Selecting a relatively small number of elements from a larger defined group of elements
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Why do we collect a sample?
Impossible/Unreasonable to conduct a census; Less time consuming and less costly; Influence the type of research design, the survey instrument, and actual questionaire
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Population
an identifiable group of elements (people, products, organizations)
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Sampling Units
Target population elements actually available to be used during the sampling process
Ex: Study the brand's advertising strategy; A brands recent ad copy.
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Sampling Frame
The list of all eligible sampling units
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Sampling Errors
A statistical error; It's any bias that results from mistakes in either 1.) the selection process or prospective sampling units or 2.) determining the sample size
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Nonsampling Errors
Is an error that occurs during data collection, causing the data to differ from the true values. Ex: data entry errors, biased survey questions, biased processing/decision making; Hard to detect/define.
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Probability sampling
Knowing the probability of being selected for the sample
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Nonprobability Sampling
Not knowing the probability of selecting each sampling unit (don't know the sampling error) based on the judgment of the researcher and may or may not be representative of the target population.
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Simple Sampling
A probability sampling procedure in which every sampling unit has a known and equal chance of being selected
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Systematic Sampling
defined target population is ordered in some way, usually a customer list, taxpayer roll, or membership roster and selected systematically
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Stratified Random Sampling
Separation of the target population into groups, called strata, and the selection of samples from each stratum.
1. Divide target audience population into homogeneous subgroups/strata 2. Combine the samples into a single sample of the target population
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Convenience Sampling
Draws samples at the convenience of the researcher; Commonly used in the early stages of research and pretesting questionnaires
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Snowball Sampling
A set of respondents is chosen, and they help the researcher identify additional respondents; Typically used when the defined target population is small and unique or compiling a complete list of sampling units is difficult; Referral Sampling
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Determining the appropriate sampling design & what to consider
Research Objective: calls for qualitative or quantitative Degree of Accuracy: are inferences or just insights needed? Resources: is there a tight budget? Time Frame: how quickly does the research need to be completed? How Much Prior Knowledge: are there complete lists? how easy is it too generate sampling frame of respondents? Scope of Research: international, national, regional, or local? Statistical Analysis Needed: is statistical projection or hypothesis testing required?
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What is a measurement?
The process of developing methods to systematically characterize or quantify information about persons, events, ideas, or objects of interest.
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Abstract
An abstract idea or concept formed in a persons mind; A combination of a number of similar characteristics of the construct
Example: consumers intention to support the organization
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Variables
Consists of those characteristics that collectively define the concept
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Construct Development
is the process in which researchers identify characteristics that define the concept being studied by the researcher
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Construct
An unobservable concept measured indirectly by a group of related variables
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Consumer Concrete Properties
age, marital status, sex, income, brand last purchased, dollar amount last purchased, types of products purchased, color of eyes and hair
name of company, number of employees, number of locations, total assets, fortune 500 rating, computer capacity, types and numbers of products and service offerings
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Organization Abstract Properties
competence of employees, quality control, channel power, competitive advantages, company image, consumer orientated practices
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Scale Measurement
Assigning a set of scale descriptors to represent the range of possible responses to a question about a particular object or construct
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Nominal Scale
Requires respondent to provide only some type of descriptor as the raw response
Example(s): Please indicate your marital status: ___ Married ____ Single ____ Divorced Do you like or dislike chocolate ice cream? ___ Like ____ Dislike
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Ordinal Scale
Allows a respondent to express relative magnitude between the answers to a question
Example: For each pair of retail discount stores, circle the one store at which you would be more likely to shop: _____ Costco or Target _____ Target or Walmart _____ Walmart or Costco
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Interval Scale
Demonstrates absolute differences between each scale point
Example: How likely are you to recommend the Santa Fe Grill to a friend?
Definitely Will Not Rec. Definitely Will Rec. 1 2 3 4 5 6 7
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Ratio Scale
allows the researcher not only to identify the absolute differences between each scale but also to make comparisons between responses
Example(s): Please circle the number of children under the age of 18 currently living in your household __1 __2 __3 __4 __5 __6 __7 If more than 7 please specify __
In the past seven days, how many times did you go online to shop at Amazon? ______ # of times
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Reliablity
Results are consistent
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Validity
Results satisfy objectives
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Scale Reliability
extent to which a scale can reproduce the same or similar measurement results in repeated trials; measures consistency
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Scale Validity
assesses whether a scale measures what it is supposed to measure
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Likert Scale
An ORDINAL scale format asking respondents to indicate the extent to which they agree or disagree with a series of mental or behavioral belief statements about a given subject
Example: DA - Disagree SDA- Somewhat DA AG- Agree
DA SDA SAG AG I buy many things with a credit Card ___ ___ ____ ____ I wish we had a lot more money ___ ____ ____ ____
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Semantic Scale
A unique bipolar ORDINAL scale format that captures a persons attitudes or feelings on a given object; Semantic Differential Scale; Use even number of anchors.
The inappropriate narrative expressions of the scale descriptors; A well-designed scale has truly bipolar anchors; Use even number of points.
GOOD Example: (Like) 1 2 3 4 5 6 7 8 (Dislike)
BAD Example: (Like) 1 2 3 4 5 6 7 8 (Interesting)
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Balanced Scale
has an equal number of positive and negative response alternatives
Example: - Very Satisfied - Satisfied - Dissatisfied - Very dissatisfied
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Unbalanced Scale
Has more options on one side
Example: - Very Likely - Somewhat Likely - Likely - Unlikely - Very Unlikely
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Forced Choice
does NOT have a neutral descriptor; Even amount of options
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Comparative Scale
A respondent expresses their attitudes, feelings, or behaviors about an object on the basis of some other object
Example: Please rank your top three preferences of types of music you enjoy listening to by writing your first, second, and third choices below.
First Choice ______________________ Second Choice____________________ Third Choice______________________
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Non-Comparative Scale
Used when the objective is to have respondent express their attitudes, behavior, or intentions about a specific object WITHOUT making references to another
Example: Smiley Face pain descriptor
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Measurement Scale Issues
When phrasing the question element of the scale, use clear wording; Make sure scale point descriptors are relevant and adequate
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Double Barreled Questions - BAD
Includes two or more attributes in the same question, but responses allow comment on a single issue
Example: How well do you get along with your managers and coworkers?
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Leading Question - BAD
Influences the respondents answers
Example: Our customer service team is the most responsive in the industry. How responsive --or unresponsive-- do you think they are?
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Double Negative Question - BAD
Contains two negative thoughts in the same question
Example: Do you oppose to not allowing policy to enforce all employees to wear a mask while flying?
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Loaded Question - BAD
Suggests a socially desirable answer or involves emotionally charged issue
Example: Should Americans buy imported automobiles that take away American jobs?
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Ambiguous Questions - BAD
involve possible responses that can be interpreted a number of ways
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Complex Questions - BAD
Are worded in a way making the respondent unsure of how to respond
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Designing Measurement Scales: Steps & Questions
1. Understanding the Research Problem 2. Identifying and Developing Constructs 3. Establishing Detailed Data Requirements 4. Understanding the Scaling Properties 5. Selecting the Appropriate Measurement Scale
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Developing Questionnaire Design: Steps
1. Confirm research objectives and information requirements 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 questions 7. Implement survey
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Step 1: Confirm research objectives and information requirements
Understanding whether the current advertising strategy is effective; To identify information you need to collect consumers opinion about the current advertising strategy
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Step 2: Select appropriate data collection method
Determine the most appropriate and effective communication method for interacting with the targeted respondents
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Step 3: Develop questions and scaling
Question Format - Unstructured: open-ended questions formatted to allow respondents to reply in their own words - allow unlimited response - often skipped** - Structured: close-ended questions that require the respondent to chose from a predetermined set of responses or scale points - reduces respondents effort - easy to answer
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Step 4: Layout and questionnaire assesment
Give overview of research; Screening Question(s); Arranging questions; Include demographic questions; End with thank you statement
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Step 5: Obtain initial client approval
Copies of questionnaire should be given to all parties involved in the project; Researchers MUST obtain final approval BEFORE pretest
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Institutional Review Board (IRB)
reviews and approved, prior to initiation, all research that involves use of human participants as the source of data, to make sure their rights are protected
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Step 6: Pretest, revise, and finalize questionnaire
- Pretest: survey sent to 10-30 subjects - Pilot Study: 100-200 respondents of target population
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Step 7: Implementing survey
Collect the data using the agreed upon questionnaire
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Data Analyzation Process
1. Data collection 2. Data reduction 3. Data display 4. Conclusion drawing/verifying
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Data Reduction
Researchers make decisions about how to categorize and represent the data; The most systematic method is to read transcripts and develop categories to represent the data.
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Coding
Unstructured data (open ended answers) requires some type of "coding" prior to analysis
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Code Sheet
has all the codes on it; the codes can be words or numbers that refer to categories on the coding sheet.
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Comparison - Analyzing
Developing and refining theory and constructs by analyzing the differences and similarities in passages, themes or types of participants
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Iteration - Analyzing
Working through the data several times in order to modify early ideas
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Memoing
writing down thoughts after interviews, focus groups, or site visits
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Negative Case Analysis
Used during the ITERATIVE process; Researchers look for cases that contradict the developing theories; Establish boundaries and conditions for theory; Researchers should be skeptical
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Data Display
Reduce and summarize data and convey major ideas
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Credibility - Qualitative Research
Describes the rigor and believability in qualitative analysis
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Emic Validity
Affirms that key members of a culture/subculture agree with findings
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Cross-Researcher Reliability
Degree of similarity in coding by different researchers
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Triangulation
Requires that research to be addressed from multiple perspectives
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Data validation
Determines if surveys, interviews, and observations were conducted correctly and free of errors
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Data Editing
Checking the data for mistakes by the interviewer, the respondent, or in the process of transferring information from scanner databases or other sources to the company data warehouse
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Data Entry
Procedure used to enter the data into a computer file for subsequent data analysis
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Error Detection
Identifies errors from data entry or other sources
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Tabulation
Counting the number of responses in categories
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Cross-Tabulation
Categorize responses to two or more questions
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Missing Data
Situation where respondents do not provide an answer to a question
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Mean
Average of data; Most commonly used measure of central tendency
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Median
The middle value of an ordered set of values
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Mode
The most occurring value in a distribution of values
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Range
The spread of data; Distance between the smallest and largest values
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Short Answer Q1: Write a question that measures people's response toward an advertisement using 1.) Likert Scale and 2.) Semantic Scale
Likert: This advertisement made me more likely to purchase a product from this company 1. Completely Disagree 2. Somewhat Disagree 3. Disagree 4. Agree 5. Somewhat Agree 6. Completely Agree
Semantic Scale: How was your last experience purchasing a product from company? (Pleasant) 1 2 3 4 5 6 7 8 (Not Pleasant)
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Short Answer Q2: Write advantages and disadvantages of using UNSTRUCTURED questions in a survey
Advantage: Respondents get to put in their personal input/thoughts Disadvantage: Likelihood for the question to be skipped entirely or will get no response