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Introduction to Marketing ResearchBy Sanjay Kumar
Redefining Marketing Research The American Marketing Association
(AMA) redefined Marketing Research as:
The function which links the consumer, the
customer, and public to the marketer
through INFORMATION
Used to identify and define market opportunities and problems
Generate, refine, and evaluate marketing performance
Monitor marketing performance
Improve understanding of marketing as a process
Redefining Marketing Research
Definition of Marketing ResearchMarketing 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.
A Classification of Marketing Research
Marketing Research
Problem Identification Research
Problem Solving Research
Market Potential ResearchMarket Share ResearchMarket Characteristics ResearchSales Analysis ResearchForecasting ResearchBusiness Trends Research
Segmentation Research
Product Research
Promotion Research
Distribution Research
Fig 1.1
Marketing Research Process
Step 1: Problem Definition
Step 2: Development of an Approach to the Problem
Step 3: Research Design Formulation
Step 4: Fieldwork or Data Collection
Step 5: Data Preparation and Analysis
Step 6: Report Preparation and Presentation
The Role of Marketing Research
ControllableMarketing
•Product
•Pricing
•Promotion
•Distribution
Variables
Marketing Research
MarketingDecisionMaking
ProvidingInformation
AssessingInformationNeeds
Marketing Managers
• Market Segmentation
• Performance & Control
• Target Market Selection• Marketing Programs
UncontrollableEnvironmentalFactors
•Economy
•Technology
•Laws & Regulations
•Social & Cultural Factors
•Political Factors
Customer Groups
• Employees• Shareholders
Suppliers•
• Consumers
Fig 1.2
The Dept. Store ProjectThe following information was solicited:1. Familiarity with the ten department stores.2. Frequency with which household members shopped at each
of the ten stores.3. Relative importance attached to each of the eight factors of
the choice criteria. 4. Evaluation of the ten stores on each of the eight factors of the
choice criteria.5. Preference ratings for each store.6. Rankings of the ten stores (from most preferred to least
preferred).7. Degree of agreement with 21 lifestyle statements.8. Standard demographic characteristics (age, education, etc.)9. Name, address, and telephone number.
Research Design
A Classification of Marketing Research Designs
Single Cross-Sectional Design
Multiple Cross-Sectional Design
Fig. 3.1
Research Design
Conclusive Research Design
Exploratory Research Design
Descriptive Research
Causal Research
Cross-Sectional Design
Longitudinal Design
Potential Sources of Error inResearch Designs
Surrogate Information Error
Measurement Error
Population Definition Error
Sampling Frame Error
Data Analysis Error
Respondent Selection Error
Questioning Error
Recording Error
Cheating Error
Inability Error
Unwillingness Error
Fig. 3.2Total Error
Non-sampling Error
Random Sampling Error
Non-response Error
Response Error
Interviewer Error
Respondent Error
Researcher Error
Exploratory Research Design:Secondary Data
A Classification of Secondary Data
Secondary Data
Ready to Use Requires Further Processing
PublishedMaterials
Computerized Databases
Syndicated Services
Fig. 4.1
Internal External
A Classification of Published Secondary Sources
StatisticalData
Guides Directories Indexes Census Data
Other Government Publications
Fig. 4.2
Published Secondary Data
General Business Sources Government Sources
A Classification of Computerized Databases
Bibliographic Databases
Numeric Databases
Full-Text DatabasesDirectory Databases
Special-Purpose Databases
Fig. 4.3
Computerized Databases
Online Off-LineInternet
A Classification of Syndicated Services
Unit ofMeasurement
Fig. 4.4
Households/Consumers Institutions
Syndicated Services: ConsumersFig. 4.4 cont.
Psychographic& Lifestyles General
AdvertisingEvaluation
Households / Consumers
Scanner Diary Panels with Cable TV
Surveys Volume Tracking Data
Scanner Diary Panels
Electronic scanner servicesPurchase Media
Panels
International Organizations
Government Sources
Nongovernment Sources Governments
Trade Associations
A Classification of International SourcesFig. 4.5
Domestic Organizations in the United States
International Organizations in the United States
Organizations in Foreign Countries
International Secondary Data
Exploratory Research Design:Qualitative Research
A Classification of Marketing Research Data
Survey Data
Observational and Other Data
Experimental Data
Fig. 5.1
Qualitative Data Quantitative Data
Descriptive Causal
Marketing Research Data
Secondary Data Primary Data
A Classification of Qualitative Research Procedures
Association Techniques
Completion Techniques
Construction Techniques
Expressive Techniques
Fig. 5.2
Direct (Non disguised) Indirect (Disguised)
Focus Groups Depth Interviews
Projective Techniques
Qualitative Research Procedures
Completion TechniquesIn 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.
A person who shops at Big Bazaar is ______________________
A person who receives a gift certificate good for Videocon Gift vocher would be __________________________________
Kellogg’s corn flakes is most liked by _________________________
When I think of shopping in a department store, I ________
A variation of sentence completion is paragraph completion, in which the respondent completes a paragraph beginning with the stimulus phrase.
Completion Techniques
In story completion, respondents 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.
Construction Techniques
With a picture response, the respondents are asked to describe a series of pictures of ordinary as well as unusual events. The respondent's interpretation of the pictures gives indications of that individual's personality.
In cartoon tests, 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 TechniquesIn expressive techniques, respondents are presented with a verbal or visual situation and asked to relate the feelings and attitudes of other people to the situation.
Role playing Respondents are asked to play the role or assume the behavior of someone else.
Third-person technique The respondent 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.
Descriptive Research Design: Survey and Observation
A Classification of Survey Methods
Traditional Telephone
Computer-Assisted Telephone Interviewing
Mail Interview Mail Panel
Fig. 6.1
In-Home Mall Intercept Computer-Assisted Personal Interviewing
E-mail Internet
Survey Methods
Telephone Personal Mail Electronic
A Classification of Observation Methods
Observation Methods
Personal Observation
Mechanical Observation
Trace Analysis
Content Analysis
Audit
Fig. 6.3
Classifying
Observation
Methods
Causal Research Design:Experimentation
Experimental Design
An experimental design is a set of procedures specifying
– the test units and how these units are to be divided into homogeneous subsamples,
– what independent variables or treatments are to be manipulated,
– what dependent variables are to be measured, and
– how the extraneous variables are to be controlled.
Validity in Experimentation
• Internal validity refers to whether the manipulation of the independent variables or treatments actually caused the observed effects on the dependent variables. Control of extraneous variables is a necessary condition for establishing internal validity.
• 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?
Extraneous Variables
• History refers to specific events that are external to the experiment but occur at the same time as the experiment.
• Maturation (MA) refers to changes in the test units themselves that occur with the passage of time.
• Testing effects are caused by the process of experimentation. Typically, these are the effects on the experiment of taking a measure on the dependent variable before and after the presentation of the treatment.
• The main testing effect (MT) occurs when a prior observation affects a latter observation.
Extraneous Variables• In the interactive testing effect (IT), a prior measurement
affects the test unit's response to the independent variable. • Instrumentation (I) refers to changes in the measuring
instrument, in the observers or in the scores themselves. • Statistical regression effects (SR) occur when test units with
extreme scores move closer to the average score during the course of the experiment.
• Selection bias (SB) refers to the improper assignment of test units to treatment conditions.
• Mortality (MO) refers to the loss of test units while the experiment is in progress.
Controlling Extraneous Variables• Randomization refers to the random assignment of test units
to experimental groups by using random numbers. Treatment conditions are also randomly assigned to experimental groups.
• Matching involves comparing test units on a set of key background variables before assigning them to the treatment conditions.
• Statistical control involves measuring the extraneous variables and adjusting for their effects through statistical analysis.
• Design control involves the use of experiments designed to control specific extraneous variables.
A Classification of Experimental Designs
Pre-experimental
One-Shot Case Study
One Group Pretest-Posttest
Static Group
True Experimental
Pretest-Posttest Control Group
Posttest: Only Control Group
Solomon Four-Group
Quasi Experimental
Time Series
Multiple Time Series
Statistical
Randomized Blocks
Latin Square
Factorial Design
Figure 7.1
Experimental Designs
One-Shot Case Study
X 01
• A single group of test units is exposed to a treatment X.
• A single measurement on the dependent variable is taken (01).
• There is no random assignment of test units. • The one-shot case study is more appropriate for
exploratory than for conclusive research.
One-Group Pretest-Posttest Design
01 X 02
• A group of test units is measured twice. • There is no control group. • The treatment effect is computed as
02 – 01.• The validity of this conclusion is questionable
since extraneous variables are largely uncontrolled.
Static Group Design
EG: X 01
CG: 02
• A two-group experimental design. • The experimental group (EG) is exposed to the
treatment, and the control group (CG) is not. • Measurements on both groups are made only after the
treatment.• Test units are not assigned at random. • The treatment effect would be measured as 01 - 02.
True Experimental Designs: Pretest-Posttest Control Group Design
EG:R 01 X 02
CG: R 03 04
• Test units are randomly assigned to either the experimental or the control group.
• A pretreatment measure is taken on each group. • The treatment effect (TE) is measured as:(02 - 01) - (04 - 03). • Selection bias is eliminated by randomization. • The other extraneous effects are controlled as follows:
02 – 01= TE + H + MA + MT + IT + I + SR + MO04 – 03= H + MA + MT + I + SR + MO= EV (Extraneous Variables)
• The experimental result is obtained by:(02 - 01) - (04 - 03) = TE + IT
• Interactive testing effect is not controlled.
Posttest-Only Control Group Design
EG : R X 01
CG : R 02
• The treatment effect is obtained byTE = 01 - 02
• Except for pre-measurement, the implementation of this design is very similar to that of the pretest-posttest control group design.
Quasi-Experimental Designs: Time Series Design
01 02 03 04 05 X 06 07 08 09 010
• There is no randomization of test units to treatments.
• The timing of treatment presentation, as well as which test units are exposed to the treatment, may not be within the researcher's control.
Multiple Time Series Design
EG : 01 02 03 04 05 X 06 07 08 09 010
CG : 01 02 03 04 05 06 07 08 09 010
• If the control group is carefully selected, this design can be an improvement over the simple time series experiment.
• Can test the treatment effect twice: against the pretreatment measurements in the experimental group and against the control group.
Statistical DesignsStatistical 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.
The most common statistical designs are the randomized block design, the Latin square design, and the factorial design.
Randomized Block Design
• Is useful when there is only one major external variable, such as store size, that might influence the dependent variable.
• The test units are blocked, or grouped, on the basis of the external variable.
• By blocking, the researcher ensures that the various experimental and control groups are matched closely on the external variable.
Randomized Block Design
Treatment Groups Block Store Commercial Commercial Commercial Number Patronage A B C 1 Heavy A B C 2 Medium A B C 3 Low A B C 4 None A B C
Table 7.4
Latin Square Design• Allows the researcher to statistically control two noninteracting external
variables as well as to manipulate the independent variable. • Each external or blocking variable is divided into an equal number of
blocks, or levels. • The independent variable is also divided into the same number of levels. • A Latin square is conceptualized as a table (see Table 7.5), with the rows
and columns representing the blocks in the two external variables. • The levels of the independent variable are assigned to the cells in the
table. • The assignment rule is that each level of the independent variable should
appear only once in each row and each column, as shown in Table 7.5.
Latin Square DesignTable 7.5
Interest in the Store Store Patronage High Medium Low
Heavy B A C Medium C B A Low and none A C B
Factorial Design
• Is used to measure the effects of two or more independent variables at various levels.
• A factorial design may also be conceptualized as a table.
• In a two-factor design, each level of one variable represents a row and each level of another variable represents a column.
Factorial DesignTable 7.6
Amount of Humor Amount of Store No Medium High Information Humor Humor Humor
Low A B C Medium D E FHigh G H I
Laboratory versus Field Experiments
Factor Laboratory Field
Environment Artificial RealisticControl High Low Reactive Error High Low Demand Artifacts High Low Internal Validity High LowExternal Validity Low HighTime Short LongNumber of Units Small LargeEase of Implementation High Low Cost Low High
Table 7.7
Limitations of Experimentation• Experiments can be time consuming, particularly if the
researcher is interested in measuring the long-term effects.
• Experiments are often expensive. The requirements of experimental group, control group, and multiple measurements significantly add to the cost of research.
• Experiments can be difficult to administer. It may be impossible to control for the effects of the extraneous variables, particularly in a field environment.
• Competitors may deliberately contaminate the results of a field experiment.
Measurement and Scaling: Fundamentals and Comparative
Scaling
7 38
Primary Scales of MeasurementScaleNominal Numbers
Assigned to Runners
Ordinal Rank Orderof Winners
Interval PerformanceRating on a
0 to 10 Scale
Ratio Time to Finish, in
Seconds
Figure 8.1
Thirdplace
Secondplace
Firstplace
Finish
Finish
8.2 9.1 9.6
15.2 14.1 13.4
Primary Scales of MeasurementTable 8.1
Scale Basic Characteristics
Common Examples
Marketing Examples
Nominal Numbers identify & classify objects
Social Security nos., numbering of football players
Brand nos., store types
Percentages, mode
Chi-square, binomial test
Ordinal Nos. indicate the relative positions of objects but not the magnitude of differences between them
Quality rankings, rankings of teams in a tournament
Preference rankings, market position, social class
Percentile, median
Rank-order correlation, Friedman ANOVA
Ratio Zero point is fixed, ratios of scale values can be compared
Length, weight Age, sales, income, costs
Geometric mean, harmonic mean
Coefficient of variation
Permissible Statistics Descriptive Inferential
Interval Differences between objects
Temperature (Fahrenheit)
Attitudes, opinions, index
Range, mean, standard
Product-moment
Measurement and Scaling
Measurement means assigning numbers or other symbols to characteristics of objects according to certain prespecified rules. – One-to-one correspondence between the numbers and
the characteristics being measured. – The rules for assigning numbers should be standardized
and applied uniformly. – Rules must not change over objects or time.
A Classification of Scaling Techniques
Likert Semantic Differential
Stapel
Figure 8.2
Scaling Techniques
NoncomparativeScales
Comparative Scales
Paired Comparison
Rank Order
Constant Sum
Q-Sort and Other Procedures
Continuous Rating Scales
Itemized Rating Scales
Measurement and Scaling:No comparative Scaling
Techniques
Noncomparative Scaling Techniques
• Respondents evaluate only one object at a time, and for this reason noncomparative scales are often referred to as monadic scales.
• Noncomparative techniques consist of continuous and itemized rating scales.
Continuous Rating ScaleRespondents rate the objects by placing a mark at the appropriate position on a line that runs from one extreme of the criterion variable to the other.The form of the continuous scale may vary considerably. How would you rate Bigbazaar as a department store?Version 1Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Probably the best Version 2Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - Probably the best0 10 20 30 40 50 60 70 80 90
100 Version 3
Very bad Neither good Very good nor bad
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - -Probably the best0 10 20 30 40 50 60 70 80 90
100
Itemized Rating Scales
• The respondents are provided with a scale that has a number or brief description associated with each category.
• The categories are ordered in terms of scale position, and the respondents are required to select the specified category that best describes the object being rated.
• The commonly used itemized rating scales are the Likert, semantic differential, and Stapel scales.
Likert ScaleThe Likert scale requires the respondents to indicate a degree of agreement ordisagreement with each of a series of statements about the stimulus objects.
Strongly Disagree Neither Agree Strongly disagree agree nor agree
disagree 1. Bigbazaar sells high quality merchandise. 1 2X 3 4 5 2. Bigbazaar has poor in-store service. 1 2X 3 4 5 3. I like to shop at Bigbazaar. 1 2 3X 4 5
• The analysis can be conducted on an item-by-item basis (profile analysis), or a total (summated) score can be calculated.
• When arriving at a total score, the categories assigned to the negative statements by the respondents should be scored by reversing the scale.
Semantic Differential ScaleThe semantic differential is a seven-point rating scale with end points associated with bipolar labels that have semantic meaning.
Bigbazaar IS:Powerful --:--:--:--:-X-:--:--: WeakUnreliable --:--:--:--:--:-X-:--: ReliableModern --:--:--:--:--:--:-X-: Old-fashioned
• The negative adjective or phrase sometimes appears at the left side of the scale and sometimes at the right.
• This controls the tendency of some respondents, particularly those with very positive or very negative attitudes, to mark the right- or left-hand sides without reading the labels.
• Individual items on a semantic differential scale may be scored on either a -3 to +3 or a 1 to 7 scale.
A Semantic Differential Scale for Measuring Self- Concepts, Person Concepts, and Product Concepts
1) Rugged :---:---:---:---:---:---:---: Delicate
2) Excitable :---:---:---:---:---:---:---: Calm
3) Uncomfortable :---:---:---:---:---:---:---: Comfortable
4) Dominating :---:---:---:---:---:---:---: Submissive
5) Thrifty :---:---:---:---:---:---:---: Indulgent
6) Pleasant :---:---:---:---:---:---:---: Unpleasant
7) Contemporary :---:---:---:---:---:---:---: Obsolete
8) Organized :---:---:---:---:---:---:---: Unorganized
9) Rational :---:---:---:---:---:---:---: Emotional
10) Youthful :---:---:---:---:---:---:---: Mature
11) Formal :---:---:---:---:---:---:---: Informal
12) Orthodox :---:---:---:---:---:---:---: Liberal
13) Complex :---:---:---:---:---:---:---: Simple
14) Colorless :---:---:---:---:---:---:---: Colorful
15) Modest :---:---:---:---:---:---:---: Vain
Stapel ScaleThe Stapel scale is a unipolar rating scale with ten categoriesnumbered from -5 to +5, without a neutral point (zero). This scaleis usually presented vertically.
Bigbazaar
+5 +5+4 +4+3 +3+2 +2X+1 +1
HIGH QUALITY POOR SERVICE-1 -1-2 -2-3 -3-4X -4-5 -5
The data obtained by using a Stapel scale can be analyzed in thesame way as semantic differential data.
Questionnaire & Form Design
Questionnaire Definition
• A questionnaire is a formalized set of questions for obtaining information from respondents.
Choosing Question StructureUnstructured Questions
• Unstructured questions are open-ended questions that respondents answer in their own words.
Do you intend to buy a new car within the next six months?__________________________________
Choosing Question StructureStructured Questions
• Structured questions specify the set of response alternatives and the response format. A structured question may be multiple-choice, dichotomous, or a scale.
Choosing Question StructureMultiple-Choice Questions
• In multiple-choice questions, the researcher provides a choice of answers and respondents are asked to select one or more of the alternatives given.
Do you intend to buy a new car within the next six months?____ Definitely will not buy____ Probably will not buy____ Undecided____ Probably will buy____ Definitely will buy____ Other (please specify)
Choosing Question StructureDichotomous Questions
• A dichotomous question has only two response alternatives: yes or no, agree or disagree, and so on.
• Often, the two alternatives of interest are supplemented by a neutral alternative, such as “no opinion,” “don't know,” “both,” or “none.”
Do you intend to buy a new car within the next six months?_____ Yes_____ No_____ Don't know
Choosing Question StructureScales
• Scales were discussed in detail in Chapters 8 and 9:
Do you intend to buy a new car within the next six months?
Definitely Probably Undecided Probably Definitelywill not buy will not buy will buy will buy1 2 3 4 5
Choosing Question WordingDefine the Issue
• Define the issue in terms of who, what, when, where, why, and way (the six Ws). Who, what, when, and where are particularly important.
Which brand of shampoo do you use? (Incorrect)
Which brand or brands of shampoo have youpersonally used at home during the last month? In case of more than one brand, pleaselist all the brands that apply. (Correct)
Choosing Question WordingThe W's Defining the Question
Who The RespondentIt is not clear whether this question relates to the individual respondent or the respondent's total household.
What The Brand of ShampooIt is unclear how the respondent is to answer this question if more than one brand is used.
When UnclearThe time frame is not specified in this question. The respondent could interpret it as meaning the shampoo used this morning, this week, or over the past year.
Where At home, at the gym, on the road?
Choosing Question WordingUse Ordinary Words
“Do you think the distribution of soft drinks is adequate?”
(Incorrect)
“Do you think soft drinks are readily available when you want to buy them?” (Correct)
Choosing Question WordingUse Unambiguous Words
In a typical month, how often do you shop in department stores?_____ Never_____ Occasionally_____ Sometimes_____ Often_____ Regularly (Incorrect)
In a typical month, how often do you shop in department stores?_____ Less than once_____ 1 or 2 times_____ 3 or 4 times_____ More than 4 times (Correct)
Determining the Order of Questions
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.
Difficult Questions• Difficult questions or questions which are sensitive,
embarrassing, complex, or dull, should be placed late in the sequence.
Determining the Order of Questions
Logical OrderThe following guidelines should be followed for branching questions:
• 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.
Classification of Sampling TechniquesFig. 11.2
Sampling Techniques
NonprobabilitySampling Techniques
ProbabilitySampling Techniques
ConvenienceSampling
JudgmentalSampling
QuotaSampling
SnowballSampling
SystematicSampling
StratifiedSampling
ClusterSampling
Other SamplingTechniques
Simple RandomSampling
Convenience Sampling
Convenience sampling attempts to obtain a sample of convenient elements. Often, respondents are selected because they happen to be in the right place at the right time.
– use of students, and members of social organizations– mall intercept interviews without qualifying the
respondents– department stores using charge account lists– “people on the street” interviews
Judgmental Sampling
Judgmental sampling is a form of convenience sampling in which the population elements are selected based on the judgment of the researcher.
– test markets– purchase engineers selected in industrial marketing
research – bellwether precincts selected in voting behavior research– expert witnesses used in court
Quota SamplingQuota sampling may be viewed as two-stage restricted judgmental sampling. – The first stage consists of developing control categories, or quotas, of
population elements. – In the second stage, sample elements are selected based on convenience
or judgment.
Population Samplecomposition composition
ControlCharacteristic Percentage Percentage NumberSex Male 48 48 480 Female 52 52 520
____ ____ ____100 100 1000
Snowball Sampling
In snowball sampling, an initial group of respondents is selected, usually at random.
– After being interviewed, these respondents are asked to identify others who belong to the target population of interest.
– Subsequent respondents are selected based on the referrals.
Simple Random Sampling
• 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.
• This implies that every element is selected independently of every other element.
Systematic Sampling• The sample is chosen by selecting a random starting point and then
picking every ith element in succession from the sampling frame. • The sampling interval, i, is determined by dividing the population size N by
the sample size n and rounding to the nearest integer. • When the ordering of the elements is related to the characteristic of
interest, systematic sampling increases the representativeness of the sample.
• If the ordering of the elements produces a cyclical pattern, systematic sampling may decrease the representativeness of the sample. For example, there are 100,000 elements in the population and a sample of 1,000 is desired. In this case the sampling interval, i, is 100. A random number between 1 and 100 is selected. If, for example, this number is 23, the sample consists of elements 23, 123, 223, 323, 423, 523, and so on.
Stratified Sampling
• A two-step process in which the population is partitioned into subpopulations, or strata.
• The strata should be mutually exclusive and collectively exhaustive in that every population element should be assigned to one and only one stratum and no population elements should be omitted.
• Next, elements are selected from each stratum by a random procedure, usually SRS.
• A major objective of stratified sampling is to increase precision without increasing cost.
Stratified Sampling• The elements within a stratum should be as homogeneous as possible,
but the elements in different strata should be as heterogeneous as possible.
• The stratification variables should also be closely related to the characteristic of interest.
• Finally, the variables should decrease the cost of the stratification process by being easy to measure and apply.
• In proportionate stratified sampling, the size of the sample drawn from each stratum is proportionate to the relative size of that stratum in the total population.
• In disproportionate stratified sampling, the size of the sample from each stratum is proportionate to the relative size of that stratum and to the standard deviation of the distribution of the characteristic of interest among all the elements in that stratum.
Cluster Sampling• The target population is first divided into mutually exclusive and
collectively exhaustive subpopulations, or clusters. • Then a random sample of clusters is selected, based on a probability
sampling technique such as SRS. • For each selected cluster, either all the elements are included in the
sample (one-stage) or a sample of elements is drawn probabilistically (two-stage).
• Elements within a cluster should be as heterogeneous as possible, but clusters themselves should be as homogeneous as possible. Ideally, each cluster should be a small-scale representation of the population.
• In probability proportionate to size sampling, the clusters are sampled with probability proportional to size. In the second stage, the probability of selecting a sampling unit in a selected cluster varies inversely with the size of the cluster.
Types of Cluster SamplingFig. 11.3 Cluster Sampling
One-StageSampling
MultistageSampling
Two-StageSampling
Simple ClusterSampling
ProbabilityProportionate
to Size Sampling
Fieldwork/Data Collection ProcessFig. 13.1
Selecting Field Workers
Training Field Workers
Supervising Field Workers
Validating Fieldwork
Evaluating Field Workers
A Classification of Multivariate TechniquesFig. 14.7
More Than One Dependent
Variable* Multivariate
Analysis of Variance and Covariance
* Canonical Correlation
* Multiple Discriminant Analysis
* Cross- Tabulation
* Analysis of Variance and Covariance
* Multiple Regression
* Conjoint Analysis
* Factor Analysis
One Dependent Variable
Variable Interdependence
Interobject Similarity
* Cluster Analysis* Multidimensional
Scaling
Dependence Technique
Interdependence Technique
Multivariate Techniques
A General Procedure for Hypothesis TestingStep 1: Formulate the Hypothesis
• A null hypothesis is a statement of the status quo, one of no difference or no effect. If the null hypothesis is not rejected, no changes will be made.
• An alternative hypothesis is one in which some difference or effect is expected. Accepting the alternative hypothesis will lead to changes in opinions or actions.
• The null hypothesis refers to a specified value of the population parameter (e.g., ), not a sample statistic (e.g., ).
, , X
• The test of the null hypothesis is a one-tailed test, because the alternative hypothesis is expressed directionally. If that is not the case, then a two-tailed test would be required, and the hypotheses would be expressed as:
H 0: = 0.40
H1: 0.40
A General Procedure for Hypothesis TestingStep 1: Formulate the Hypothesis
Type I Error • Type I error occurs when the sample results lead to the
rejection of the null hypothesis when it is in fact true. • The probability of type I error ( ) is also called the level of
significance.
Type II Error • Type II error occurs when, based on the sample results, the
null hypothesis is not rejected when it is in fact false. • The probability of type II error is denoted by . • Unlike , which is specified by the researcher, the magnitude
of depends on the actual value of the population parameter (proportion).
A General Procedure for Hypothesis TestingStep 3: Choose a Level of Significance
Probabilities of Type I & Type II ErrorFigure 15.4
99% of Total Area
Critical Value of Z
= 0.40
= 0.45
= 0.01
= 1.645Z
= -2.33Z
Z
Z
95% of Total Area
= 0.05
Independent Samples
Paired Samples Independent
SamplesPaired
Samples* Two-Group t test
* Z test
* Paired t test * Chi-Square
* Mann-Whitney* Median* K-S
* Sign* Wilcoxon* McNemar* Chi-Square
A Classification of Hypothesis Testing Procedures for Examining DifferencesFig. 15.9 Hypothesis Tests
One Sample Two or More Samples
One Sample Two or More Samples
* t test* Z test
* Chi-Square * K-S * Runs* Binomial
Parametric Tests (Metric Tests)
Non-parametric Tests (Nonmetric Tests)
Hypothesis Testing Related to Differences
• Parametric tests assume that the variables of interest are measured on at least an interval scale.
• Nonparametric tests assume that the variables are measured on a nominal or ordinal scale.
• These tests can be further classified based on whether one or two or more samples are involved.
• The samples are independent if they are drawn randomly from different populations. For the purpose of analysis, data pertaining to different groups of respondents, e.g., males and females, are generally treated as independent samples.
• The samples are paired when the data for the two samples relate to the same group of respondents.
Chi-square DistributionFigure 15.8
Reject H0
Do Not Reject H0
CriticalValue
2
Report Preparation and Presentation
The Report Preparation and Presentation Process
Fig. 22.1
Data Analysis
Oral Presentation
Report Preparation
Interpretations, Conclusions, and Recommendations
Reading of the Report by the Client
Research Follow-Up
Problem Definition, Approach, Research Design, and Fieldwork
Report Format
X. Problem definitiona. Background to the problemb. Statement of the problem
XI. Approach to the problemXII. Research design
a. Type of research designb. Information needsc. Data collection from secondary sourcesd. Data collection from primary sourcese. Scaling techniques f. Questionnaire development and pretestingg. Sampling techniquesh. Fieldwork
Report Format
XIII. Data analysis a. Methodologyb. Plan of data analysis
XIV. Results XV. Limitations and caveatsXVI. Conclusions and recommendationsXVII. Exhibits
a. Questionnaires and formsb. Statistical outputc. Lists
Report Writing• Readers. A report should be written for a specific reader
or readers: the marketing managers who will use the results.
• Easy to follow. The report should be easy to follow. It should be structured logically and written clearly.
• Presentable and professional appearance. The looks of a report are important.
• Objective. Objectivity is a virtue that should guide report writing. The rule is, "Tell it like it is."
• Reinforce text with tables and graphs. It is important to reinforce key information in the text with tables, graphs, pictures, maps, and other visual devices.
• Terse. A report should be terse and concise. Yet, brevity should not be achieved at the expense of completeness.
Guidelines for Tables• Title and number. Every table should have a number (1a) and title
(1b). • Arrangement of data items. The arrangement of data items in a
table should emphasize the most significant aspect of the data. • Basis of measurement. The basis or unit of measurement should be
clearly stated (3a).• Leaders, rulings, spaces. Leaders, dots or hyphens used to lead the
eye horizontally, impart uniformity and improve readability (4a). Instead of ruling the table horizontally or vertically, white spaces (4b) are used to set off data items. Skipping lines after different sections of the data can also assist the eye. Horizontal rules (4c) are often used after the headings.
• Explanations and comments: Headings, stubs, and footnotes. Designations placed over the vertical columns are called headings (5a). Designations placed in the left-hand column are called stubs (5b). Information that cannot be incorporated in the table should be explained by footnotes (5c).
• Sources of the data. If the data contained in the table are secondary, the source of data should be cited (6a).
MFG 1997 1998 1999 2000 2001GM 4,766,000 4,604,000 5,017,000 4,953,000 4,898,517
Ford 4,432,000 4,370,000 4,787,000 4,933,000 4,661,685Chrysler 2,312,400 2,548,900 2,693,000 2,470,000 2,196,000Honda 940,037 1,009,600 1,076,893 1,158,860 1,207,639Toyota 1,230,583 1,361,025 1,515,366 1,656,981 1,787,882Nissan 658,000 628,000 713,000 744,000 695,640Other* 1,161,980 1,444,475 1,615,741 1,901,159 1,752,637Total 15,501,000 15,966,000 17,418,000 17,817,000 17,200,000
TABLE 22.1U.S. Automotive Sales 1997-2001
Unit Sales
1b
1a3a
6a
5b
5a
4c
2a4a
5c
4b
* - includes all other producersSource: Company Websites
U.S. Auto Sales 1997 - 2001Table 22.1
Guidelines for GraphsGeographic and Other Maps
• Geographic maps can pertain to countries, states, counties, sales territories, and other divisions.
• Chapter 21 showed examples of product-positioning.
Guidelines for GraphsRound or Pie Charts
• In a pie chart, the area of each section, as a percentage of the total area of the circle, reflects the percentage associated with the value of a specific variable.
• A pie chart is not useful for displaying relationships over time or relationships among several variables.
• As a general guideline, a pie chart should not require more than seven sections.
Pie Chart of 1996 U.S. Auto SalesFig. 22.2
Guidelines for GraphsLine Charts
• A line chart connects a series of data points using continuous lines.
• This is an attractive way of illustrating trends and changes over time.
• Several series can be compared on the same chart, and forecasts, interpolations, and extrapolations can be shown.
Line Chart of Total U.S. Auto SalesFig. 22.3
Un
its
Year
Guidelines for GraphsLine Charts
• A stratum chart is a set of line charts in which the data are successively aggregated over the series.
• Areas between the line charts display the magnitudes of the relevant variables.
Stratum Chart of Auto Sales by Manufacturer (1997-2001)
0
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
16,000,000
18,000,000
20,000,000
1997 1998 1999 2000 2001
Other
Nissan
Toyota
Honda
Chrysler
Ford
GM
Fig. 22.4
Stratum Chart of Total U.S. Auto Sales
Guidelines for GraphsPictographs
• A pictograph uses small pictures or symbols to display the data.
• Pictographs do not depict results precisely. Hence, caution should be exercised when using them.
Pictograph of Auto Sales (2001)
0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000
GM
Ford
Chrysler
Honda
Toyota
Nissan
Ma
nu
fac
ture
r
Cars Sold
Pictograph for 1996 U.S. Auto SalesFig. 22.5
*Each Symbol Equals 1,000,000 Units
Guidelines for GraphsHistograms and Bar Charts
• A bar chart displays data in various bars that may be positioned horizontally or vertically.
• The histogram is a vertical bar chart and in which the height of the bars represents the relative or cumulative frequency of occurrence of a specific variable.
Histogram of Auto Sales by Manufacturer (2001)
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
GM Ford Chrysler Honda Toyota Nissan Other
Figure 22.6
Histogram of 1996 U.S. Auto Sales
Make
Un
its
Guidelines for GraphsSchematic Figures and Flow Charts
• Schematic figures and flow charts take on a number of different forms. They can be used to display the steps or components of a process, as in Figure 22.1.
• Another useful form of these charts is a classification diagram. Examples of classification charts for classifying secondary data were provided in Chapter 4 (Figs. 4.1 to 4.4).
• An example of a flow chart for questionnaire design was given in Chapter 10 (Figure 10.2).
Oral Presentation
• The key to an effective presentation is preparation. • A written script or detailed outline should be prepared
following the format of the written report. • The presentation must be geared to the audience. • The presentation should be rehearsed several times before it
is made to the management.• Visual aids, such as tables and graphs, should be displayed
with a variety of media.• It is important to maintain eye contact and interact with the
audience during the presentation.
Oral Presentation
• Filler words like "uh," "y'know," and "all right," should not be used.
• The "Tell 'Em" principle is effective for structuring a presentation.
• Another useful guideline is the "KISS 'Em" principle, which states: Keep It Simple and Straightforward (hence the acronym KISS).
• Body language should be employed.• The speaker should vary the volume, pitch, voice quality,
articulation, and rate while speaking.• The presentation should terminate with a strong
closing.
Reading the Research Report
• Addresses the Problem – The problem being addressed should be clearly identified and the relevant background information provided.
• The research design should be clearly described in non-technical terms.
• Execution of the Research Procedures – The reader should pay special attention to the manner in which the research procedures were executed.
• Numbers and statistics reported in tables and graphs should be examined carefully by the reader.
Reading the Research Report
• Interpretation and Conclusions – The interpretation of the basic results should be differentiated from the results per se. Any conclusions or recommendations made without a specification of the underlying assumptions or limitations should be treated cautiously by the reader.
• Generalizability – It is the responsibility of the researcher to provide evidence regarding the reliability, validity, and generalizability of the findings.
• Disclosure – The reader should carefully examine whether the spirit in which the report was written indicates an honest and complete disclosure of the research procedures and results.
Research Follow-up
• Assisting the Client – The researcher should answer questions that may arise and help the client to implement the findings.
• Evaluation of the Research Project – Every marketing research project provides an opportunity for learning and the researcher should critically evaluate the entire project to obtain new insights and knowledge.
