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Research process- A

systematic approachResearch refers to the systematic method consisting of:

Defining the problem,

Formulating a hypothesis,

Collecting the fact or data,

Analyzing the facts and

Reaching certain conclusions in the form of solutions

towards the concerned problem

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Characteristics of Research

a. Systematic Approach

Each step must of your investigation be so planned that it leads to the next step.Planning and organization are part of this approach. A planned and organizedresearch saves your time and money.

b. Objectivity

It implies that True Research should attempt to find an unbiased answer to thedecision-making

c. ReproducibleA reproducible research procedure is one, which an equally competent researcher

could duplicate, and from it deduces approximately the same results.

d. Relevancy It avoids collection of irrelevant information and saves time and money

It enables to see whether the research is proceeding in the right direction

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ROLE OF RESERCH- EXMP

MARKETING:

Advertising research, packaging research, product performance evaluation research, salesanalysis, distribution channel, Demand forecasting, Consumer buying behaviour,

Measuring advertising effectiveness, Media selection for advertising, Test marketing,

Product positioning, Product potential

Production: Product development, Cost reduction, Work simplification, Profitabilityimprovement, Inventory control, Quality control

HR: wage rates, incentive schemes, cost of living, employee turnover rates, employment trends,

and performance appraisal.

Finance: Investment avenues, Investment Behaviour, Portfolio management, Researches in

Capital Markets, Portfolio Management, cost analysis, Working Capital Management.

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Basic terminology

A problem statement: a problem statement articulates the

problem to be addressed and indicates the need for a study.A statement of purpose: which is the researcher s summary

of the overall goal of a study

A research question is a clear, focused, concise, complex

and arguable question around which you centre your

research. You should ask a question about an issue that you

are genuinely curious about.

Research aims or objectives: the specific accomplishmentsthe researcher hopes to acheive by conducting the study.The

objectives include obtaining answers to reach questions or

testing research hypotheses

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Source of research problems

Students are sometimes puzzled about the origins ofresearch problems

Where do ideas for research problems come from

How do researchers select topic areas and develop researchquestions

At the most basic level, research topics originateresearchersinterests

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Evaluationg Research problem

There are no rules for making a final selection of aresearch problem

The four most important consideration are

the significance,

researchability, and

feasibility of the problem and

its interest to the researcher

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The Significance of Problem Its significance to current practice

Researchers should pose the following kinds of questions:

Is the problem an important one?

Will society or organisation or employees benefit from theevidence that will be produced?

Will the results lead to practical applications

Will the findings challenge untested asuumptions?

If the answer to all these questions is no then the problem

should be abandoned (behind, left alone)

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Researchability of the problem

When a new area of inquiry (a search forknowledge) is being pursued, it may be

impossible to define the concepts of interest in

precise terms It may be appropriate to address the problem

using in-depth qualitative research

The problem may be stated fairly broad termsto permit full exploration of the concept of

interest

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Problemdiscovery

Problem definition(statement of

research objectives)

Secondary

(historical)

data

Experience

survey

Pilot

study

Case

study

Selection of

exploratory researchtechnique

Selection of

basic research

method

Experiment SurveyObservation

Secondary

Data StudyLaboratory Field Interview Questionnaire

Selection of

exploratory research

techniqueSampling

Probability Nonprobability

Collection of

data

(fieldwork)

Editing andcoding

data

Data

processing

Interpretation

of

findings

Report

Data

Gathering

DataProcessing

and Analysis

Conclusions

and Report

Research Design

Problem Discovery

and Definition

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Symptoms vs. Problems

Chocolate

Symptom

Consumers prefer the taste of competitors brand

PD based on the Symptom

What type of reformulated taste is needed?

True Problem

Old-fashioned package influenced taste perception

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Symptoms vs. Problems

Manufacturer of palm-size computers with Internetaccess

SymptomDistributors complain prices are too high

PD based on the Symptom

Investigate business users to learn how much pricesneed to be reduced

True Problem

Distributors do not have adequate product knowledge to

communicate products value

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Management Decision Problems vs.

Marketing Research Problems

Management Decision

Problems

Ask what the decisionmaker needs to do

Action oriented

Focus on symptoms

Marketing Research

Problems

Ask what information is

needed and how it

should be obtained

Information oriented

Focus on the underlying

causes

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Translating Management Problems into

Research Problems (Questions)

Management Problem Determine the best ways the firm can communicate

with potential purchasers of laptop computers

Research Questions How familiar are consumers with the various brands of

computers?

What attitudes do consumers have toward these brands? How important are the various factors for evaluating

the purchase of a laptop computer?

How effective are the communications efforts of thevarious competitive marketers in terms of message

recognition?

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Descriptive research question Relationship research question

Difference research question

Types of Research questions

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Typically asks what is and suggests a surveydesign

Descriptive research question

Examples:What is the prevailing organizational culture insoftware organisations in India?

What are the dominant leadership values held by the

Managers in the software industry in India?

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Relationship research question

It asks What is the relationship between two ormore variables?

Examples:Does self-concept relate to self-confidence of the

employees?

Is organizational commitment related to theemployers length of service with the company?

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Difference research question

Typically asks Is there a difference between two

groups?

This type of question is used when the researcher

compares two or more observations.

Examples:

1. Do male and female students marks in GATE examinationdiffer?

2. Is there a significant difference in the investment pattern withrespect to different classification s of:

2.1 age;

2.2 gender; and

2.3 Family status?

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Common

Errors

Errors in Defining the Research Problem

Problem Definition is

too Broad

Does Not Provide

Guidelines for

Subsequent Steps

e.g., Improving the

Companys Image

Problem Definition

is too Narrow

May Miss Some

Important Components

of the Problem

e.g. Changing Prices in

Response to a

Competitors Price

Change.

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Bad vs. Good Research Questions

Research questions should be stated as clearly as

possible

Bad research questionIs advertising copy X better than advertising copy Y?

Good research question

Which advertising copy has a higher day-after recall score?

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Sample Research Questions

Unclear:Why are social networking sites harmful?

Clear:How are online users experiencing or addressingprivacy issues on such social networking sites as MySpace andFacebook?

Unfocused:What is the effect on the environment from global

warming?

Focused:How is glacial melting affecting penguins in Antarctica?

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Components of

the MarketingResearch Problem

Research

Questions

Hypotheses

AnalyticalFramework

and

Models

Development of Research Questions & Hypothesis

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Analytical Framework & Models

Research questions & hypotheses are developed withinanalytical frameworks Basically, theories & models

Theory suggests that satisfaction improves

morale & perceptionsA sales manager who wants to increase market share

(management problem) may:

Ask how to encourage salespeople to generate moresales (research question)

State that (based on theory) higher job satisfactionleads to greater sales productivity (hypothesis)

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The overall goal of the project is to assess the

performance of national pharmaceutical policies in

developing countries (focusing on policy outputs

andpolicy process), to analyze the reasons for theirsuccess or failure, and to propose strategies for

improvement.

RQ & OBJECTIVES

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RQ & OBJECTIVES

The principal research question that the project seeks to answer is:Have National Drug Policies (whether they exist as explicit policy

documents, or are implicit in government actions) in developing

countries been successful in achieving the goals of availability,

accessibility, good quality, and rational use of essential drugs? Why orwhy not?

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RQ & OBJECTIVES

Within this context, the specific objectives are:

a) To identify strengths, weaknesses, and political dimensions of

pharmaceutical policy formulation and implementation within each

country;

b) To propose explanations for cross-national variations in performance;

and

c) To propose effective strategies, both national and international, that

can improve pharmaceutical policy implementation.

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Theory testing and theory construction

Theory building

Theory building is a process in which research begins with

observations and uses inductive reasoning to derive a theory from

these observations.

Theory testing

1. Theory testing approach begins with a theory and2. Uses theory to guide which observations to make:

3. It moves from the general to the particular.

4. The observations should provide a test of the worth of the

theory.

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Theory building and theory testing approaches to research

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RESEARCH DESIGN

It is the framework, a blueprint for the research study which guides thecollection and analysis of data.

To be effective, a research design should furnish at least the following

details.

a) A statement of objectives of the study or the research output.

b) A statement of the data inputs required on the basis of which theresearch problem is to be solved.

c) The methods of analysis which shall be used to treat and analyse the

data inputs.

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Types of Research Design Three traditional categories of research design:

Exploratory

Descriptive

Causal/Experimental

The choice of the most appropriate design dependslargely on the objectives of the research and how much

is known about the problem and these objectives.

Uncertainty Influences The Type Of Research

COMPLETELY

CERTAIN

ABSOLUTE

AMBIGUITY

CAUSALOR

DESCRIPTIVE

EXPLORATORY

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Research Design: Exploratory Research

The exploratory research design, as the name suggests:

-involves getting a feel of the situation;

- emphasises a discovery of ideas and

-possible insights that may help in identifying areas of further rigorous

study.

The main objective of the exploratory research is to fine tune the

broad problem into specific problem statement and generate possible

hypotheses.

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The exploratory studies are mainly used for:

1) Providing information to enable a more precise problem

definition or hypothesis formulation.

2) Establishing research priorities.

3) Giving the researcher a feel of the problem situation and

familiarising him with the problem.

4) Collecting information about possible problems in carrying out

research, using specific collection tools and specific techniques for

analysis.

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The generally used methods in exploratory research are:

a) Survey of existing literature

b) Survey of experienced individuals

c) Analysis of selected case situations.

d) Focus Groups

e)Projective Techniques

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DESCRIPTIVE RESEARCH DESIGN

Descriptive research is undertaken to provide answers to questionsof who, what, where, when, and howbut not why.

Descriptive designs are aimed only at providing accurate

descriptions of variables relevant to the problem under

consideration, they are generally used for preliminary andexplorative studies.

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Descriptive research can be used for the following purposes:

a) To describe the characteristics of certain groups of interest to the

marketer e.g. users of the product, potential users, non users, possiblereceivers of promotional communication by the company and so on.

b) To estimate the proportion of people in a given population who behave

in a certain way for example the proportion of consumers who are proneto deals.

c) To make specific predictions for specified future periods.

d) To develop inferences whether certain variables are associated, for

example income and shopping place preference.

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Two basic classifications: Descriptive Research

Design Cross-sectional studies

Longitudinal studies

The cross sectional study is aimed at taking a one time measure of the

situation or the phenomenon in which the decision maker is interested.

Cross sectional designs give the picture of the situation at a given point

of time.

Cross-sectional studies measure units from a sample of the population

at only one point in time.

CROSS SECTIONAL STUDIES

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LONGITUDINAL STUDIES

Involves the continual or periodic information collection from a fixed

panel or sample of respondents.

Two types of panels:

Continuous panels ask panel members the same questions on eachpanel measurement.

Discontinuous (Omnibus) panels vary questions from one time tothe next.

Longitudinal data used for:

Market tracking

Brand-switching

Attitude and image checks

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Research Hypotheses

A hypothesis is a prediction about the relationshipbetween two or more variables

A hypothesis translates a quantitative researchquestion into a precise prediction of expected

outcomes

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Functions

Bringing clarity to the research problem

Serves the following functions

provides a study with focus

signifies what specific aspects of a research problem is toinvestigate

what data to be collected and what not to be collected

enhancement of objectivity of the study

formulate the theory

enable to conclude with what is true or what is false

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Characteristics Hypotheses has the following characteristics:

1. Operationalisable

2. a tentative proposition

3. unknown validity

4. specifies relation between two or more variables

5. Simple, specific, and contextually clear

6. Capable of verification7. Related to the existing body of knowledge

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Typologies

Three types

working hypothesis

Null hypothesis

Alternate hypothesis

Working hypothesis

Theworking or trail hypothesis is provisionally adopted to

explain the relationship between some observed facts forguiding a researcher in the investigation of a problem.

A Statement constitutes a trail or working hypothesis (which) is

to be tested and conformed, modifies or even abandoned asthe investi ation roceeds.

Typologies

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Typologies

NNull hypothesis

A Null hypothesis is formulated against the working hypothesis; opposes the

statement of the working hypothesis

....it is contrary to the positive statement made in the working hypothesis;formulated to disprove the contrary of a working hypothesis

When a researcher rejects a null hypothesis, he/she actually proves a working

hypothesis

IIn statistics, to mean a null hypothesis usually Ho is used. For example,HoQ = O

where Q is the property of the population under investigation

O is hypothetical

Typologies

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Typologies

Alternate hypothesis

An alternate hypothesis is formulated when a researcher totallyrejects null hypothesis

He/she develops such a hypothesis with adequate reasons

The notion used to mean alternate hypothesis is H1

Q>Oi.e., Q is greater than O

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Example

Working hypothesis: Population influences the number of bankbranches in a town

Null hypothesis (Ho): Population do not have any influence on

the number of bank branches in a town.

Alternate hypothesis (H1): Population has significant effect on thenumber of bank branches in a town. A researcher formulates this

hypothesis only after rejecting the null hypothesis.

W di f h th i

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Wording of hypothesis

Simple versus complex hypotheses

Simple: expresses an expeted relationship between oneindependent and one dependent variable

A complex a prediction of a relationship between twoor more independent variables and or two or more

dependent variable Multivariate hypotheses involve multiple variables

Hypothesis should be worded in the present tense

Researcher make predictions about the relationship thatexist in the population and not just about therelationship that will be revealed in a particular sample


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Directionl versus nondirectional hypotheses

Directional, is one that specifies not only the existence butthe expected direction of the relationship betweenvariables

Older patient are at greater risk of falling than younger

ones A nondirectional hypothesis these hypothesis state the

prediction that apatients age and the risk of falling arerelated, they do not stipulate (specify as a condition)

whether the researcher think that older or youger patientsare at great risk

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Research versus null hypothesis

Research hypothesis,also refered to as

(substantive, declarative and scientific hypotheses)

are statements of expected relationships between

variables

Null hypothesis, there is no relationship betweenthe independent and dependent variables

Lib R h H th i F ti

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Library Research

Learning what is known

about the target behavior

Hypothesis Formation

Based on Lib. Rsh., propose

some new knowledge Research Design

Determine how to

obtain the data to testthe RH:

Data Collection

Carrying out the

research design and

getting the data.

Data AnalysisData collation and

statistical analysisHypothesis Testing

Based on design properties

and statistical results

Draw Conclusions

Decide how your new

knowledge changes

what is known about

the target behavior

the Research Loop

Novel RH:

Replication

Convergence

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Five types of statistical analysis

Descriptive

Inferential

Differences

Associative

Predictive

What are the characteristics of the respondents?

What are the characteristics of the population?

Are two or more groups the same or different?

Are two or more variables related in a systematic way?

Can we predict one variable if we know one or

more other variables?

G l P d f

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General Procedure for

Hypothesis Test

1. Formulate H0 (null hypothesis) and H1(alternative hypothesis)

2. Select appropriate test3. Choose level of significance

4. Calculate the test statistic (SPSS)

5. Determine the probability associated withthe statistic.

Determine the critical value of the teststatistic.

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General Procedure for

Hypothesis Test

6 a)Compare with the level of significance,

b) Determine if the critical value falls in the

rejection region. (check tables)

7 Reject or do not reject H0

8 Draw a conclusion

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The hypothesis the researcher wants to test is calledthe alternative hypothesis H1.

The opposite of the alternative hypothesis is the null

hypothesis H0 (the status quo)(no difference betweenthe sample and the population, or between samples).

The objective is to DISPROVE the null hypothesis.

The Significance Level is the Criticalprobability ofchoosing between the null hypothesis and the

alternative hypothesis

1. Formulate H1andH0

2 Select Appropriate Test

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The selection of a proper Test depends on:

Scale of the data

nominal interval

the statistic you seek to compare

Proportions (percentages)

means the sampling distribution of such statistic

Normal Distribution

T Distribution

2 Distribution Number of variables

Univariate

Bivariate

Multivariate

Type of question to be answered

2. Select Appropriate Test

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Testing for Differences Between Mean of the

Sample and Mean of the Population

The manager ofPepperoni Pizza Restauranthasrecently begun experimenting with a new method

of baking its pepperoni pizzas. He believes that the new method produces a

better-tasting pizza, but he would like to base a

decision on whether to switch from the old method

to the new method on customer reactions.

Therefore he performs an experiment.

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For 40 randomly selected customers who order apepperoni pizza for home delivery, he includes bothan old style and a free new style pizza in the order.

All he asks is that these customers rate the differencebetween pizzas on a -10 to +10 scale, where -10means they strongly favor the old style, +10 meansthey strongly favor the new style, and 0 means theyare indifferent between the two styles.

The Experiment

-10 +100

Old pizza New pizza

1 F l H d H

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One-Tailed Versus Two-Tailed Tests

The form of the alternative hypothesis can be either a

one-tailed or two-tailed, depending on what you are

trying to prove.

A one-tailed hypothesis is one where the only sample

results which can lead to rejection of the null hypothesis

are those in a particular direction, namely, those where

the sample mean rating is positive. A two-tailed test is one where results in either of two

directions can lead to rejection of the null hypothesis.

1. Formulate H1andH0

1 F l t H d H

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One-Tailed Versus Two-Tailed Tests -- continued

Once the hypotheses are set up, it is easy to detectwhether the test is one-tailed or two-tailed.

One tailed alternatives are phrased in terms of > or

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1. Formulate H1andH0 As the manager you would like to observe a

difference between both pizzas

If the new baking method is cheaper, you would

like the preference to be for it.

Null Hypothesis

AlternativeTwo tail

test

One tail

test= mu=population mean

H0 =0 (there is no differencebetween the old style and the new

style pizzas) (The difference between

the mean of the sample and the mean

of the population is zero)

H1 0 or H1>0

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What we want to test is whether consumers prefer the

new style pizza to the old style. We assume that there

is no difference (i.e. the mean of the population is

zero) and want to know whether our observed result is

significantly (i.e. statistically) different.

The one-sample t test is used to test whether the mean

of the sample is equal to a hypothesized value of the

population from which the sample is drawn.

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Accepting the null hypothesis that the pizzas are

equal, when they are really perceived to be differentby the customers of the entire population.

Type I Error

Rejecting the null hypothesis that the pizzas are

equal, (and saying that they are different or the new

style is better) when they really are perceived equal

by the customers of the entire population.

Type II error

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3. Choose Level of Significance

Significance Level selected is typically .05 or .01

i.e 5% or 1%

The ratings of 40 randomly selected customers

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produces the following table and statistics

From the summary statistics, we see that the sample mean is 2.10

and the sample standard deviation is 4.717

The positive sample meansuggests a slight preference for the newpizza, (alternative hypothesis) but there is a fair degree of variation.

What we dont know is whether this preference is significant

4 Calculate the Test Statistic

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816.240/717.4

010.2

valuet

4. Calculate the Test Statistic

t = X- 0s/n T(n-1)

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5. Determine the Probability-value (Critical Value)

We use the right tail

because the alternative isone-tailed of the greaterthan variety

The probability beyondthis value in the right tailof the tdistribution with

n-1 = 39 degrees offreedom isapproximately 0.004

The probability, 0.004,is thep-value for the

test. It indicates thatthese sample resultswould be very unlikelyif the null hypothesis istrue.

6 Compare with the level of significance ( 05)and

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1-Reject H0 Reject H0

Do not Reject H0

0

2.8162.023-2.023

/2/2

6. Compare with the level of significance, (.05)anddetermine if the critical value falls in the rejection region

Since the statistic falls in the rejection area we reject Ho

and conclude that the perceived difference between the

pizzas is significantly different from zero.

7. Reject or do not reject H0

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8 Conclusion

the sample evidence is fairly convincing thatcustomers, on average, prefer the new-style pizza.

Should the manager switch to the new-style pizza on

the basis of these sample results?

Depends. There is no indication that the new-style pizza

costs any more to make than the old-style pizza.

Therefore, unless there are reasons for not switching (for

example, costs) then we recommend the switch.

i

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Comparing Means

Suppose you are the brand manager forTylenol,and a recent TV ad tells the consumers that Advilis more effective (quicker) at treating headachesthan Tylenol.

An independent random sample of 400 people witha headache is given Advil, and 260 people reportthey feel better within an hour.

Another independent sample of 400 people is taken

and 252 people that tookTylenol reported feelingbetter.

Is the TV ad correct? Or, in other words, is there adifference between the means of the two samples

Hypothesis Test for Two

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Hypothesis Test for Two

Independent SamplesTest for mean difference:

Null Hypothesis

Alternative

H0 1= 2H1 12

Under H0 1- 2 = 0. So, the test concludes whether there is adifference between the means or not.

Comparison of means:

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Comparison of means:

Graphically

Are the means equal? Or are the differences simply

due to chance?


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2. Select Appropriate TestIn this example we have two independent samples

Other examples

populations of users and non-users of a brand differ in

perceptions of the brand

high income consumers spend more on the product than lowincome consumers

The proportion of brand-loyal users in Segment 1 (eg males)

is more than the proportion in segment II (e.g. females)

The proportion of households with Internet in Canada

exceeds that in USA

Can be used for examining differences between means and

proportions


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The two populations are sampled and the means and

variances computed based on the samples of sizes n1 and n2

If both populations are found to have the same variance

then a t-statistic is calculated.

The comparison of means of independent samples assumes

that the variances are equal.

If the variances are not known an F-test is conducted to

test the equality of the variances of the two populations.


0

F

f

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Unequal variances: The problem

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Tylenol vs Advil

We would need to test if the difference is zero or not.H0:A - T = 0;

H1:A - T 0

z= .65 - .63

(.65)(.35)/400+ (.63)(.37)/400= 0.66

pA= 260/400= 0.65

pT = 252/400= 0.63

For large samples the t-distribution approaches the normal

distribution and so the t-test and the z-test are equivalent.

Variability of random

means

mean 1mean 2t =

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Differences Between Groups

when Comparing Means Ratio scaled dependent variables

t-test

When groups are small

When population standard deviation is

unknown

z-testWhen groups are large

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Degrees of Freedom

d.f. = n - k

where:

n = n1 + n2

k = number of groups

The degrees of freedom is (n1 + n22)

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Tylenol vs Advil

- 0 0.66

= 0.10 Critical value = 1.64

1.64-1.64

/2/2 -1

Since 0.66 is less than the critical value of 1.64 we accept the null

hypothesis: there is no difference between Advil and Tylenol users

Test for Means Difference on Paired Samples

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Test for Means Difference on Paired Samples

What is a paired sample?

When two sets of observations relate to the same respondents

When you want to measure brand recall before and afteran ad campaign.

Shoppers consider brand name to be more important than

price Households spend more money on pizza than onhamburgers

The proportion of a banks customers who have a checking

account exceeds the proportion who have a savings account Since it is the same population that is being sampled theobservations are not independent.

The appropriate test is a paired-t-test

Example

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Q1. When purchasing golf clubs rate the importance 1-5 of priceQ2. When purchasing golf clubs rate the importance 1-5 of brand

Example

H0

H1 One tailed

H1 Two Tailed

There is no difference in importance between brand and

price

There is a difference in importance between

brand and price

Price is more important than brand

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What is an ANOVA?

One-way ANOVA stands for Analysis ofVariance

Purpose:

Extends the test formean difference betweentwo independent samples to multiple samples.

Employed to analyze the effects of

manipulations (independent variables) on arandom variable (dependent).

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What does ANOVA test? The null hypothesis tests whether the mean of all

the independent samples is equal

H0 1= 2 = 3..= n

H1 123.. n

The alternative hypothesis specifies that all themeans are not equal

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Definitions

Dependent variable: the variable we aretrying to explain, also known as responsevariable (Y).

Independent variable: also known asexplanatory variables or Factors (X).

Research normally involves determiningwhether the independent variable has an

effect on the variability of the dependentvariable

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Comparing Antacids

Non comparative ad:

Acid-off provides fast relief

Explicit Comparative ad:

Acid-off provides faster relief than Tums

Non explicit comparative adAcid-off provides the fastest relief

The maker of Acid-off, an antacid stomach remedy wants to

know which type of ad results in the most positive brand

attitude among consumers.

Three groups of people are exposed to one type of ad and

asked to rate their attitude towards the ad.

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Comparing Antacids

Brand

Attitude

Type of AdNon

Comparative

Explicit

Comparative

Non Explicit

Comparative

Means

The dependent variable (denoted by Y) is called the response

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The dependent variable (denoted by Y) is called the response

variable and in this case it is brand attitude (I.e. we want to

know what effect ad type has on attitude toward the brand)

The independent variables are called factors, in this case

type of ad: non-comparative, explicit comparative, non-explicit

comparative

The different levels of the factor are called treatments. In

this case the treatments are the different ratings for each of the

three types of ads.

There will be two sources of variation.

Variation within the treatment (e.g. within the non-

comparative ad etc.)

Variation between the treatments (I.e. between the three

types of ads)

The whole idea behind the analysis of variance is to compare

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The whole idea behind the analysis of variance is to compare

the ratio of between group variance to within group variance.

If the variance caused by the interaction between the samples is

much larger when compared to the variance that appears

within each group, then it is because the means are different.

groupswithinVariance

groupsbetweenVarianceF

Degrees of Freedom

The F statistic has DF for both numerator (between group) and

denominator (within group)

DF between group = (c-1) where c=number of groups

DF within group = (N-c) where N is sample size

Decomposition of the Total

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Independent Variable X

Categories Total Sample

X1 X2 X3 . Xc

Y1 Y1 Y1 . Y1 Y1Y2 Y2 Y2 . Y2 Y2

Yn Yn Yn . Yn Yn

Y1 Y2 Y3 Yc Y

Decomposition of the Total

Variation

Total

Variation

SSy

Between Category Variation SSbetween

Category

Mean

Within

Category

Variation

SSwithin

Grand

Mean

ANOVA T t

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ANOVA TestThe null hypothesis would be tested with

the F distribution

df(c-1)/(N-c)

Reject H0F distribution

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One way ANOVA investigates:Main effects

factor has an across-the-board effect

e.g., type of ad

Or age

or involvement

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A TWO-WAY ANOVA investigates:

INTERACTIONS

effect of one factor depends on another factor

e.g., larger advertising effects for those with no

experience

importance of price depends on income level and

involvement with the product

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Testable means that there must be some way to

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Testable -- means that there must be some way to

way to collect the data to evaluate the RH

Falsifiable -- means that the RH: must possibly be wrong!

General Definition

a tentative explanation or a guess about the target behavior

MUST BE TESTABLE ( falsifiable ) !!!

3 Different Kinds

Attributive

Associative

Causal

Attributive Research Hypothesis

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states that a behavior exists, can be measured, and

can be distinguished from similar other behaviors univariate hypothesis (one variable)

Evidence to support ...

need to demonstrate a technique that allows properlytrained researchers to reliably record and score the

behavior

with what type of knowledge about behavior does

this correspond ?? _________________

Associative Research Hypothesis

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states that a relationship exists between two

behaviors -- that knowing the amount or kind of onebehavior helps you to predict the amount or kind of

the other behavior

bivariate hypothesis (two variables) Evidence to support

show that there is a reliable statistical relationship betwee

the two variables

with what type of knowledge about behavior does

this type of RH correspond ??

Causal Research Hypothesis

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states that differences in the amount or kind of one

behavior cause/produce/create/change/etc.differences in amount or kind of the other behavior

bivariate hypothesis -- causal behavior

& effectbehavior

Evidence needed to support a causal hypothesis...

temporal precedence (cause precedes effect)demonstrate a statistical relationship

elimination of alternative explanations (no other viable

causes/explanations of the effect)

Library Research


Hypothesis Formation

Based on Lib Rsh propose

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about the target behavior

Based on Lib. Rsh., propose

some new knowledge Research Design

Determine how to

obtain the data to testthe RH:

Data Collection

Carrying out theresearch design and

getting the data.

Data Analysis

Data collation and

statistical analysisHypothesis Testing

Draw Conclusions

Decide how your new

knowledge changes

what is known about

the target behavior

the Research Loop

Novel RH:

Replication

Convergence

Documents

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