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Understanding Research Methodology
Live webinar series-2
CMA Dr. Kameswararao.M
MBA, ACMA, CertIFR, Ph.D
8th May, 2021, from 6pm to 8pm
Agenda
Part 1 Research Methodology & Research Design
Part 2 Data Analysis using statistics
Part 3 Interpretation of the outcome of the analysis
…Research Methodology…
Research Methodology
Research methodology Procedure & technique
Data collection methods
Sources of data.
Data to collect.
Analyzing the data
Factors influence research methodology
 Problem statement.
 Objectives.
 Scope.
 Limitations.
Selection of research methodology
Explanatory Research
Confirmatory Research
It is a process of investigating a problem that has not been studied thoroughly in the past. It is
usually conducted to have a better understanding of the existing problem, but does not lead to a
conclusive result.
 A research to find out the degree of job satisfaction of an employee.
 A survey on mobile phone specifications that a customer prefers before buying.
 A deeper insight on customer’s reaction on introduction of new product in a FMCG sector.
Examples:
Confirmatory research is an approach to the validity of already made hypothesis, known as
a priori hypothesis. This research method is normally based on previous studies, to confirm an
existing result or theory. The benefit is that it makes the results more meaningful.
 A research study to find the relationship between movement of stock prices and market risk.
 A study on the corporate brand value before and after the new market strategies.
 An investigation on the cause and effect on psychological stress on students through online
education.
Examples:
Selection of research methodology
Research Methodology
Explanatory Confirmatory
Researcher aims to uncover the
possible relationship between the
variables.
Researcher has a clear idea about
the possible relationship between
the variables.
Objective
Nature
Type of data
Application of
statistics
Mainly attempts to explain the
observations.
Mainly attempts to explain &
confirms the observations.
Qualitative data Quantitative data
No application of statistics Statistical tools are required.
Selection of research methodology
Research Methodology
Quantitative Qualitative
Focuses of describing individual
experiences and believes.
Focuses on describing the
characteristics of the population.
Analytical
objective
Questions
Data collection
method
Form of data
produced
Mainly open-ended questions. Mainly closed-ended questions.
In-depth interviews, focused
groups, deep observations
Questionnaires and surveys
Descriptive data Numerical data.
…Research Design…
Meaning of research design
 A careful plan to structure the research activity highly aimed to
improve the quality of the research.
 It is a blueprint of research project.
 Contains the plan and strategies of research project to complete
within the pre-defined time frame and cost by utilizing the resources
efficiently.
Categories of Research Design
 Root cause analysis.
 Impact analysis.
 Root cause and Impact analysis.
 Pre and Post analysis.
 Describing/review a system or a mechanism or a process or a technology.
 Designing a new process.
 Study the relationship between two or more variables.
 Cost, benefit analysis (CBA).
 Roles, challenges, responsibilities of a system/technology/process.
Contents of Research Design
Research
Design
Research
objectives
Population &
sample size
Methods of
data
collection
Outcome &
action to be
taken
Data analysis
Type of data
needed
Time & Cost
Meaning of research design
 A careful plan to structure the research activity highly aimed to
improve the quality of the research.
 It is a blueprint of research project.
 Contains the plan and strategies of research project to complete
within the pre-defined time frame and cost by utilizing the resources
efficiently.
Types of Research Design
 Describing a given or a specific situation.
 No root cause analysis or impact analysis.
 Presenting a data that is studied in terms of, “How much?”, “How regularly?”, “What
percentage?”, “What is?”, “What time?”
Descriptive research design:
 Surveys
 Observations
 Case studies
 Customer survey about a new features of a product.
 Explaining the functionality of a new software application/equipment/any other asset.
 Studying the stock markets based on a specific parameter.
 Studying the human behavior at work place under stress conditions.
Types of Research Design
 Describing a given or a specific situation.
 Primary focus on root cause analysis or impact analysis.
 Considered as highly practical research method.
 Studies relationship between two or more variables.
 Concludes with suggestions or action point.
Experimental research design:
 Observations.
 Simulations.
 Survey.
 Patients health condition before and after vaccination.
 Corporate brand value before and after change management .
 Employee performance measurement.
 Students psychology before and after the COVID19 pandemic.
Types of Research Design
 Describing a given or a specific situation.
 Considered as highly quantitative research method.
 Studies relationship between two or more variables in terms of dependency of one variable
over other
 Concludes with suggestions.
Correlational research design:
 Journals/periodicals/new papers
 Observations.
 Survey.
 Movement Stock prices Vs. stock indices.
 Study on relationship between employee age, marital status, past experience on
Organization performance.
 Study the pattern of sales in employee performance.
Sampling Design
 Exploring for the first time.
 Intended to discover some ideas and insights on a situation which has no past data.
 Studies relationship between two or more variables in terms of dependency of one variable
over other
 Concludes with suggestions.
Exploratory research design:
 Journals/periodicals/new papers
 Observations.
 Survey.
 A study into the role of social networking sites as an effective marketing communication
channel
 An investigation into the ways of improvement of quality of customer services within
hospitality sector.
 An assessment of the role of corporate social responsibility on consumer behavior in
pharmaceutical industry.
…Sample Design…
Sampling Design
 A process of selection of sample size/units that are related to
individuals/locations/entities .
 Selection of a suitable sample design method ensures that the samples you
invest your time and money into collecting can support the inferences you
want to make.
 It forms an important basis of observation, survey and analysis of the data.
Determinants of sample size
 Population size  Restricted to a specific control variable.
 Margin of error  the percentage of error in the data you allow. Usually it is
5%
 Confidence level  It represents how confident you want to be that the actual
mean falls within the margin of error. Usually it is 90% or 95% or &99%.
 Standard deviation  This has to be ascertained to find out how much
deviation from actual mean.
Calculation of Sample Size
Necessary Sample Size = (Z-score)2 * StdDev*(1-StdDev) / (margin of error)2
Step -1: First you need to find the Z-Score
Step -2: Use the formula to calculate sample size
Here’s a worked example, assuming you chose a 95% confidence level, .5 standard
deviation, and a margin of error (confidence interval) of +/- 5%.
((1.96)2 x .5(.5)) / (.05)2  (3.8416 x .25) / .0025  .9604 / .0025  384.16
385 respondents are needed
The z-score at various confidence levels are (published and standard values)
@ +90% CL = 1.645
@ +95% CL = 1.96
@ +99% CL = 2.576
Calculation of Sample Size
n = Required Sample size,
z = Z-Score
p = Population Proportion
q = 1-p
e = margin of error
…Data Analysis tools in statistics…
Data Analysis Tools
Data Analysis tools comparision.
Data Analysis Tools
…Testing of hypothesis…
Testing of hypothesis
Testing of hypothesis
Testing of hypothesis
Testing of hypothesis
Parametric Test Non-parametric Test
Evaluate hypothesis for a
particular parameter, usually the
population mean.
Evaluate hypothesis for entire
population distributions.
It considers only quantitative
data.
It considers both quantitative
and qualitative data.
Require assumptions about the
distributional characteristics of
the population in terms of
normal shape and equal
variance.
Require no assumptions. It is
used with non-normal
distributions and when
variances of the groups are not
equal.
More powerful than non-
parametric tests when
assumptions are met.
Generally easy to compute but
less effective than parametric
test.
…Interpretation…
Interpretation of data
 Summarize the outcome of the research in a much professional manner.
 Straight forward, exactly related to the outcome of the research.
 Use generally accepted professional language.
 Must clearly depicts the objective of the research.
 Components of interpretation:
 Summary of findings
 Concluding observations
 Suggestions or action points.
…Conclusion…
Key takeaways
 Define explicitly the problem statement, objectives, scope and limitations at
the inception of the research project.
 Always try to choose Confirmatory research as it has greater weightage.
 Make sure to include quantitative data and qualitative data in your project.
 Research design is a strategy that aims to bring quality in the research.
 Always draw a justifiable sample size using the formula.
 Apply relevant statistical tools according to the data.
 Cross check the results of analysis by taking help from experts.
 Draw your conclusions straight to the point of observation.
 Become expert in MS-Excel.
…Questions?…

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Research methodology presentation

  • 1. Understanding Research Methodology Live webinar series-2 CMA Dr. Kameswararao.M MBA, ACMA, CertIFR, Ph.D 8th May, 2021, from 6pm to 8pm
  • 2. Agenda Part 1 Research Methodology & Research Design Part 2 Data Analysis using statistics Part 3 Interpretation of the outcome of the analysis
  • 4. Research Methodology Research methodology Procedure & technique Data collection methods Sources of data. Data to collect. Analyzing the data
  • 5. Factors influence research methodology  Problem statement.  Objectives.  Scope.  Limitations.
  • 6. Selection of research methodology Explanatory Research Confirmatory Research It is a process of investigating a problem that has not been studied thoroughly in the past. It is usually conducted to have a better understanding of the existing problem, but does not lead to a conclusive result.  A research to find out the degree of job satisfaction of an employee.  A survey on mobile phone specifications that a customer prefers before buying.  A deeper insight on customer’s reaction on introduction of new product in a FMCG sector. Examples: Confirmatory research is an approach to the validity of already made hypothesis, known as a priori hypothesis. This research method is normally based on previous studies, to confirm an existing result or theory. The benefit is that it makes the results more meaningful.  A research study to find the relationship between movement of stock prices and market risk.  A study on the corporate brand value before and after the new market strategies.  An investigation on the cause and effect on psychological stress on students through online education. Examples:
  • 7. Selection of research methodology Research Methodology Explanatory Confirmatory Researcher aims to uncover the possible relationship between the variables. Researcher has a clear idea about the possible relationship between the variables. Objective Nature Type of data Application of statistics Mainly attempts to explain the observations. Mainly attempts to explain & confirms the observations. Qualitative data Quantitative data No application of statistics Statistical tools are required.
  • 8. Selection of research methodology Research Methodology Quantitative Qualitative Focuses of describing individual experiences and believes. Focuses on describing the characteristics of the population. Analytical objective Questions Data collection method Form of data produced Mainly open-ended questions. Mainly closed-ended questions. In-depth interviews, focused groups, deep observations Questionnaires and surveys Descriptive data Numerical data.
  • 10. Meaning of research design  A careful plan to structure the research activity highly aimed to improve the quality of the research.  It is a blueprint of research project.  Contains the plan and strategies of research project to complete within the pre-defined time frame and cost by utilizing the resources efficiently.
  • 11. Categories of Research Design  Root cause analysis.  Impact analysis.  Root cause and Impact analysis.  Pre and Post analysis.  Describing/review a system or a mechanism or a process or a technology.  Designing a new process.  Study the relationship between two or more variables.  Cost, benefit analysis (CBA).  Roles, challenges, responsibilities of a system/technology/process.
  • 12. Contents of Research Design Research Design Research objectives Population & sample size Methods of data collection Outcome & action to be taken Data analysis Type of data needed Time & Cost
  • 13. Meaning of research design  A careful plan to structure the research activity highly aimed to improve the quality of the research.  It is a blueprint of research project.  Contains the plan and strategies of research project to complete within the pre-defined time frame and cost by utilizing the resources efficiently.
  • 14. Types of Research Design  Describing a given or a specific situation.  No root cause analysis or impact analysis.  Presenting a data that is studied in terms of, “How much?”, “How regularly?”, “What percentage?”, “What is?”, “What time?” Descriptive research design:  Surveys  Observations  Case studies  Customer survey about a new features of a product.  Explaining the functionality of a new software application/equipment/any other asset.  Studying the stock markets based on a specific parameter.  Studying the human behavior at work place under stress conditions.
  • 15. Types of Research Design  Describing a given or a specific situation.  Primary focus on root cause analysis or impact analysis.  Considered as highly practical research method.  Studies relationship between two or more variables.  Concludes with suggestions or action point. Experimental research design:  Observations.  Simulations.  Survey.  Patients health condition before and after vaccination.  Corporate brand value before and after change management .  Employee performance measurement.  Students psychology before and after the COVID19 pandemic.
  • 16. Types of Research Design  Describing a given or a specific situation.  Considered as highly quantitative research method.  Studies relationship between two or more variables in terms of dependency of one variable over other  Concludes with suggestions. Correlational research design:  Journals/periodicals/new papers  Observations.  Survey.  Movement Stock prices Vs. stock indices.  Study on relationship between employee age, marital status, past experience on Organization performance.  Study the pattern of sales in employee performance.
  • 17. Sampling Design  Exploring for the first time.  Intended to discover some ideas and insights on a situation which has no past data.  Studies relationship between two or more variables in terms of dependency of one variable over other  Concludes with suggestions. Exploratory research design:  Journals/periodicals/new papers  Observations.  Survey.  A study into the role of social networking sites as an effective marketing communication channel  An investigation into the ways of improvement of quality of customer services within hospitality sector.  An assessment of the role of corporate social responsibility on consumer behavior in pharmaceutical industry.
  • 19. Sampling Design  A process of selection of sample size/units that are related to individuals/locations/entities .  Selection of a suitable sample design method ensures that the samples you invest your time and money into collecting can support the inferences you want to make.  It forms an important basis of observation, survey and analysis of the data.
  • 20. Determinants of sample size  Population size  Restricted to a specific control variable.  Margin of error  the percentage of error in the data you allow. Usually it is 5%  Confidence level  It represents how confident you want to be that the actual mean falls within the margin of error. Usually it is 90% or 95% or &99%.  Standard deviation  This has to be ascertained to find out how much deviation from actual mean.
  • 21. Calculation of Sample Size Necessary Sample Size = (Z-score)2 * StdDev*(1-StdDev) / (margin of error)2 Step -1: First you need to find the Z-Score Step -2: Use the formula to calculate sample size Here’s a worked example, assuming you chose a 95% confidence level, .5 standard deviation, and a margin of error (confidence interval) of +/- 5%. ((1.96)2 x .5(.5)) / (.05)2  (3.8416 x .25) / .0025  .9604 / .0025  384.16 385 respondents are needed The z-score at various confidence levels are (published and standard values) @ +90% CL = 1.645 @ +95% CL = 1.96 @ +99% CL = 2.576
  • 22. Calculation of Sample Size n = Required Sample size, z = Z-Score p = Population Proportion q = 1-p e = margin of error
  • 23. …Data Analysis tools in statistics…
  • 25. Data Analysis tools comparision.
  • 31. Testing of hypothesis Parametric Test Non-parametric Test Evaluate hypothesis for a particular parameter, usually the population mean. Evaluate hypothesis for entire population distributions. It considers only quantitative data. It considers both quantitative and qualitative data. Require assumptions about the distributional characteristics of the population in terms of normal shape and equal variance. Require no assumptions. It is used with non-normal distributions and when variances of the groups are not equal. More powerful than non- parametric tests when assumptions are met. Generally easy to compute but less effective than parametric test.
  • 33. Interpretation of data  Summarize the outcome of the research in a much professional manner.  Straight forward, exactly related to the outcome of the research.  Use generally accepted professional language.  Must clearly depicts the objective of the research.  Components of interpretation:  Summary of findings  Concluding observations  Suggestions or action points.
  • 35. Key takeaways  Define explicitly the problem statement, objectives, scope and limitations at the inception of the research project.  Always try to choose Confirmatory research as it has greater weightage.  Make sure to include quantitative data and qualitative data in your project.  Research design is a strategy that aims to bring quality in the research.  Always draw a justifiable sample size using the formula.  Apply relevant statistical tools according to the data.  Cross check the results of analysis by taking help from experts.  Draw your conclusions straight to the point of observation.  Become expert in MS-Excel.