A research design provides a framework or blueprint for conducting a research project. It details the procedures necessary for obtaining needed information to structure or solve research problems. A research design constitutes a plan or blueprint that specifies methods and procedures for collecting and analyzing data. Key components of a research design include defining needed information, designing exploratory, descriptive, and causal phases, specifying measurement and scaling procedures, developing data collection instruments, specifying sampling processes and sample sizes, and developing a data analysis plan. Research designs fall into three main categories: exploratory, descriptive, and causal.
RESEARCH DESIGN , Sampling Designs , Dependent and Independent Variables, Extraneous Variables, Hypothesis, Exploratory Research Design, Descriptive and Diagnostic Research
Exploratory Research Design - Meaning and MethodsSundar B N
This ppt contains Exploratory Research Design which covers Introduction to Exploratory Research, Meaning of Exploratory Research, Techniques of Exploratory Research, Examples of Exploratory Research, Methods of Designing Exploratory Research
caling is the branch of measurement that involves the construction of an instrument that associates qualitative constructs with quantitative metric units. Scaling evolved out of efforts in psychology and education to measure “unmeasurable” constructs like authoritarianism and self-esteem. In many ways, scaling remains one of the most arcane and misunderstood aspects of social research measurement. And, it attempts to do one of the most difficult of research tasks – measure abstract concepts.
Most people don’t even understand what scaling is. The basic idea of scaling is described in General Issues in Scaling, including the important distinction between a scale and a response format. Scales are generally divided into two broad categories: unidimensional and multidimensional. The unidimensional scaling methods were developed in the first half of the twentieth century and are generally named after their inventor. We’ll look at three types of unidimensional scaling methods here:
Thurstone or Equal-Appearing Interval Scaling
Likert or “Summative” Scaling
Guttman or “Cumulative” Scaling
In the late 1950s and early 1960s, measurement theorists developed more advanced techniques for creating multidimensional scales. Although these techniques are not considered here, you may want to look at the method of concept mapping that relies on that approach to see the power of these multivariate methods.
RESEARCH DESIGN , Sampling Designs , Dependent and Independent Variables, Extraneous Variables, Hypothesis, Exploratory Research Design, Descriptive and Diagnostic Research
Exploratory Research Design - Meaning and MethodsSundar B N
This ppt contains Exploratory Research Design which covers Introduction to Exploratory Research, Meaning of Exploratory Research, Techniques of Exploratory Research, Examples of Exploratory Research, Methods of Designing Exploratory Research
caling is the branch of measurement that involves the construction of an instrument that associates qualitative constructs with quantitative metric units. Scaling evolved out of efforts in psychology and education to measure “unmeasurable” constructs like authoritarianism and self-esteem. In many ways, scaling remains one of the most arcane and misunderstood aspects of social research measurement. And, it attempts to do one of the most difficult of research tasks – measure abstract concepts.
Most people don’t even understand what scaling is. The basic idea of scaling is described in General Issues in Scaling, including the important distinction between a scale and a response format. Scales are generally divided into two broad categories: unidimensional and multidimensional. The unidimensional scaling methods were developed in the first half of the twentieth century and are generally named after their inventor. We’ll look at three types of unidimensional scaling methods here:
Thurstone or Equal-Appearing Interval Scaling
Likert or “Summative” Scaling
Guttman or “Cumulative” Scaling
In the late 1950s and early 1960s, measurement theorists developed more advanced techniques for creating multidimensional scales. Although these techniques are not considered here, you may want to look at the method of concept mapping that relies on that approach to see the power of these multivariate methods.
Motivation in research - Research Methodology - Manu Melwin Joymanumelwin
What makes people to undertake research? This is a question of fundamental importance. The possible motives for doing research may be either one or more of the following:
Desire to get a research degree along with its consequential benefits.
A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research with economy in procedure.
It is a conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data.
Scaling is the process of measuring or ordering entities with respect to quantitative attributes or traits. With comparative scaling, the items are directly compared with each other .In non -comparative scaling each item is scaled independently of the others.
v When to Choose a Statistical Tests OR When NOT to Choose? v Parametric vs. Non-Parametric Tests (Comparison)
v Parameters to check when Choosing a Statistical Test:
- Distribution of Data
- Type of data/Variable
- Types of Analysis (What’s the hypothesis)
- No of groups or data-sets
- Data Group Design
v Snapshot of all statistical test and “How” to Choose using above parameters v Explanation using Examples:
- Mann Whitney U Test
- Wilcoxon Sign Rank Test
- Spearman’s co-relation
- Chi-Square Test
v Conclusion
Motivation in research - Research Methodology - Manu Melwin Joymanumelwin
What makes people to undertake research? This is a question of fundamental importance. The possible motives for doing research may be either one or more of the following:
Desire to get a research degree along with its consequential benefits.
A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research with economy in procedure.
It is a conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data.
Scaling is the process of measuring or ordering entities with respect to quantitative attributes or traits. With comparative scaling, the items are directly compared with each other .In non -comparative scaling each item is scaled independently of the others.
v When to Choose a Statistical Tests OR When NOT to Choose? v Parametric vs. Non-Parametric Tests (Comparison)
v Parameters to check when Choosing a Statistical Test:
- Distribution of Data
- Type of data/Variable
- Types of Analysis (What’s the hypothesis)
- No of groups or data-sets
- Data Group Design
v Snapshot of all statistical test and “How” to Choose using above parameters v Explanation using Examples:
- Mann Whitney U Test
- Wilcoxon Sign Rank Test
- Spearman’s co-relation
- Chi-Square Test
v Conclusion
A sales quota is a quantitative goal assigned to a sales unit relating to a particular period of time.
A sales territory represents a group of customers or markets or geographical areas
“Sales promotion are those marketing activities that provide extra value or incentives to the sales force, the distributors, or the ultimate consumer and can stimulate immediate sales”.
“Sales promotion includes marketing devices for stimulating buyer interest and product trial.”
Transportation is the operational area of logistics that
geographically moves and positions inventory. Transportation system is the physical link connecting a company with the customers, raw material suppliers, plants, ware houses and
distribution channel members. The five basic transportation modes are Rail, Highway, Water, Pipeline.
Sales forecast is about estimating future sales.
Sales forecast is an estimated unit of sales in either rupees or number of units which could be sold for a specific period of time
Better sales forecasts
Enables a company to perform better
Make more informed decisions; and
Serves as a basis for determining the short run and the long term performance of a organization
Provide inputs for expected sales for a particular company or industry
Sales organization is a part of the total organization which is given the responsibility of selling of products manufactured by a company
It is another organization within the larger organization which is given the responsibility of selling function
It involves people working together for attaining the sales objectives of the company
It is concerned with planning, organizing, leading and controlling the activities of the sales force
Sales persons follow a sequence of activities while making a sale and these may be defined as different phases followed by salesperson.
A cycle start with prospect/potential customer identification, to converting him to a customer.
The sequential order of the steps may vary across selling situations
Objectives of sales management are derived from the organizations marketing objectives.
Ultimate sales objective of an organisation is to have a decent growth in sales.
More specifically, sales management objectives can be grouped under:
Quantitative Objectives (Short-term)
Qualitative Objectives (Long-term)
Sales and Sales Management: Meaning and DefinitionAmitabh Mishra
A sale is the pinnacle activity involved in selling products/services in return for money or other compensation. It is an act of completion of a commercial activity.
Sales is everything that you do to close the sale and get a signed agreement or contract.
Product Life Cycle shows the stages that products go through from development to withdrawal from the market.
The company’s differentiation and positioning strategies must change as the product, market, competitors changes over time.
Targeting, Differentiation and PositioningAmitabh Mishra
Once the firm has identified its market segment opportunity , it has to decide how many and which one to target.
•“Market targeting is a process of evaluating the market segments and identify one or more market segments to serve”.
Marketing Environment by Dr. Amitabh MishraAmitabh Mishra
•“Marketing Environment includes the actors and forces that affect management’s ability to build and maintain successful relationships with target customers”.
•These factors may be-
–Controllable: which the company can control
–Non-controllable: which the company can monitor and respond.
“Marketing Mix is set of marketing tools that the firm uses to pursue its marketing objectives in the target market”
"Marketing mix is a general phrase used to describe the different kinds of choices organizations have to make in the whole process of bringing a product or service to market”.
Companies approach and conduct business in different ways in order to achieve their organizational goals.
•Every company can have different ideas or philosophy. For example-
•A particular company can have its idea or philosophy that if the production is done on a large scale, the cost would be less and the product would be sold automatically.
Marketing is “The management process of anticipating, identifying and satisfying customer requirements profitably” (CIM, 2001).
•According to “The American Marketing Association” -“Marketing is the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large” (AMA, 2007).
Dr
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
2. Research Design: Definition
• “A research design is a framework or blueprint for
conducting the research project. It details the procedures
necessary for obtaining the information needed to
structure or solve research problems”.
• “Research design constitute the blue print for the
collection, measurement and analysis of data”
2Dr. Amitabh Mishra
3. A research design is:
• A framework for the research
• A plan of action.
• Master plan that specifies the methods and
procedures for collecting and analyzing the
needed information
• A strategy for how the data will be collected.
Dr. Amitabh Mishra 3
4. Components of a Research Design
• Define the information needed.
• Design the exploratory, descriptive, and/or causal phases of the
research
• Specify the measurement and scaling procedures.
• Construct and pretest a questionnaire (interviewing form) or an
appropriate form for data collection.
• Specify the sampling process and sample size.
• Develop a plan of data analysis.
4Dr. Amitabh Mishra
6. • The choice of the most appropriate design
depends largely on the objectives of the
research and how much is known about the
problem and research objectives.
Dr. Amitabh Mishra 6
7. • Three traditional categories:
–Exploratory
–Descriptive
–Causal
Dr. Amitabh Mishra 7
8. A Classification of Research Designs
Single Cross-
Sectional Design
Multiple Cross-
Sectional Design
Research Design
Conclusive
Research Design
Exploratory
Research Design
Descriptive
Research
Causal Research
Cross-Sectional
Design
Longitudinal
Design
8Dr. Amitabh Mishra
9. Exploratory & Conclusive Research Differences
Objective:
Character-
istics:
Findings/
Results:
Outcome:
To provide insights and
understanding
Information needed is defined only
loosely. Research process is flexible
and unstructured. Sample is small
and non-representative. Analysis of
primary data is qualitative
Tentative
Generally followed by further
exploratory or conclusive research
To test specific hypotheses and examine
relationships
Information needed is clearly defined.
Research process is formal and
structured. Sample is large and
representative. Data analysis is
quantitative
Conclusive
Findings used as input into decision
making
Exploratory Conclusive
9Dr. Amitabh Mishra
10. A Comparison of Basic Research Designs
Objective:
Characteristics:
Methods:
Discovery of ideas and
insights
Flexible, versatile
Often the front end of
total research design
Expert surveys
Pilot surveys
Case studies
Secondary data:
qualitative analysis
qualitative research
Describe market
characteristics or
functions
Marked by the prior
formulation of specific
hypotheses
Preplanned and
structured design
Secondary data:
quantitative analysis
Surveys
Panels
Observation and other
data
Determine cause
and effect
relationships
Manipulation of
independent
variables, effect on
dependent
variables
Control mediating
variables
Experiments
Exploratory Descriptive Causal
10Dr. Amitabh Mishra
12. • “Exploration is particularly useful when
researchers lack a clear idea of problem they
will meet during the study. Through
exploration researcher develop concept,
establish priorities, develop operational
definitions and improve final research design”
Dr. Amitabh Mishra 12
13. Characteristics of Exploratory Research
• It is usually conducted when the researcher does
not know much about the problems
• Exploratory research seeks to discover new
relationship
• Exploratory research looks for hypothesis
Dr. Amitabh Mishra 13
14. • Exploratory research is flexible with respect to
methods
• It rarely involves structured questionnaire, large
samples and probability sampling
• The research structure is qualitative
• It should be followed by descriptive and causal
research
Dr. Amitabh Mishra 14
15. Purpose of Exploratory Research
– To gain background information
– Research problem formulation
– Developing hypothesis
– Identifying and defining key research variables
Dr. Amitabh Mishra 15
16. Uses of Exploratory Research
• Formulate a problem or define a problem more precisely
• Identify alternative courses of action
• Develop hypotheses
• Isolate key variables and relationships for further
examination
• Gain insights for developing an approach to the problem
• Establish priorities for further research
16Dr. Amitabh Mishra
17. Methods of Exploratory Research
• Secondary Data Analysis
• Experience Surveys or Survey of experts
– Focus Groups
– Depth interviews
– Projective Techniques
• Case Analysis
17Dr. Amitabh Mishra
19. Descriptive Research
• Descriptive research is undertaken to describe some
thing usually market characteristics or functions.
Dr. Amitabh Mishra 19
20. Characteristics of Descriptive Research
• In contrast to exploratory research it is marked
by-
– Clear statement of problem
– Specific hypothesis, and
– Detailed information needed
• It assumes that researcher has prior knowledge
about the problem situation
Dr. Amitabh Mishra 20
21. • It is pre planned and structured
• It is based on large representative sample
• Specific hypothesis are formulated before
conducting the research
Dr. Amitabh Mishra 21
22. • It requires clear specification of 6 W’s-
1. Who- should be surveyed
2. What- what information should be obtained
3. When- should the information be obtained
4. Where- from where (house, shopping mall, market etc.)
5. Why-why we are obtaining information from
respondents
6. Way- in what way we are going to obtain the
information i.e personal interview, telephone, mail
survey etc .
Dr. Amitabh Mishra 22
23. Purpose/Use of Descriptive Research
• To describe the characteristics of relevant groups, such as
consumers, salespeople, organizations, or market areas .
(ex- developing profile of heavy users of a prestigious store)
• To estimate the percentage of units in a specified population
exhibiting a certain behavior .
(% of heavy users of a prestigious store who also patronize
discount departmental store)
23Dr. Amitabh Mishra
24. • To determine the perceptions of product characteristics
(Ex- how do household perceive the various
departmental stores in terms of salient features of the
choice)
• To determine the degree to which marketing variables
are associated
(to what extent is shopping at department store is
related to eating out)
Dr. Amitabh Mishra 24
25. • To make specific predictions
(ex- what will be retail sales of reliance super for
fashion clothing in Noida area)
Dr. Amitabh Mishra 25
26. Methods of Descriptive Research
• Secondary data analyzed in a quantitative, as
opposed to a qualitative, manner
• Surveys
• Panels
• Observational and other data
26Dr. Amitabh Mishra
27. Types of Descriptive Research
Dr. Amitabh Mishra 27
Single Cross-
Sectional Design
Multiple Cross-
Sectional Design
Descriptive
Research
Cross-Sectional
Design
Longitudinal
Design
28. Cross-Sectional Designs
• “Cross-sectional research design involve the collection of
information from any given sample of population elements only
once”.
• Cross-sectional studies take “snapshots” of the population at a
point in time.
• It is most frequently used descriptive design in marketing
research.
28Dr. Amitabh Mishra
29. EXAMPLE: 1
How did American people rate the performance of
President “Barack Obama” immediately after killing of
“Osama-bin-Laden”
Dr. Amitabh Mishra 29
30. • “In single cross-sectional designs, there is only one sample of
respondents and information is obtained from this sample
only once”. This is also called sample survey research design.
• In multiple cross-sectional designs, there are two or more
samples of respondents, and information from each sample is
obtained only once. Often, information from different
samples is obtained at different times.
Dr. Amitabh Mishra 30
31. Longitudinal Designs
• In longitudinal design a fixed sample (or samples) of
population elements is measured repeatedly on the same
variables.
• i.e. Same people are studied over time and same variables
are measured.
• A longitudinal design differs from a cross-sectional design in
that the sample or samples remain the same over time.
31Dr. Amitabh Mishra
32. EXAMPLE:1
How did American people change the view of President Barack
Obama’s performance during financial crisis.
Dr. Amitabh Mishra 32
33. EXAMPLE: 2
How did Indian change the view of Prime Minister Narender
Modi’s performance during demonetization
Dr. Amitabh Mishra 33
34. Advantages and Disadvantages of Longitudinal and
Cross-Sectional Designs
Evaluation
Criteria
Cross-Sectional
Design
Longitudinal
Design
Detecting Change
Large amount of data collection
Accuracy
Representative Sampling
Response bias
-
-
-
+
+
+
+
+
-
-
Note: A “+” indicates a relative advantage over the other design,
whereas a “-” indicates a relative disadvantage.
34Dr. Amitabh Mishra
36. Causal Research
• “Causal research is conducted to identify the
cause and effect relationship between two or
more business variables”.
• Major objective of causal research is to obtain
evidence regarding cause and effect relationship.
Dr. Amitabh Mishra 36
37. • Example- A common assumption that a decrease in price
will lead to increase in sales and market share does not hold
true in certain competitive environment.
Dr. Amitabh Mishra 37
39. • Causality is “a situation when occurrence of X
increases the probability of occurrence of Y”.
• A statement such as "X causes Y" shows causality.
• Experimentation is commonly used to infer causal
relationships.
Dr. Amitabh Mishra 39
40. Concept of Causality
A statement such as "X causes Y" will have the
following meaning to an ordinary person and to a
scientist.
____________________________________________________
Ordinary Meaning Scientific Meaning
____________________________________________________
X is the only cause of Y. X is only one of a number of
possible causes of Y.
X must always lead to Y The occurrence of X makes the
(X is a deterministic occurrence of Y more probable
cause of Y). (X is a probabilistic cause of Y).
It is possible to prove We can never prove that X is a
that X is a cause of Y. cause of Y. At best, we can
infer that X is a cause of Y.
40Dr. Amitabh Mishra
42. • Some basic concepts needed to understand causal
research are-
1. Independent variables (Treatment)
2. Test units
3. Dependent variables
4. Extraneous variables
5. Experiment
Dr. Amitabh Mishra 42
43. Independent Variable/Treatment
• “Independent variables are variables or alternatives that are
manipulated and whose effects are measured and compared”.
• Independent variables are those variables which the
researcher has control over and wishes to manipulate.
• Example: The 4 P’s i.e. level of advertising expenditure; type of
advertising appeal; price; product features, etc.
5-43Dr. Amitabh Mishra
44. Test units
• “Test units are individuals, organizations or other
entities whose response to the independent variable
or treatment is being examined”.
• Test units may include-
– Consumers,
– Stores or
– Geographical areas.
Dr. Amitabh Mishra 44
45. Dependent Variables
• “Dependent variables are the variables which measure
the effect of the independent variables on the test
units”.
• Example- sales, profits, and market shares
• Dependent variables are those variables that we have
little or no direct control over, yet we have a strong
interest.
Dr. Amitabh Mishra 5-45
46. Extraneous Variables
• “Extraneous variables are all variables other than the independent
variables that affect the response of the test units”.
• “Extraneous variables are those variables that may have some effect on a
dependent variable yet are not independent variables”.
• Example- store size, store location, and competitive effort.
• Extraneous variables must be controlled through proper experimental
design.
5-46Dr. Amitabh Mishra
47. Experiments
• An experiment is defined as “Manipulating an
independent variable to see how it affects a
dependent variable, while also controlling the effects
of additional extraneous variables”.
Dr. Amitabh Mishra 5-47
48. Experimental Design
• Experimental design is a procedure for
devising an experimental setting such that a
change in a dependent variable may be
attributed solely to the change in an
independent variable.
5-48Dr. Amitabh Mishra
49. Uses of Causal Research
• To understand which variables are the cause (independent
variables) and which variables are the effect (dependent
variables) of a phenomenon
• To determine the nature of the relationship between the
causal variables and the effect to be predicted.
Dr. Amitabh Mishra 49
50. Types of Experimental Design
•Experimental design are of 4 types
1. Pre-Experimental Designs
2. True Experimental Designs
3. Quasi-Experimental Designs
4. Statistical (Correlational and Ex Post Facto)
Designs
51. Experimental Design
• Symbols of an experimental design:
• O = measurement of a dependent variable
• X = manipulation, or change, of an independent variable
• R = random assignment of subjects to experimental and
control groups
• E = experimental effect
59. Quasi-Experimental Designs
Time Series Experimental Design
To determine the influence of a variable
introduced only after a series of initial of
observations and only where one group is
available.
O1 O2 O3 O4 X
O5 O6 O7 O8
60. Quasi-Experimental Designs
Control Group Time Series Design
To bolster the validity of the previous design with
the addition of a control group.
O1 O2 O3 O4 X
O5 O6 O7 O8
O1 O2 O3 O4
O5 O6 O7 O8
62. Correlational and Ex Post
Facto Designs
Casual-Comparative
Correlational Studies
To seek for cause-effect relationships
between two sets of data.
OA = OB
63. Correlational and Ex Post
Facto Designs Designs
Ex Post Facto Studies
To search backward from consequent data for
antecedent causes.
Direction of the
Research Effort
O
Other Possible Direction
Other Possible Direction
Origin
65. Conditions for Causality
• Before assuming causality, three conditions
must be satisfied-
1. Concomitant variation.
2. The time order of occurrence.
3. The absence of other possible causal factors.
Dr. Amitabh Mishra 65
66. • Concomitant variation is the extent to which a cause,
X, and an effect, Y, occur together or vary together in
the way predicted by the hypothesis under
consideration.
Dr. Amitabh Mishra 66
67. • The time order of occurrence condition states that
the causing event must occur either before or
simultaneously with the effect; it cannot occur
afterwards.
Dr. Amitabh Mishra 67
68. • The absence of other possible causal factors means
that the factor or variable being investigated should
be the only possible causal explanation.
• i.e all other possible factors will be assumed
constant or held controlled.
68Dr. Amitabh Mishra
69. Validity in Experimentation
While conducting an experiment, researcher in interested in insuring-
1.Internal validity
2.External validity
Dr. Amitabh Mishra 69
70. Internal validity
• 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.
Dr. Amitabh Mishra 70
71. External validity
• External validity refers to whether the cause-and-effect
relationships found in the experiment can be generalized.
• And if so, To what populations, settings, times, independent
variables, and dependent variables can the results be
projected?
71Dr. Amitabh Mishra
72. 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.
72Dr. Amitabh Mishra
73. A Comparison of Basic Research Designs
Objective:
Characteristics:
Methods:
Discovery of ideas and
insights
Flexible, versatile
Often the front end of
total research design
Expert surveys
Pilot surveys
Case studies
Secondary data:
qualitative analysis
qualitative research
Describe market
characteristics or
functions
Marked by the prior
formulation of specific
hypotheses
Preplanned and
structured design
Secondary data:
quantitative analysis
Surveys
Panels
Observation and other
data
Determine cause
and effect
relationships
Manipulation of
independent
variables, effect on
dependent
variables
Control mediating
variables
Experiments
Exploratory Descriptive Causal
73Dr. Amitabh Mishra
74. Test Marketing
• Test marketing is the phrase commonly used to
indicate an experiment, study, or test that is
conducted in a field setting.
• Uses of test markets
– To test sales potential for a new product or service
– To test variations in the marketing mix for a product or
service
74Dr. Amitabh Mishra