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1、Overview of Research Methodologies QUANTITATIVE RESEARCH METHODS,Table of Contents,Part I-Introduction To Basic Quantitative MethodsPart II-Case Study-Brand Tracking StudyDemonstration Using SPSS 14.0 Sample Size Calculation Overview of Data Composition,Scale,Types of variables etc.,Exploratory Data
2、 AnalysisBasic Statistical Tests To Detect Differences Between groups of doctorsBetween brandsStatistical Tests To Detect RelationshipsStatistical Hypothesis TestingPart III-Introduction To Advanced Quantitative MethodsFactor Analysis Perceptual MappingSegmentation Analysis,PART IINTRODUCTION TO BAS
3、IC QUANTITATIVE METHODS,Definition of Quantitative Research,Quantitative research is numerically oriented and often involves statistical analysis.The main rule with quantitative research is that every respondent is asked the same series of questions.This approach is very structured and normally invo
4、lves large numbers of interviews.,Types of Data,Numerical data generally come in two kinds:MEASUREMENT DATA(sometimes called quantitative data)On an average how many patients with diabetes did you treat in a month?_ patientsCATEGORICAL DATA(also known as frequency data or count data)What is your spe
5、cialty?Please tick one1.Cardiologists,2.Endocrinologists3.Nephrologists4.Internal Medicine5.General Practitioner,Scales of Measurement,Measurement is frequently defined as the assignment of numbers to objects:INTERVAL SCALE in which we can speak of differences between scale pointsHow many years you
6、have been in practice?_yearsORDINAL SCALE which orders people,objects or events along some continuumHow satisfied your are with brand A?1.Not at all satisfied2.Not satisfied3.Neutral4.Satisfied5.Very satisfiedNOMINAL SCALE is not really a scale as they do not scale items along any dimension What is
7、your gender?Please tick one1.Male2.FemaleIn which state do you normally practice?Please tick one1.ACT 2.NSW 3.NT 4.QLD 5.SA 6.TAS 7.VIC 8.WA,Composition of Data,A data typically consists of:VARIABLES are properties or characteristics of a study or therapy type etc.,e.g.attitudinal statements,product
8、 characteristics,functional and emotional attributes,patient flow etc.,CASES typically correspond to respondents e.g.Doctors,Patients,Pharmacists etc.,RESPONSES are values assigned to each variable e.g.1,2 or 3 etc.,Types of Variables,The variables fall under two types depending on different values
9、assigned:DISCRETE VARIABLES in which the variable can take on only one of a relatively few possible values e.g.Gender,Location,Specialty etc.,CONTINUOUS VARIABLES in which the variable could assume any value between the lowest and highest points on the scale e.g.Number of patients treated,Diagnostic
10、 parameters like BP,LDL-C,HDL-C,HbA1c etc.,We can also distinguish between different types of variables in an additional way:DEPENDENT VARIABLE is the variable of interest or whose values we wish to predict e.g.Overall brand satisfactionINDEPENDENT VARIABLES(also referred as explanatory variables or
11、 predictor variables)are the variables which influences or affects dependent variable.e.g.Importance statements,product characteristics,INFERENTIAL Inferential statistics are concernedwith using SAMPLES to infersomething about POPULATIONS.Population can range from arelatively small set of numbers,Wh
12、ich is easily collected,to aninfinitely large set of numbers,which can never be completelycollected.Hence we are forced to draw only aSAMPLE of observations from thatPOPULATIONRange of statistical tests areavailable to choose from whichdepends on the objectives of thestudy,Types of Data Analysis,EXP
13、LORATORY Exploratory techniques are used forpresenting data in visually meaningfulways.Also,these techniques are usedfor initial data screening purposes.Frequency distributionsHistogramsBox and Whisker plotsStem and Leaf plotsMissing valuesOutliers,DESCRIPTIVE Descriptive statistical tests are usedt
14、o describe a set of data.Mean MedianModeSumMeasures of dispersionMinimumMaximumRangeVarianceStandard deviationStandard error DistributionKurtosisSkewness,Probability Sampling MethodsThis method gives all members of the population a known chance of being selected for inclusion in the sample,Methods o
15、f Sampling,Non-probability Sampling MethodsThe quotas(quota sampling)within subgroups are set beforehand usually proportions are set to match known population distributions.Interviewers then select respondents according to these criteria rather than at random.The subjective nature of this selection
16、means that only about a proportion of the population has a chance of being selected in a typical quota sampling strategy,Sample Size CalculationGeneral Rules,What margin of error can you accept?The margin of error is the amount of error that you can tolerate.Lower margin oferror requires a larger sa
17、mple size5%is a common choiceWhat confidence level do you need?The confidence level is the amount of uncertainty you can tolerate.Higherconfidence level requires a larger sample size.Typical choices are 90%,95%,or 99%What is the population size?How many people are there to choose your random sample
18、from?What is the response distribution?For each question,what do you expect the results will be?If the sample is skewed highly to one end,the population probably is,too.If you dont know,use 50%.This gives the largest sample size.The most conservative choice is 50%,Sample Size Calculation Infinite vs
19、.Finite Population,INFINITE POPULATIONThe sample size does not change much for populations larger than 20,000FINITE POPULATIONIn pharmaceutical market research studies we commonly encounter a small population(i.e.finite population)in certain therapy areas such as Oncology,Nephrology,Neurology etc.,I
20、n such situations the sample size calculation must incorporate FINITE POPULATION CORRECTION(FPC)With small populations,we may have to interview a significant proportion of the population to achieve stable estimatesHowever,once a population reaches about 5000 or more,we can generally ignore the finit
21、e population correction factor,as it has very small impact on sample size decisions,Sampling Design Sources of Error,BIAS:occurs when flawed sampling procedure is used.Bias cannot be measured,and the selection of a larger sample does not correct for the fact that the sample is biased SAMPLING ERROR:
22、occurs when samples of respondents deviate from the underlying population.If we have used random sampling method,any sampling error is due to a chance.With random sampling,we reduce sampling error by increasing the sample size.MEASUREMENT ERROR:arises from many sourcesdata collection methodsintervie
23、wers quality and experiencerespondents understanding of the questionnairetype of scale questionnaire designcontext of data collection,Statistical TestingParametric vs.Non-Parametric Tests,The selection between a parametric or non-parametric tests depend on whether the data being analysed are sampled
24、 from a population that are NORMALLY DISTRIBUTED(also referred as Gaussian distribution)or notPARAMETRIC STATISTICAL TESTS:are used when normality is metNON-PARAMETRIC STATISTICAL TESTS(or distribution free tests):are used when normality is not metA normal distribution is a symmetric,unimodal distri
25、bution,and“bell shaped”,Statistical TestingProperties of Normal Distribution,68.2%of the responses fall within a standard deviation of+1The mean,median and mode are equalGenerally the distribution tend to become normal for a sample size of greater than 30,Most marketing questions(i.e.statistical)fal
26、l roughly into one of two overlapping categories:DIFFERENCESIs there any difference between endocrinologists and GPs in terms of overall satisfaction of diabetes treatment?Is there any difference between brands?RELATIONSHIPSIs there any relationship between importance of product attributes and overa
27、ll performance of a given brand?,Statistical TestingDifferences vs.Relationships,Statistical Hypothesis Testing,A hypothesis test usually derives from a prior research hypothesis(usually QUALITATIVE stage)stating that a relationship exists between two or more variables,or two or more groups will be
28、different on some characteristics.For example,Hypothesis:Among doctors,orthopaedics believe In post-menopausal women with osteoporosis,Vitamin D inadequacy is widespread and needs to be corrected”than GPsTo test this research hypothesis statistically,we would formulate two statistical hypothesis:Nul
29、l hypothesis:the mean for orthopaedics on the above statement is equal to or less than the mean for GPs.Expressed in symbols:Ho:ortho GPAlternative hypothesis:the mean for orthopaedics will be greater than the mean for GPs.Expressed symbolically:H1:ortho GPThe two hypotheses are mutually exclusive.T
30、hey cannot both be true.As a researcher performing a statistical test,we must ultimately make one of two decisions relative to thenull hypothesis Choosing a statistical test to test the research hypothesisOne-tailed test:is used if we know the direction of the hypothesised difference i.e.Orthopedics
31、 believe than GPsTwo-tailed test:is used if we do not know the direction of that difference,Choosing a Basic Statistical Test,DIFFERENCES,RELATIONSHIP,NOTE:*These analyses will be demonstrated with the help of a case study,PART IICase Study-Brand Tracking Study,Demonstration Using SPSS 14.0 Sample S
32、ize CalculationOverview of Data Composition,Scale,Types of variablesExploratory Data AnalysisBasic Statistical Tests To Detect Differences Between groups of doctorsBetween brandsStatistical Tests To Detect RelationshipsHypothesis Testing,PART IIIINTRODUCTION TO ADVANCED QUANTITATIVE METHODS(MULTIVAR
33、IATE TECHNIQUES),Case StudyFactor AnalysisPerceptual MappingSegmentation Analysis,Multivariate Techniques,Multivariate techniques are broadly grouped into two categories:INTERDEPENDENT techniques are used to either grouping similar customers or variables To identify target customer segments(grouping
34、 customers)To identify underlying attitudinal/emotional“themes”or“factors”(grouping variables)DEPENDENT techniques are used to study the effect of a number of variables on one or more variables To identify drivers of brand satisfaction(satisfaction vs.product,attitudinal,emotional attributes),Choosi
35、ng a Multivariate TechniqueInterdependent Techniques,NOTE:*These analyses will be discussed in detail,Choosing a Multivariate TechniqueDependent Techniques,Factor Analysis,Factor analysis is an exploratory data analysis technique often used as a data reduction methodFactor analysis transforms a set
36、of correlated variables into fewer conceptual dimensions known as“factors”Factor names are provided by analyst,based on dominant or common attributes within the bundle of attributes,Sample size considerations The common rule is to have at least 10-15 responses per attribute,Factor AnalysisCase Study
37、,MARKETING APPLICATIONA marketer have measured 30 different PERCEPTION ATTRIBUTES that are considered important to a specific therapy area The marketer wanted to identify underlying themes or factors within those 30 attributes rather than evaluating individual attributes.TOOLBased on intercorrelatio
38、ns among these 30 ATTRIBUTES,factor analysis reduced them to 7 THEMES OR FACTORS This has helped the marketer to focus and develop marketing strategy accordinglyThis has also helped the market researcher to reduce the number of attributes to be incorporated in the questionnaire for future studies,Fa
39、ctor AnalysisCase Study,QUESTIONNAIREPlease indicate your level of agreement with each of the following statements as they apply to the treatment of a“specific therapy area”.Using the 5-point scale shown,where“1”means“strongly disagree”,“5”means“strongly agree”,please cross the most appropriate resp
40、onse.Attribute 1Attribute 2.Attribute 30,Factor AnalysisIdentification of Underlying Themes,The 30 perception statements rated by respondents are simplified into 7 key themes or factors using factor analysis*.,Factor Analysis,Factor Analysis,The 30 perception statements rated by respondents are simp
41、lified into 7 key factors or components using factor analysis*.,Factor AnalysisIdentification of Underlying Themes,Perceptual Mapping,Perceptual map is a visual representation of TWO data sets such as different brands and product attributes different brands and demographic traits different corporati
42、ons and key image attributes etc.,Perceptual map is produced by using TWO different techniques:Correspondence analysisMultidimensional scaling,Perceptual MappingCase Study,MARKETING APPLICATIONA marketer wanted to identify how 5 DIFFERENT BRANDS are perceived on 8 KEY ATTRIBUTES as applied to a spec
43、ific therapy area TOOLCorrespondence analysis produced a perceptual map which positions brands against attributes on a two dimensional map This has helped the marketer to UNDERSTAND BRAND POSITIONING,Perceptual MappingCase Study,QUESTIONNAIREBased on your knowledge and experience with the brand,plea
44、se identify presence or absence of below 8 attributes that a brand may haveBrand 1 Brand 2 Brand 3 Brand 4 Brand 5 Attribute 1Attribute 2.Attribute 8,Perceptual Mapping:Brands vs.Attributes,Brand E,Brand A,Brand B,Brand D,Brand C,Works fast,Improves bone quality,Prevents hipfractures,Safe for long-t
45、erm use,Convenience,Prevents vertebral fractures,Well tolerated,The relative perceived positioning of the various 5 brands vs.8 product attributes,Increases BMD,Segmentation Analysis,The purpose of segmentation analysis is to form groups of respondents(doctors,patients etc.,)such that,with respect t
46、o clustering variable(s),each group is as homogenous as possible and as different from the other groups as possible.There are TWO main routes to segmentation:A priori segmentation(referred as OUTSIDE-IN)The segments are ASSUMED before-hand such as based on demographics,geographic etc.,Cluster-based
47、segmentation*(INSIDE-OUT)The segments are NOT ASSUMED before-hand but identified based on homogeneity exhibited by respondents on certain parameters such as behavioural attributes,perception statements,attitude towards new drug introduction etc.,NOTE:*This will be discussed in detail,VARIABLE SELECT
48、ION is the single most crucial step in cluster analysisThe selection of variable depends on the type of business objective that we have in mind.We may want to segment respondents based on“benefit segmentation,”or“need-based segmentation”or“attitudinal segmentation”etc.,The variables that meet our bu
49、siness objective are chosen for cluster analysisThe segments are then profiled to identify distinct differences between the segments The number of clusters(i.e.segments)depends on the following characteristics:Meaningfulness How sensible or meaningful the segments are Accessibility How effectively c
50、an the segment be reachedSustainability The degree to which the segments are large or profitable enoughActionability The degree to which they can have programs designed for them,Segmentation AnalysisGeneral Rules,Segmentation AnalysisCase Study,MARKETING APPLICATIONPurpose of the segmentation study
