MRKT 396 FINAL
What types of questions might be irrelevant but sometimes necessary?
- Filler questions to disguise the purpose or sponsorship of the project. - Easy-to-answer or interesting questions at the beginning to build a relationship with respondents or capture their attention - Questions for the purpose of examining the quality of responses.
What are the various types of secondary data? Know and be able to apply (i.e., provide and describe an example of each).
- Internal: Ready to use, requires processing - External: Published materials, computerized database, syndicated services
What are the types of non-sampling errors?
- Non-response: No response from respondents - Response: When respondents give inaccurate or mis analyzed response (sources of error in sampling)
What are depth interviews?
- One on one - Unstructured - Direct - Personal interview
Examples of observation research?
- People watching in the grocery store
How can an interviewer probe?
- Repeating the question - Repeating the respondents reply - Using a pause or silent probe - Boosting or reassuring the respondent (there are no incorrect answers) - Eliciting clarification (can you tell me a bit more about that) - using objective/neutral questions or comments (why, anything else)
What are the limitations of ACS and US Decennial Census data?
- Think critically before comparing ACS data with data from other sources. (Ask yourself, are these data sources really comparable?) - ACS is a survey, not a census. It does not provide accurate 'counts' of populations. Be careful in drawing conclusions about small differences between estimates. Look for statistical significance. - Do not assume that annual fluctuations are long-term trends. - Remember that the 2006 ACS changed somewhat from previous years. Beginning in 2006, people living in group homes (e.g., dorms, nursing homes) were included in the sample.
What is the purpose of exploratory research? Methods?
-Provides NOVEL insights and understanding, CLARIFIES ISSUES -Small sample, non-representative -Data analysis is qualitative - Informal, unstructured -Followed by further exploratory or conclusive research OR sometimes the only research conducted Methods: -Pilot surveys, survey of experts -Case studies -Qualitative Research - Focus groups, interviews, observation -Secondary data, qualitative analysis
What is the purpose of conclusive research? Methods?
-Tests SPECIFIC HYPOTHESIS and examines relationships with clear statements of the problem (majority) -Large sample, representative -Data analysis is quantitative -Formal and structured -Finding used as input into decision making Methods -Surveys -Secondary research -Panels -Observational
What are the potential sources of error in measurement?
1) Other relatively stable characteristics of the individual that influence the test score, such as intelligence, social desirability, and education. 2) Short-term or transient personal factors, such as health, emotions,and fatigue. 3) Situational factors, such as the presence of other people, noise, and distractions. 4) Sampling of items included in the scale: addition, deletion, or changes in the scale items. 5) Lack of clarity of the scale, including the instructions or the items themselves. 6) Mechanical factors, such as poor printing, overcrowding items in the questionnaire, and poor design. 7) Administration of the scale, such as differences among interviewers. 8) Analysis factors, such as differences in scoring and statistical analysis.
How do we infer causality? What are the 3 conditions? Explain each.
1. CONCOMITANT VARIATION - The extent to which a cause, X, and an effect, Y, occur together or vary together in the way predicted by the hypothesis under consideration. CORRELATION 2. TIME ORDER OF OCCURRENCE OF VARIABLES - The 'Time order of occurrence' condition states that the causing event must occur either before or simultaneously with the effect; it cannot occur afterwards. CAUSE MUST PRECEDE EFFECT 3. ELIMINATION OF OTHER POSSIBLE CAUSAL FACTORS - Absence of other possible causal factors means that the factor or variable being investigated should be the only possible causal explanation. - Control for other possible explanations * All three of these must exist to infer causality
What are scale characteristics?
1. DESCRIPTION - unique labels or descriptors for each value (all scales have description) 2. ORDER- relative sizes or positions of descriptors. Order is denoted by descriptors such as greater than, less than, and equal to. 3. DISTANCE - absolute differences between the scale descriptors are known and may be expressed in units (e.g., a three person household has one person more than a two person household) 4. ORIGIN - unique or fixed beginning (i.e., has a true zero point)
Rules about question wording?
1. Define the issue in terms of who, what, when, and where (the 4 Ws). 2. Use ordinary words: questionnaire wording should match the vocabulary level of the respondents. 3. Use unambiguous words. The words used in a questionnaire should have a single meaning that is known to the respondents. 4. Avoid leading or biasing questions 5. Avoid implicit Alternatives. 7. Avoid generalizations and estimates. Questions should be worded so that the respondent does not have to make generalizations or estimates (again, make it easy for the respondent).
How do you evaluate the quality of secondary data?
1. Dependable Source: who gathered the data? 2. Objective: what was the purpose of the study? 3. Nature: what information was collected? 4. Currency: when was the information collected? 5. Method: how was the information collected? 6. Error: are the data accurate?
What are the threats to internal validity? Provide examples.
1. HISTORY - refers to specific events that are external to the experiment but occur at the same time as the experiment. 2. MATURATION - Changes in the test units themselves that occur with the passage of time. 3. TESTING EFFECTS - The experiment itself may produce its own effect on the responses observed. - MAIN TESTING EFFECT a prior observation affects a latter observation - INTERACTIVE TESTING EFFECTt a prior measurement affects the test unit's response to the independent variable. INSTRUMENTATION - Changes in the measuring instrument (interviews or observers) that might affect measurement. STATISTICAL REGRESSION- test units with extreme scores move closer to the average score during the course of the experiment. - People with extreme attitudes have more room for change so variation is more likely. SELECTION BIAS - Systematic differences between the test group and the control group due to a biased selection process MORTALITY - The loss of test units while the experiment is in progress.
What factors are used to determine sample size?
1. IMPORTANCE of decision 2. Nature of the research (EXPLORATORY VS CONCLUSIVE) 3. Number of variables (MORE VARIABLE, LARGER SAMPLE) 4. Nature of the analysis (TYPE OF STATISTICS) 5. Sample sizes used in similar studies 6. incidence rates & effect sizes (RARE INCIDENCES AND SMALL EFFECTS = LARGER SAMPLE SIZE) 7. Completion rates 8. Resource constraints
What are independent variables? Test units? Dependent variables? Extraneous variables?
1. Independent variables [IVs] - variables or alternatives that are manipulated and whose effects are measured and compared, e.g., price levels. 2. Test units [Participants] - individuals, organizations, or other entities whose response to the independent variables or treatments is being examined, e.g., consumers or stores. 3. Dependent variables [DVs] - Variables which measure the effect of the independent variables on the test units, e.g., sales, profits, and market shares. 4. Extraneous variables [covariates] - All variables other than the independent variables that affect the response of the test units (e.g., store size, store location, and competitive effort).
Why do we need to know scale types?
1. Knowing scale type enables us apply APPROPRIATE scales to appropriate marketing variables. 2. Knowing scale type informs us what STATISTICAL Analysis to perform in the data analysis stage. 3. Different types of scales may be used to measure the same variable.
What are different question techniques? Explain each.
1. LADDERING: the line of questioning proceeds from product characteristics to user characteristics. This technique allows the researcher to tap into the consumer's NETWORK of meanings. AIR TRAVEL EXAMPLE: "What attitudes do male middle managers have towards airlines?" Advertising theme: You will feel good about yourself when flying our airline. "You're The Boss." 2. HIDDEN ISSUE QUESTIONING: the focus is not on socially shared values but rather on personal "sore spots;" not on general lifestyles but on deeply felt personal concerns. AIR TRAVEL EXAMPLE: Advertising theme: communicate aggressiveness, high status, and competitive heritage of the airline. 3. SYMBOLIC ANALYSIS: attempts to analyze the symbolic meaning of objects by comparing them with their opposites. AIRLINE EXAMPLE: Advertising theme: The airline will do the same thing for a manager as Federal Express does for a package.
What are the various considerations you need to make in creating scales?
1. NUMBER OF CATEGORIES - Traditional guidelines suggest that there should be between 5 - 9 categories 2. BALANCED VS UN BALANCED - The scale should be balanced to obtain objective data 3. ODD/EVEN NO OF CATEGORIES - If neutral or indifferent scale response is possible for at least some respondents, an odd number of categories should be used 4. FORCED VS NON FORCED - In situations where the respondents are expected to have no opinion, the accuracy of the data may be improved by a non - forced scale 5. VERBAL DESCRIPTION - An argument can be made for labeling all or many scale categories. The category descriptions should be located as close to the response categories as possible 6. PHYSICAL FORM - A number of options should be tried and the best selected
Order of questions?
1. OPENING QUESTIONS - The opening questions should be interesting, simple, and non-threatening. - Type of Information. As a general guideline, basic information should be obtained first, followed by classification, and finally, identification information. BASIC: relating to your research CLASSIFICATION: demographics and socioeconomic characteristics IDENTIFICATION contact information (e.g., email, phone number DIFFICULT QUESTIONS - Difficult questions or questions which are sensitive, embarrassing, complex, or dull, should be placed late in the sequence. 2. LOGICAL ORDER - Questions should be asked in a logical order. 3. BRANCHING QUESTIONS - Direct respondents to different places in the questionnaire based on previous response. (For instance, "if you answered no to question 3, skip to question 10) - The question being branched [the one to which the respondent is being directed] should be placed as close as possible to the question causing the branching. - The branching questions should be ordered so that the respondents cannot anticipate what additional information will be required.
What are the different observation methods? Describe each and know examples.
1. PERSONAL OBSERVATION: - A researcher observes actual behavior as it occurs. - The observer does not attempt to manipulate the phenomenon being observed but merely records what takes place. - For example, a researcher might record traffic counts and observe traffic flows in a department store. 2. MECHINE OBSERVATION 1. Traffic Counters - Turnstiles - recording visitors - Video Cameras PHYSIOLOGICAL MEASUREMENT - RAS: activation is stimulated via a subcortical unit - EEG: electroencephalogram - GSR: galvanic skin response (perspiration = emotion and excitement) - FMRI - Pupilometer: pupil dilation - Voice Pitch Analysis: measures emotion - Response latency 3. BEHAVIOR MEASUREMENT - People Reader: Simultaneously records both the reading material and the readers eyes. Can also be used to measure for radio listening habits. - Rapid Analysis Measurement (RAMS): Hand-held device records respondents feelings by their turning a dial - Also called dial turning device - GPS Technology: Tracks motorist and pedestrian exposure to outdoor advertising - The People Meter: Used to measure national TV audiences that transmits demographic information overnight. Records not only WHAT people are watching but also WHO is watching. - The Internet: How often is a website visited? How much time is spent on a page? (This information can be tracked using "cookies" 4. AUDIT - The researcher collects data by examining physical records or performing inventory analysis. - Data are collected personally by the researcher. - The data are based upon counts, usually of physical objects. 5. CONTENT ANAYSIS - The objective, systematic, and quantitative description of the manifest content of a COMMUNICATION - Books, websites, artwork, letters etc... - The unit of analysis may be WORDS, CHARACTERS, (individuals or objects), THEMES (propositions), SPACE AND TIME MEASURES (length or duration of the message), or TOPICS (subject of the message). - Analytical categories for classifying the units are developed and the COMMUNICATION IS BROKEN DOWN according to prescribed rules. TRACE ANALYSIS - Data collection is based on PHYSICAL TRACES, OR EVIDENCE, OF PAST BEHAVIOR. - The selective erosion of tiles in a museum indexed by the replacement rate was used to determine the relative popularity of exhibits. - The number of different fingerprints on a page was used to gauge the readership of various advertisements in a magazine. - The position of the radio dials in cars brought in for service was used to estimate share of listening audience of various radio stations. - The age and condition of cars in a parking lot were used to assess the affluence of customers. - The magazines people donated to charity were used to determine people's favorite magazines. - Internet visitors leave traces which can be analyzed to examine browsing and usage behavior by using cookies. - WEB ANALYTICS AS OBSERVATION
How can you improve response rates?
1. PRIOR NOTIFICATION - "you will be receiving a survey" 2. MOTIVATING RESPONDENTS - Foot in the door (small request, then bigger), Door in the face (big request, than smaller). 3. INCENTIVES - e.g. $$$ 4. QUESTIONNAIRE DESIGN AND ADMIN - trained interviewers 5. FOLLOW Up - checking with non-respondents 6. OTHER - personal letters 7. CALL BACKS
What are the steps in the 'marketing research process'?
1. Problem Definition 2. Development of an approach to the problem 3. Research design formulation 4. Fieldwork or data collection 5. Data preparation and analysis 6. Report preparation and presentation
Characteristics and roles of good focus group moderators? (be able to recall textbook examples, lecture notes, and examples from the Mad Men clip you watched)
1. QUICKLY BUILD RAPPORT: Quickly build rapport: The moderator must quickly establish a connection with the participants and a feeling of trust. 2. KINDNESS WITH FIRMNESS: The moderator must combine a disciplined detachment with understanding empathy so as to generate the necessary interaction [don't answer your own questions!] 3. PERMISSIVENESS: The moderator must be permissive yet alert to signs that the group's cordiality or purpose is disintegrating [Keep it together & on track!] 4. INVOLVEMENT: The moderator must encourage and stimulate intense personal involvement [get people excited/involved!] 5. INCOMPLETE UNDERSTANDING: The moderator must encourage respondents to be more specific about generalized comments by exhibiting incomplete understanding [be curious!] 6. ENCOURAGEMENT: The moderator must encourage unresponsive members to participate [Make sure everyone talks!] 7. FLEXIBILITY: The moderator must be able to improvise and alter the planned outline amid the distractions of the group process [allow freedom of discussion!] 8.SENSITIVITY: The moderator must be sensitive enough to guide the group discussion at an intellectual as well as emotional level [Don't squash/ignore someone's comments]
How can you control extraneous variables?
1. RANDOMIZATION- random assignment of test units to experimental groups by using random numbers. Treatment conditions are also randomly assigned to experimental groups. 2. MATCHING - comparing test units on a set of key background variables before assigning them to the treatment conditions. 3. STATISTICAL CONTROLl -measuring the extraneous variables and adjusting for their effects through statistical analysis. 4. DESIGN CONTROL - involves the use of experiments designed to control specific extraneous variables.
Characteristics of observation research?
1. STRUCUTRED VS UNSTRUCTURED - Is researcher taking detailed notes or making more general observations 2. DISGUISED VS UNDISGUISED - Does the subject know the purpose of the research 3. NATURAL VS. CONTRIVED - Is the setting made up by the researcher or are you observing a naturally occurring event
How can you adjust for nonresponse?
1. SUBSAMPLING OF NONRESPONDENTS - contact a subsample of the nonrespondents 2. REPLACEMENT - replace nonrespondents in the current survey with nonrespondents from an earlier, similar survey 3. SUBSTITUTION - substitute nonrespondents with substitutes who are similar to nonrespondents 4. SUBJECT ESTIMATES - evaluate likely effects of nonresponse based on experience and available info 5. TREND ANALYSIS - examine trend between early and late respondents
What are the different types of survey methods?
1. TELEPHONE - Traditional telephone, computer assisted telephone interviewing 2. PERSONAL - In home, mail intercept, computer assisted personal interviewing 3. MAIL - Mail interview, mail panel 4. ELECTRONIC - E - mail, internet
What are the different types or variations of focus groups?
1. TWO WAY FOCUS GROUP: One target group listens and learns from a related group. E.g. A focus group of physicians view a focus group of arthritis patients discussing the treatment they desired 2. DUAL MODERATOR GROUP: A focus group conducted by two moderators: One moderator is responsible for the smooth flow of the session, and the other ensures that specific issues are discussed. 3. DUELING MODERATOR GROUP: There are two moderators, but they deliberately take opposite positions on the issues to be discussed [good cop / bad cop] 4. RESPONDENT MODERATOR GROUP - moderator asks selected participants to play the role of moderator temporarily to improve group dynamics. 5. CLIENT PARTICIPATION GROUP - Client personnel are identified and made part of the discussion group. 6. MINI GROUPS - These groups consist of a moderator and only 4 or 5 respondents. 7. TELESEEION GROUPS - Focus group sessions by phone using the conference call technique. 8. ONLINE FOCUS GROUPS - Focus groups conducted online over the Internet.
Advantages and disadvantages of focus groups?
ADVANTAGES 1. Synergism 2. Snowballing - one idea leads to another, which leads to another, and so on... 3. Stimulation 4. Security 5. Spontaneity 6. Serendipity 7. Specialization 8. Scientific scrutiny - observers can watch the research unfold and witness any potential bias or problems. 9. Structure - the structure of focus groups is flexible which allows for new ideas to be uncovered. 10. Speed DISADVANTAGES 1. Misuse 2. Misjudge 3. Moderation - it is hard to moderate groups and good moderators are rare. 4. Messy - the information from focus groups can feel chaotic and can be hard to organize and interpret. 5. Misrepresentation - it can be tempting to overstate the implications of focus group results. Results are not representative, rather focus groups explore and provide insights into how people think, feel, and behave.
What are the conditions for using observation?
CONDITIONS: - The information must be OBSERVABLE OR INFERABLE - The behavior must be REPETITIVE OR FREQUENT - The behavior must be RELATIVELY SHORT in duration
Advantages and disadvantages of projective techniques.
ADVANTAGES -They may elicit responses that subjects would be unwilling or unable to give if they knew the purpose of the study. -Helpful when the issues to be addressed are personal, sensitive, or SUBJECT TO STRONG SOCIAL NORMS -Helpful when UNDERLYING MOTIVATION, beliefs, and attitudes are operating at a SUBCONSCIOUS level. DISADVANTAGES -Suffer from many of the disadvantages of unstructured direct techniques, but to a greater extent. -Require highly-trained interviewers. -Skilled interpreters are also required to analyze the responses. -There is a serious risk of interpretation bias. -They tend to be expensive. -May require respondents to engage in unusual behavior.
Advantages and disadvantages of observation research?
ADVANTAGES of Observation Research - We can see what people actually do - Avoids interviewer bias - Quick/cheap data collection* - Some data can ONLY be collected using observation DISADVANTAGES of Observation Research - Researcher does not learn motives - Time-consuming and expensive* - May not be entirely accurate
What is the ACS? What type of information can be found in the ACS? How is the US Decennial Census different from the ACS?
AMERICAN COMMUNITY SURVEY ACS Purpose: to measure the changing social and economic characteristics of the U.S. population ACS -Designed to measure social and economic change (a moving image). -Collects and reports data annually. -Experienced researchers conduct nonresponse follow-up interviews. - Proxy interviews (with neighbors) not allowed. Smaller sample size than Decennial Long form DECENNIAL CENSUS - Designed to provide an official count of the population at a place in time (a snapshot). - Collects and reports data every 10 years. - Temporary researchers with less training. - Proxy interviews (with neighbors) allowed. - Long form has a larger sample size than ACS
What is the process of analysis of qualitative data?
ANALYSIS OF QUALITATIVE DATA: (FOCUS GROUPS) - Look for THEMES - THEMES are patterns across the data set - Qualitative ReporTs are typically narrative descriptions of the relevant THEMES 1. DATA REDUCTION - Select which aspects of the data are to be emphasized, minimized, or set aside for the project at hand. - This takes careful thought, keep an open mind 2. DATA DISPLAY - Develop a visual interpretation of the data with the use of such tools as a diagram, chart, or matrix. - The display helps to illuminate patterns and interrelationships in the data. - Do not use frequency information 3. CONCLUSION DRAWING AND VERIFICATION - Consider the meaning of analyzed data and assess its implications for the research question at hand.
Describe the research that took place in the article "Anthropology Inc."?
ARTICLE American drinking cultures and report back on the elusive phenomenon known as the "home party.
Describe applied and basic research?
Applied: To better understand the market Basic: To expand the frontiers of knowledge
CHAPTER 8/9 What is measurement?
Assigning numbers to CHARACTERISTICS s of objects, events, or people according to certain pre-specified RULES.
CHAPTER 11 What is the difference between a sample and a census?
CENSUS - Surveying the ENTIRE population of interest. - Costly and slow SAMPLE - A subgroup of the population selected for participation in the study. - Faster and cheaper than a census
What is the difference between a survey and a census?
CENSUS: A census collects information about every member of the population. - You can also think of it as a 100% sample survey. - Accurate and detailed - Costly and slow SURVEY: A survey is a data collection activity where only part of the population is selected (referred to as a sample of the population). -Not as accurate as a census - Faster and cheaper than a census
What are the types of comparative scales? Describe each, type of data obtained, their pros and cons, and a sample question.
COMPARATIVE VS NON COMPARATIVE SCALES COMPARATIVE SCALES - Measurement scales in which one object, concept, or person is COMPARED WITH ANOTHER ON A SCALE - Comparative scale data must be interpreted in relative terms and have only ORDINAL(IE. RANK) PROPERTIES. 1. PAIRED COMPARISON SCALE - A respondent is presented with two objects and asked to select one according to some criterion. It is the MOST WIDELY used comparative scaling technique. - The data obtained are ORDINAL in nature. Under the assumption of transitivity, it is possible to convert paired comparison data to a rank order. - Pros: less order bias. It is easy for people to select one item from a set of two than to rank a large set of objects. - Cons: Interviewee fatigue—with n brands, [n(n - 1) /2] paired comparisons are required. 2. RANK ORDER SCALE - Respondents are presented with several objects simultaneously and asked to order or rank them according to some criterion. - Pros: Instructions are easy to understand. - Cons: Possible that the respondent may dislike the brand ranked 1 in an absolute sense. Order bias may exist. Only produces ORDINAL data. 3. CONSTANT SUM SCALE - Respondents allocate a constant sum of units, such as 100 points, to attributes of a product to reflect their importance. - The number of points reflects both the rankings and the relative magnitude of each alternatives as perceived by the respondent. - If an attribute is unimportant, the respondent assigns it zero points. - Pros: Avoid long lists of paired items. Respondents are allowed to indicate equal value to two alternatives if they perceive so. - Cons: Respondent may have difficulty allocating the points to total 100 if there are a lot of items. Ten items is the upper limit.
What are nonprobability sampling techniques (i.e., convenience, judgmental, quota and snowball sampling)? Be able to describe/identify each technique.
CONVIENCE: Sample is selected based on the convenience of the researcher. Often, respondents are selected because they happen to be in the right place at the right time. JUDGMENTAL: Researcher chooses the sample elements because she or he believes they represent the population of interest QUOTA: May be viewed as two-stage judgment sample, first stage consists of developing control categories, or quotes of population elements. Second stage, sample elements are selected based on convenience or judgment SNOWBALL: Initial group of respondents is selected usually at random, after being interviewed these respondents are asked to identify other who belong to the target population of interest
What is the difference between correlation and causation?
CORRELATION - Non-directional relationship between two variables. - Increase in X is associated with Increase in Y, but could also be stated as Increase in Y is associated with increase in X. - In other words, X and Y appear to be related, but we do not know if one causes the other. CAUSATION - Directional relationship between at least two variables. - Increase in X leads to increase in Y, but reverse may not be true.
What is the confidence interval?
Confidence Interval: range into which the true population parameter will fall, assuming a given level of confidence - Based on the construction of confidence intervals around the sample mean or proportion using the standard error formula - Calculating the confidence interval involves determining a distance above and below the population mean which contains a specified area of the normal curve
Know experimental notation.
Definition of Symbols X = the exposure of a group to an independent variable or treatment. 0 = observation or measurement of the dependent variables on the test units. R = the random assignment of test units to separate treatment.
Describe cross-sectional and longitudinal designs. Know and understand examples. What are the advantages and disadvantages of each?
Descriptive research may be either cross-sectional or longitudinal. Cross-Sectional Design - information collected from a sample population only ONCE at ONE moment in time - Multiple cross-secitonal design: two or more samples of respondents info obtained once Longitudinal Design - OVER time Information collected repeatedly from the same variable from the SAME sample over time Advantages & Disadvantages - Sample measured repeatedly - Not done enough - Expensive and complicated
CHAPTER 6 What is ethnography and participant-observation? How and why is it used in marketing research?
ETHNOGRAPHY: the scientific description of the customs of individual peoples and cultures PARTICIPANT - OBSERVATION - Naïve (childlike) observation can provide novel insight - Deeply embedded customer research - Taking users' perspective - Living with families - The researcher participates in activities with the research subjects (e.g., attend parties and BBQs, go shopping together, do ride-alongs) - Recording product usage Ethnography provides a "deep" understanding of people's motives and behaviors that other methods of research cannot capture.
Explain an experimental design?
EXPERIMENTAL DESIGN- a set of procedures specifying: 1. Sample & Assignment - test units and how these units are to be divided into homogeneous subsamples 2. How independent variables or treatments are to be manipulated 3. The dependent variable(s) to be measured 4. How the extraneous variables will be controlled
Why might a respondent be unwilling to answer a question?
Effort required of the respondent Legitimate purpose Sensitive information
What is ethnographic research?
Ethnographic research refers to open or disguised observation in a natural setting. It is typically intended to understand the cultural and symbolic meanings within a specific group of people. - Ethnographic Research - From (cultural) anthropology - Records people in their natural settings - Observation of behavior and physical setting coupled with unstructured interviews - Primary data collection method is: Participant-Observation - Embedded researchers
What are focus groups? # of participants? Setting?
FOCUS GROUPS = guided discussion with appropriate target market in an informal setting, to gain new impressions - 8 - 12 Participants - Pre-Screened [homogenous, similar market segment] - Relatively Informal, Relaxed Setting - 1 - 3hrs [with breaks] - Record [video & audio] - Guided by moderator - Observers [on other side of one-way glass, or remote]
Describe the various types of response errors?
From the researcher: - Surrogate information error - Measurement error - Population definition error - Sampling frame error - Data analysis error From the interviewer: - Cheating error - Questioning error - Recording error - Respondent selection error From the respondent: - Inability to answer - Unwillingness to answer (types of error in research under non-sampling error)
Can an unreliable measure be valid? Can an invalid measure be reliable?
HIGLY RELIABLE AND VALID HIGHLY RELIABLE BUT NOT VALID NEITHER RELIABLE NOR VALID
What is internal validity? External validity? What is necessary for a cause and effect inference?
INTERNAL VALIDITY - Refers to whether the manipulation of the independent variables or TREATMENTS ACTUALLY CAUSE THE OBSERVED EFFECTS on the dependent variables. - Control of extraneous variables is a necessary condition for establishing internal validity. - Did my manipulation produce the effects, or was it something else? EXTERNAL VALIDITY - Refers to whether the cause-and-effect relationships found in the experiment can be GENERALIZED. - To what populations, settings, times, independent variables, and dependent variables can the results be projected?
CHAPTER 10 What makes a good questionnaire?
INTERVIEW METHOD QUESTION CONTENT ABILITY AND WILLINGNESS TO ANSWER QUESTION STRUCTURE QUESTION WORDING ORDER OF QUESTIONS FORM AND LAYOUT QUESTIONNARIE PRE TESTING
What are ethical issues in marketing research? What is the Belmont Report?
If the researcher does not follow appropriate marketing research procedure, or if the client misrepresents the finding in the company's advertising, ethical norms are violated. The Belmont Report established principles and guidelines for protecting human research subjects. Among those principles are: respect for persons, beneficence, and justice.
Why might it be helpful to use data from different sources? What is this called?
In the social sciences, researchers often use "triangulation" to confirm results. Triangulation Defined: Using more than one research method in order to check results
How does the method influence questionnaire design?
Interviewer Administered Self- administered Computer assisted
Why might a respondent be unable to answer a question?
Is respondent informed? Can the respondent remember? Can the respondent articulate?
Describe the management vs. marketing research problem.
Management Research Problem •Action oriented •Broad and general •What are the symptoms? •What does the DM need to do? -Should a new product be introduced? -Should the advertising campaign be changed? -Should the price of the brand be increased? Marketing Research Problem •Information oriented •Narrow and specific •What is causing this problem? •What info is needed and how can we find it? -To determine consumer preferences and purchase intentions for the proposed new product - To determine the effectiveness of the current advertising campaign -To determine the price elasticity of demand and the impact on sales
What is marketing research? How is marketing research defined by the AMA?
Marketing Research: is the systematic and objective identification, collection, analysis, dissemination, and use of information for the purpose of improving decision making related to the identification and solution of problems and opportunities in marketing AMA: The function which links consumer, customer, and public to the marketer through information
3. What mistakes can be made in defining the research problem. How can you avoid them?
Mistakes: 1. Defining the research problem too: Broadly - not actionable Example: "how can we improve the company's image" 2.Narrowly - eliminating interesting options Example: "which of these options should we pursue?" maybe none of them make sense 3. A Goldilocks Problem... not too narrow, not too broad just right How to Avoid: To avoid both issues it is recommended to create a BROAD STATEMENT then create SPECIFIC COMPONENTS to help define key aspects of the problem
What conditions favor the use of a sample? Of a census?
N/A
What are the types of measurement scales? Define, know characteristics, examples, and general statistical capabilities.
NOMINAL - numbers assigned to runner - Numbers serve only as LABELS OR TAGS - These numbers do not reflect the amount of characteristics possessed by the objects ORDINAL - rank orders of winners - A RANKING SCALE that indicates relative position, not the magnitude of the differences between objects. Maintains labeling characteristics of nominal scales. - Used to measure the order of consumer's preferences INTERVAL -performance rating on a 0 to 10 scale - Have the characteristics of ordinal scales, plus EQUAL INTERVALS between points. - In marketing research, attitudes, motivations, and emotions are variables measured on an interval scale. Equal intervals are normally assumed in these measures. RATIO - Time to finish in seconds - Possesses all the properties of the nominal, ordinal, and interval scales plus has a MEANINGFUL ZERO point.
What are the types of noncomparative scales? Describe each, type of data obtained, their pros and cons, and a sample question.
NONCOMPARATIVE SCALES - Respondents evaluate only one object at a time, and for this reason non-comparative scales are often referred to as monadic scales. -Non-comparative techniques consist of continuous and itemized rating scales. 1. CONTINTUOSOUS RATING SCALES - Respondents rate the objects by placing a mark on a graphic continuum anchored by two extremes. - Once the respondent has provided the ratings, the researcher divides the line into as many categories as desired and assigns scores. - This type of scale produces interval data. - Pros: Easy to construct. It can be easily implemented on an Internet based survey. -Cons: Scoring graphic scale can be cumbersome and unreliable if using paper and pencil questionnaire. Historically has had limited use in marketing research. 2. ITEMIZED RATING SCALES STAPEL SCALE - Itemized rating scales have a limited number of ordered categories with brief descriptions associated with each category. - The respondents are required to select the specified category that best describes the object being rated. - The commonly used itemized rating scales in market research are the: 1. LIKERT (most popular) - Respondents are asked to indicate a level of agreement or disagreement with each of a series of statements 2. SEMANTIC differential - The semantic differential scale is a seven-point rating scale* with end points associated with bipolar adjective labels. - Pros: Sufficient reliability, validity, and statistical robustness when applied to corporate image research. - Widely used in comparing brand, product, and company images. - Cons: Lack of standardization; the scale must be adapted for each research problem. - Halo effect: the rating of a specific attribute may be dominated by the interviewee's overall impression of the concept being rated. 3. STAPEL SCALE (least popular)
When would you use nonprobability sampling (focus groups)? When would you use probability sampling (surveys and research requiring highly accurate estimates)?
Non probability sampling - does not use chance for sampling but rather relies on the judgment of the researcher Probability sampling- sampling units are selected by chance
CHAPTER 7 What is the ordinary meaning of causality? How is it different from the scientific meaning?
ORDINARY MEANING 1. X is the only cause of Y 2. X must always lead to Y (X is a deterministic cause of Y) 3. It is possible to prove that X is a cause of Y SCIENTIFIC MEANING 1. X is only one of a number of possible causes of Y 2. The occurrence of X makes the occurrence of Y more probable ( X is probabilistic cause of Y) 3. We can never prove that X is a cause of Y. At best, we can infer that X is a cause of Y.
What is observation?
Observation Research DEFINITION: The systematic recording of patterns of occurrence or behaviors
CHAPTER 12 What are the basic statistical definitions and symbols commonly used in sampling?
PARAMETER: - measure of the target population - the true value which would be obtained if a census rather than a sample was undertaken. STATISTIC: - measure of the sample - used as an estimate of the population parameter. FINITE POPULATION CORRECTION: - The finite population correction (fpc) is a correction for overestimation of the variance of a population parameter, e.g., a mean or proportion, when the sample size is 10% or more of the population size. PRECISION LEVEL: When estimating a population parameter by using a sample statistic, the precision level is the desired size of the estimating interval. This is the maximum permissible difference between the sample statistic and the population parameter. CONFIDENCE INTERVAL: - The confidence interval is the range into which the true population parameter will fall, assuming a given level of confidence. CONFIDENCE LEVEL: - The confidence level is the probability that a confidence interval will include the population parameter.
Identify and describe the types of pre-experimental designs, true experimental designs, quasi-experimental designs, and statistical designs.
PRE EXPERIMENTAL DESIGNS: do not involve randomization. 1. One-Shot Case Study 2. One-Group Pretest-Posttest 3. Static Group TRUE EXPERIMENTAL DESIGNS: involve randomization. 1. Pretest-Posttest Control Group 2. Posttest Only Control Group 3. Solomon Four-Group (expensive and time-consuming; not typically used in marketing research) QUASI - EXPERIMENTAL DESIGNS: - Can control when measurements are taken and on whom they are taken - Lacks control over the scheduling of treatments - Unable to expose test units to treatments randomly 1. Time Series 2. Multiple Time Series STATISTICAL DESIGNS: consist of a series of basic experiments that allow for statistical control and analysis of external variables and offer the following advantages: - The effects of more than one independent variable can be measured. - Specific extraneous variables can be statistically controlled. - Economical designs can be formulated when each test unit is measured more than once. 1. Randomized block design 2. Latin square design 3. Factorial design.
What are projective techniques? Purpose? Techniques? Examples and explanation of each technique?
PROJECTIVE TECHNIQUES - Unstructured, indirect form of questioning that encourages respondents to project their UNDERLYING motivations, beliefs, attitudes or feelings regarding the issues of concern. - In projective techniques, respondents are asked to interpret image/scenario or the behavior of others. - In interpreting the image/scenario/behavior, respondents indirectly project their own motivations, beliefs, attitudes, or feelings into the situation. WORD ASSOCIATION - Respondents are presented with a list of words, one at a time, and asked to respond to each with the first word that comes to mind. - Test words & neutral words are interspersed throughout out the list RESPONSES ARE ANALYZED BY CALCULATING: 1. The frequency with which any word is given as a response [e.g. Buick Old] 2. Response Time 3. Number of no (or late) responses to test words SENTENCE COMPLETION - Respondents are given incomplete sentences and asked to complete them. Generally, they are asked to use the first word or phrase that comes to mind. STORY COMPLETION - Participants are given part of a story - enough to direct attention to a particular topic but not to hint at the ending. They are required to give the conclusion in their own words. PICTURE RESPONSE - The respondents are asked to describe a series of pictures of events. The respondent's interpretation of the pictures gives indications of that individual's personality. CARTOON RESPONSE - Cartoon characters are shown in a specific situation related to the problem. The respondents are asked to indicate what one cartoon character might say in response to the comments of another character. Cartoon tests are simpler to administer and analyze than picture response techniques. EXPRESSIVE TECHNIQUES - Participants are presented with a verbal or visual situation and asked to relate the feelings and attitudes of other people to the situation. ROLE PLAYING - Participants are asked to play the role or assume the behavior of someone else. THIRD - PERSON TECHNIQUE - The participant is presented with a verbal or visual situation and the respondent is asked to relate the beliefs and attitudes of a third person rather than directly expressing personal beliefs and attitudes. This third person may be a friend, neighbor, colleague, or a "typical" person.
What are the differences between primary data and secondary data? How might each be helpful to you as a marketing researcher?
Primary Data: data that are originated by a researcher for the SPECIFIC PURPOSE of addressing the problem at hand Benefits: Designed for the unique research needs at present Drawbacks: Expensive, time consuming, can be complex Secondary Data: data that have been collected for purpose OTHER THAN the problem at hand Benefits: Fast, easy to obtain, low cost Drawbacks: Not specific to the research need at hand
What are the pros/cons of probability sampling?
Pro: Easily understood, results projectable Con: Difficult to construct sampling frame, expensive, lower precision
What are the pros/cons of nonprobability sampling
Pro: Less expensive, least time consuming, most conivente Con: Selection bias, sample not representative,
What is problem definition? How and why is it important?
Problem Definition: A broad statement of the general problem and identification of the specific components of the marketing research problem. (management decision and marketing research problem) Problem Definition is the most critical step in a market research project -Only when the marketing research problem has been clearly defined can research be designed and conducted properly. -All the effort, time, and money spent from this point on will be wasted if the problem is misunderstood or ill defined -Incorrect problem definition leads to incorrect or irrelevant findings, which may bias managerial decision making.
What are the types of marketing research?
Problem Identification Research: is undertaken to help identify problems that are perhaps, not apparent on the surface and yet exist or are likely to arise in the future. (Examples: market potential, share, characteristics, sales analysis, forecasting, business trends) Problem Solving Research: is undertaken to help solve specific marketing problems. (Examples: segmentation, product, pricing, promotion, distribution)
CHAPTER 5 Compare and contrast qualitative and quantitative research.
QUALITATIVE RESEARCH: Characteristic based 1. OBJECTIVE: To gain a qualitative understanding of the underlying reasons and motivations 2. SAMPLE: Small number of non-representative cases 3. DATA COLLECTION: Unstructured 4. DATA ANALYSIS: Non-statistical 5. OUTCOME: Develop an initial understanding QUANTITATIVE RESEARCH: Number/fact based 1. OBJECTIVE:To quantify the data and generalize the results from the sample to the population of interest 2. SAMPLE: Large number of representative cases 3. DATA COLLECTION: Structured 4. DATA ANAYSIS:Statistical 5. OUTCOME: Recommend a final course of action
What is measurement reliability? How do we test measurement reliability?
RELIABILITY: can be defined as the extent to which measures are free from random error. The 3 approaches for assessing reliability are: 1. Test-Retest Reliability: - Respondents are administered identical sets of scale items at two different times under as nearly equivalent conditions as possible. The degree of similarity between the two measurements is determined. 2. Equivalent Form Reliability: - Two equivalent forms of the scale are constructed and the same respondents are measured with both forms at the same time. The correlation between the two measurements is assessed. 3. Internal Consistency Reliability: determines the extent to which different parts of a summated scale are consistent in what they indicate about the characteristic being measured. Split-Half Correlations - the items on the scale are divided into two halves and the resulting half scores are correlated. Coefficient alpha (Cronbach's alpha) - the average of all possible split-half coefficients resulting from different ways of splitting the scale items. This coefficient varies from 0 to 1, and a value of 0.6 or less generally indicates unsatisfactory internal consistency reliability.
What is a 'response rate' and how do you calculate it?
RESPONSE/ COMPLETION RATE The number of people who completed the interview/survey divided by the number of people in the sample. Accounts for refusals and is usually expressed as a percentage. Response Rate = Number of completed interviews/ Number of Eligible Units in Sample
What are the sources of error in research?
Random sampling error and non-sampling error
Differentiate and describe random sampling error vs. non-sampling error. Which is more problematic and why?
Random sampling error: happens because the particular sample is an imperfect representation of the population. Non-sampling error: error caused by the researcher (more problematic)
What do we mean when we talk about sampling distribution, statistical inference, and standard error?
SAMPLING DISTRIBUTION - DISTRIBUTION VALUES of a sample statistic computed for ALL POSSIBLE SAMPLES that could be drawn from target population - e.g., in practice, we draw a random sample of 5 students from a population of 20 students - BUT 15,504 different samples of 5 could be drawn The relative frequency distributions of the values of the mean of these 15,504 different samples is the sampling distribution of the mean STATISTICAL INFERENCE - Generalizing the sample results to the population - In practice, a single sample is selected and sample statistics are calculated - Hypothetically, to estimate the population parameter from the sample, every possible sample should be examined (i.e., sampling distribution) - Allows us to use probability theory to make inferences about the population
What are probability sampling techniques (i.e., simple random, systematic, stratified, and cluster sampling)? Be able to describe/identify each technique.
SIMPLE RANDOM: - Each element in the population has a known and equal probability of selection. - Each possible sample of a given size (n) has a known and equal probability of being the sample actually selected. - Every element is selected independently SYSTEMATIC: - The sample is chosen by selecting a random starting point and then picking every nth element in succession from the sampling frame STRATIFIED: - A two-step process: Divide the original population into homogeneous, mutually exclusive, and exhaustive subsets CLUSTER SAMPLING: - Divide the target population into mutually exclusive and collectively exhaustive cluster, select a random sample of clusters based on probability same line, for each cluster either include all the elements of a random sample of elements.
What factors should you consider in evaluating survey methods?
TASK FACTORS 1. DIVERSITY OF QUESTIONS AND FLEXIBILITY - Can the respondent interact with the interviewer and the survey questionnaire? Can the respondent ask clarifying questions? 2. USE OF PHYSICAL STIMULI - Physical stimuli include taste tests, a product prototype, commercials, or promotional displays. 3. SAMPLE CONTORL - The ability to reach your target population. For example, with a mail survey, you do not actually know who has completed your questionnaire, therefore mail surveys have low sample control. 4. QUANTITY OF DATA - How much data can you collect? How much time is a respondent willing to spend on your questionnaire? 5. RESPONSE RATE - The percentage of the total attempted interviews that are completed. SITUATIONAL FACTORS 1. DATA COLLECTION ENVIRONMENT - How much control does the researcher have over the environment in which the respondent answers the questionnaire? 2. FIELD FORCE - The ability to control the interviewers and supervisors involved in data collection. 3. INTERVIEWER BIAS - Have you ever been approached by an interviewer at a mall and asked to fill out a questionnaire? If the interviewer wants to get to lunch, he/she might encourage you to "hurry" through the questionnaire or skip "unimportant" sections. Yep. It happens all the time. This would be a form interviewer bias. 4. SPEED - Mail surveys can take months to administer. Internet surveys can occur in a matter of days with results immediately available. 5. COST - $$$$$$ RESPONDENT FACTORS 1. PERCEIVED ANONYMITY: - In-person surveys has LOW perceived anonymity because the researcher is present. Mail and internet surveys have HIGH perceived anonymity. 2. SOCAIL DESIRABILITY/ SENSITIVE INFORMATION - Respondents tend to give answers that are socially acceptable, whether or not they are true. 3. LOW INCIDENCE RATE - How many people are actually eligible for the study? For example, a survey calling for a sample of males, ages 18-20 who drink tea at least 5 times a week will likely have a low incidence rate which would make the research impossible to implement. 4. RESPONDENT CONTROLl - Surveys that allow respondents more control will tend to have higher response rates. Can respondents answer WHEN it is convenient for them? Can they start the questionnaire and finish it later?
What is validity? What are the various types of validity? How do we assess validity?
The validity of a scale may be defined as the extent to which differences in observed scale scores reflect true differences among objects on the characteristic being measured, rather than systematic or random error. Perfect validity requires that there be no measurement error. 1. Content (face) Validity: The degree to which a measurement seems to measure what it is supposed to measure, as judged by researchers - Aids in common-sense interpretations of scales. - Because it is subjective, content validity must be used with other validity tests. - Does the scale provide adequate coverage of the topic under study? - Systematic efforts including exhaustive literature review, focus groups, and expert panels to help determine content validity. 2. Criterion Validity 3. Construct Validity: Criterion validity reflects whether a scale performs as expected in relation to other variables selected (criterion variables) as meaningful criteria. - Addresses the question of what construct or characteristic the scale is, in fact, measuring. Convergent validity: is the extent to which the scale correlates positively with other measures of the same construct. Discriminant (divergent) validitY: is the extent to which a measure does not correlate with other constructs from which it is supposed to differ. Nomological validity: is the extent to which the scale correlates in theoretically predicted ways with measures of different but related constructs.
What is the purpose of causal research? Methods?
Type of research where the main objective is to obtain evidence regarding a CAUSE AND EFFECT relationship - Experimentation - Quasi-experiments
What are the various question structures and when and why would you use them?
UNSTRUCTURED s: are open-ended questions that respondents answer in their own words. - Good as first question - Recording error, difficult data coding, limited value in self - administered survey STRUCTURED: specify the set of response alternatives and the response format. - Multiple choice, yes or no - Easy to code and analyze - Reduce respondents effort DICHOTOMOUS - Has only two response alternatives: yes or no, agree or disagree, and so on. The two alternatives of interest are supplemented by a neutral alternative, such as "no opinion," "don't know," "both," or "none." - Wording can bias the responses SCALE (e.g., Strongly agree, agree, neither agree nor disagree, disagree, strongly disagree) - Easy to code and analyze - Reduce respondents effort
What is the US Census? How is US Census data used/collected?
US CENSUS: A census collects information about every member of the population. USES - Apportioning the representatives within the House (435) -Every state gets 1 and representative. The remainder are based on population e.g., Oregon (5), California (53), Idaho (2), North Dakota (1) - Distribute federal, state , local, and tribal funds - Draw state legislative districts - Evaluate success of programs or identify populations in need
Compare and contrast focus groups with depth interviews.
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What meaning is more appropriate for marketing research?
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