors cannot be __________________
Non Response Error
Error that occurs when respondents either cannot be reached or are unwilling to participate.
Response Error
Error that occurs when respondents intentionally or unintentionally respond to questions in ways that do not reflect their true answers
IRB
Reviews all research generated that has human participants and ensures that research follows all ethical protocols for human research. Institutional Review Board
Concept
An idea or term that summarizes similar observations or experiences
Conceptualization
The process of isolating the concepts that make up a phenomenon
Operationalization
The process of determining how to measure a concept's presence or absence
Exhaustive
If a survey is _________, it captures all levels of the variable
Mutually exclusive
If a survey is ___________, response options don't overlap
Questions to ask during Operationalization
What is the concept?
How will it surface and vary within the sample?
How will we measure its indicators?
Likert Scale
Offers statements and respondent indicates level of agreement with those statements
Semantic Differential
Offers bipolar adjectives and respondent indicates location of their attitude in relation to those adjectives
Closed-ended item
Question that requires the respondent to choose from a predetermined set of responses or scale points
Open-ended item
Question that allows participant to write in answers
When is having only one item for a given topic ok?
Common for demographic info, public opinion polls
Questionnaire Design (7 steps)
1. Confirm research objectives
2. Select appropriate data collection method
3. Develop questions and scaling
4. Determine layout and evaluate questionnaire
5. Obtain initial client approval
6. Pretest, revise, and finalize questionnaire
7. Implement the survey
Indices
The sum or average of several questions used to measure the same concept
Handbook of Marketing Scales
A clear and user-friendly collection of multi-item, self-report measures developed and frequently used in consumer behavior and marketing research.
Product Attachment
The extent to which an individual uses an object to develop and maintain a cognitive structure of self
Product Involvement
A person's perceived relevance of an object based on inherent needs, values, and interests.
Behavioral Intention Scale
A 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.
Scale Points
Designated degrees of intensity assigned to the responses in a given questioning or observation method. Assign numbers to responses which in turn enable statistical analysis.
Nominal
A scale in which the questions require respondents to provide only some type of descriptor as the raw response
Ordinal
A scale that allows a respondent to express relative magnitude between the answers to a question. The order of the values is what's important and significant, but the differences between each one is not really known
Interval
A scale that demonstrates absolute differences between each scale point. Numeric scales in which we know not only the order, but also the exact differences between the values.
Likert
Example of an Interval Scale
Ratio
A scale that allows the researcher not only to identify the absolute differences between each scale point but also to make comparisons between the responses
Validity
Assesses whether a scale measures what it is supposed to measure
4 Types of Validity
Face, Content, convergent, discriminant
Face Validity
A systematic but subjective assessment of a scale's ability to measure what it is supposed to measure, "looks good"
Content Validity
A measure of the extent to which a construct represents all the relevant dimensions
Convergent Validity
Evaluated with multi-item scales and represents a situation in which the multiple items measuring the same construct share a high proportion of variance
Discriminant Validity
The extent to which a single construct differs from other constructs and represents a unique construct
Reliability
The extent to which a scale can reproduce the same or similar measurement results in repeated trials
Test-retest
Repeating the scale measurement with either the same sample of respondents at two different times or two different samples of respondents from the same defined target population under as nearly the same conditions as possible.
Equivalent Form
Researchers create two similar yet different scale measurements for the given construct and administer both forms to either the same sample of respondents or two samples of respondents from the same defined target population
Internal Consistency
The degree to which the individual questions of a construct are correlated
Cronbach's alpha
Used to test inter-item reliability
Interpreting Cronbach's alpha
Less than 0.60 is unacceptable
.60-.65 undesirable
.66-.70 minimally acceptable
.71-.80 respectable
.81-.90+ very good
Qualtrics
Online survey creation software to design an online survey and collect data relatively easily and inexpensively
Hypothesis
An unproven supposition or proposition developed before data collection that tentatively explains certain facts or phenomena
Null hypothesis
Hypothesis that says that there is no difference in the group means
Alternative Hypothesis
Hypothesis that states that there is a difference between the group means
Descriptive statistics
Statistics used to describe the distribution of and relationship among variables mean, median, mode, frequency, correlation
Bimodal
Distribution with two different modes, and two distinct peaks when graphed
Pearson Correlation coefficient
A statistical measure of the strength of a linear relationship between two metric variables
Bivariate Pearson correlations are reported as:
Significance, strength, direction of the relationship
Bivariate Pearson correlation measures
the degree of linear association between two variables
Mean
The arithmetic average of the sample; all values of a distribution of responses are summed and divided by the number of valid responses
Median
The middle value of a rank-ordered distribution; exactly half of the responses are above and half are below
Mode
The most common value in the set of responses to a question; the response most often given to a question
Range
The distance between the smallest and largest values in a set of responses
Standard Deviation
The average distance of the distribution values from the mean
Chi-Square Analysis
Assesses how closely the observed frequencies fit the pattern of the expected frequencies and is referred to as a "goodness-of-fit" test
Chi Square Analysis enables researchers to test for
Statistical significance between the frequency distributions of two (or more) nominally scaled variables in a cross tabulation table to determine if there is any association between the variables
Chi-square statistic
tests whether or not the observed data are distributed the way we would expect them to be, given the assumption that the variables are not related
Cross Tabulation
A frequency distribution of responses on two or more sets of variables
Cross tabulation is used to determine if
differences exist between subgroups of the total sample
cross tabulation is
used to compare groups
Contingency Table
Displays the distribution of one variable for each category of another variable
ANOVA
A statistical technique that determines whether three or more means are statistically different from one anothe
ANOVA is used to
examine group means
68%
Approximately _______% of data will be within 1 SD of the mean
95%
Approximately _______% of data will be within 2 SD of the mean
99.7%
Approximately _______% of data will be within 3 SD of the mean
bell shaped
Normally distributed data is
Negative skew
The left tail is longer; the mass of the distribution is concentrated on the right of the figure
Positive skew
The right tail is longer; the mass of the distribution is concentrated on the left of the figure
Excel
Statistics software that easily calculates mean, median, mode, and standard deviation of large data sets
Frequency Distribution Table
a table showing how many people (as a number and a percentage) answered in each of the response categories.
Independent samples t-test
Evaluates the difference between the means of two independent or unrelated groups
Outlier
An exceptionally high or exceptionally low value
P-value
The likelihood that the relationship you are observing is observed by pure chance.
A p-value of 0.05 means that
there is a 5% chance that the relationship between the independent variable(s) and the dependent variable that your model established doesn't actually exist (was due to chance-a fluke).
0 and 1
P-value will always be between
5%
When studying p-values, it is standard for social scientists to be willing to accept anything less than a _______ chance.
p < .05
to note something is significant when studying p-values, we say _______.
significance
p-value helps us evaluate the ____________ of the data
Interpreting Pearson correlation
.0 to .2 = no relationship (.0), very weak
.21 to .4 = weak
.41 to .6= moderate
.61 to .8 = strong
.81 to 1= very strong, perfect relationship (1)
Bivariate regression analysis
A statistical technique that analyzes the linear relationship between two variables by estimating coefficients for an equation for a straight line. One variable is designated as a dependent variable and the other is called and independent or predictor variable.
Regression Coefficient
An indicator of the importance of an independent variable in predicting a dependent variable. In a regression coefficient, large coefficients are good predictors and small coefficients are weak predictors
Multiple Regression Analysis
A statistical technique which analyzes the linear relationship between a dependent variable and multiple independent variables by estimating coefficients for the equation for a straight line
Beta coefficient
An estimated regression coefficient that has been recalculated to have a mean of 0 and a standard deviation of 1.
Beta coefficient enables
independent variables with different units of measurement to be directly compared on their association with the dependent variable
Correlation
Shows that a relationship exists between variables
r^2
Test statistic for correlation is
p-value
When assessing correlation, we look at the
3 things we need when reporting correlational relationships
Direction
Strength
Significance
Variance
The average of the squared differences (for each case) from the Mean.
How to calculate variance
Find the Mean (the simple average of the numbers)
Then for each number: subtract the Mean and then square the result (the squared difference).
Then work out the average of those squared differences.
Perceptual mapping
A map of respondents' brand/product perceptions displayed on two dimensions
Coding
grouping and assigning values to various responses from a survey instrument
Curbstoning
Cheating or falsifying data during collection
Data Entry
Those tasks involved with the direct input of the coded data into some specific software package that ultimately allows for the research analyst to manipulate and transform the raw data into useful information
Data validation
The process of determining whether a survey's interviewers or observations were conducted correctly and are free of fraud or bias
Editing
The process where raw data are checked for mistakes made by either the interviewer or the respondent OR in the process of transferring info from scanner databases/other sources to the company data warehouse
Objectives of Marketing Research Reports
To effectively communicate the findings of the marketing research project
To provide interpretations of those findings in the form of sound and logical recommendations
To establish the credibility of the research project
To serve as a future reference document for strategic or tactical decisions
Must establish these 2 things in reports
Believability and credibility
Credibility
The quality of a report that is related to its accuracy, believability, and professional organization
Believability
The quality of a report that is based on clear and logical thinking, precise expression, accurate presentation
Format of Marketing Reports
Title page
Table of contents
Executive summary
Introduction
Research method and procedures
Data analysis and findings
Conclusions and recommendations
Limitations
Appendices
Executive summary
This part of the marketing report includes:
Research objectives
Concise statement of method
Summary of key findings
Conclusion and recommendations
Must be complete enough to provide a true representation of the document but in summary form. Shoot for one page
Introduction
This part of the marketing report includes:
Definition of terms
Relevant background information
The study's scope and emphasis
Research method and procedures
This part of the marketing report includes:
Research design used
Types of secondary data included
Procedure used to collect primary data, if any
Sample and sampling processes
Data analysis and findings
This part of the marketing report includes:
Body of the marketing research report consists of the study's findings
Presentation of findings will be different for each project because data analysis requirements differ for each project
Reporting frequencies - Through tables, bar charts, or pie charts (not all three!)
Limitations
This part of the marketing report includes:
Weaknesses in research methodology that might affect confidence in research conclusions
Appendices
This part of the marketing report includes:
A section following the main body of the report
1. Used in house complex, detailed or technical information
2. i.e. PDF of survey
Visual presentations should begin with a slide showing: (4 things)
1. Title of presentation
2. Speaker's name
3. Client identity
4. Research firm (if you hired one)
Visual presentations should conclude with
recommendations, conclusions, and research implications
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