Research Methodology

Research MethodologyFaisal Abbas, PhD

Theoretical Framework Hypothesis DevelopmentObservation broad areaPreliminary data gatheringProblem definitionTheoreticalframeworkGenerationOf hypothesisScientific research designData collectionAnalysis and interpretationDeduction hypothesisReport writingReport presentationManagerial decision makingTheoretical Framework: What and Why?Basis of entire research.

Helps in building and identifying logical sense of the relationship among the several factors that are important to the problem.

Integrating logical beliefs with published research.

Theoretical Framework: What and Why?It helps in developing a scientific basis for investigating the research problem.

Helps in testing certain relationships to improve our understanding of the situation.

Testable hypothesis can be developedTheoretical Framework: What and Why?First identify the problem and then, identify the variables that contribute to it.

Literature survey provides a solid foundation for developing a theoretical/conceptual framework.

The theoretical framework elaborates the relationships among the variables, explain the theory underlying these relations and describes the nature and direction of the relationships.

Theoretical Framework: What and Why?Clarity, identification and labeling (relevance) the variables of study

The important relationships among the variables must be defined.

Give clear explanation of the existing relationships of different variables.

VariablesThere are changeable values of any thing. (e.g. exam score)

Types of variables:

Dependent

Independent

Moderate

InterveningIndependent variable It is that variable which influences the dependent variable.

Moderating Variable

It is that variables which modifies the original relationship between the independent and the dependent variables.

Intervening variableIt is the impact on the dependent variable caused by the independent variables influence the same.

Why to do sampling?What is Census?

What is sampling? Sampling is a valid to a census because;

Entire population survey might be impracticable.

Budget and time constraints restrict data collection.

Need results from data collection quickly.What is sampling frame ?The sampling frame for any probability sample is a complete list of all the cases in the population from which your sample will be drawn.Sampling Techniques: An overviewSource: Saunders et al. (2009)

Probability Sampling With probability samples the chance , or probability, of each case being selected from the population is known and usually equal to all cases.

This means that it is possible to answer research questions and to achieve objectives that require you to estimate statistically the characteristics of the population from the sample.

Consequently, probability sampling is often associated with survey and experimental research strategies.

Probability samplingThe probability sampling is four stage process

Identify sampling frame from research objectives

Decide on a suitable sample size

Select the appropriate technique and the sample

Check whether the sample is representative!

Non probability samplesThe probability of each case being selected from the total population is not known.

It is impossible to answer research questions or to address research objectives that require you to make statistical inferences about the characteristics of the population.

You may still be able to generalize from non probability samples about the population, but not on statistical grounds. Non Probability Sampling: TechniquesQuota sampling (larger populations)

Purposive sampling

Snowball sampling

Self-selection sampling

Convenience samplingSource: Saunders et al. (2006)

Secondary Data Observation: A data collection methodObservation involves the systematic observation, recording, description analysis and interpretation of peoples behaviour.

Saunders et al. (2009)Types of observationThere are two main types of observations;

1). Participant observation

Emphasises the discovery of meaning attached to actions (qualitative)

2). Structured observation It is concerned with frequency of actions (quantitative)Research InterviewsAn interview is a purposeful discussion between two or more peopleKahn and Cannell (1957)

Types of interview used in research are;

1).Semi-structured2).Structured3).In-depth 4).Group

Saunders et al. (2009)Research purpose and strategyForms of interview

Saunders et al. (2009)

Figure 10.1 Forms of interviewTypes of interviewStructured interviews: use questionnaire based on a predetermined and standardized or identical set of questions and we refer to them as interviewer administered questionnaires.

Semi-structure interviews:

the researcher will have a list of themes and questions to be covered, although these may vary from interview to interview.

This means that you may omit some questions in particular interviews, given a specific organizational context that is encountered in relation to the research topic.

The order of questions also be varied depending on the flow of conversation.

On the other hand, additional questions may be required to explore your research question and objectives given the nature of events within particular organizations.

Types of interviewUnstructured interviews:

Unstructured interviews are informal.

You would use these to explore in-depth a general area in which you are interested .

We therefore, refer to these as in-depth interviews.

There is no predetermined list of questions to work through in this situation, although you need to have a clear idea about the aspect or aspects that you want to explore.

The interviewee is given the opportunity to talk freely about events behavior and beliefs in relation to topic area. What is questionnaire?Techniques of data collection in which each person is asked to respond to the same set of questions in a predetermined order

Adapted from deVaus (2002)Use of questionnaires When to use questionnaires

For explanatory or descriptive research.

Linked with other methods in a multiple-methods research design.

To collect responses from a large sample prior to quantitative analysis.

Types of QuestionnaireThese are the types of questionnaire given in tabular form below;

Saunders et al. (2009)

Figure 11.1 Types of questionnairePreparing, inputting and checking dataIf you intend to undertake quantitative analysis consider the following:

type of data (scale of measurement);

format in which your data will be input to the analysis software; SPSS, EVIEWS, STATA, NVIVO.

impact of data coding on subsequent analyses (for different data types);

methods you intend to use to check data for errors.Quantitative Data Quantitative data can be divided into two distinct groups: categorical and numerical.

Categorical data refer to data whose values cannot be measured numerically but can be either classified into sets (categories) according to the characteristics that identify or describe the variable or placed in rank order (Berman Brown and Saunders 2008).Quantitative Data They can be further sub-divided into descriptive and ranked.

A car manufacturer might categorise the types of cars it produces as hatchback, saloon and estate. These are known as descriptive data or nominal data as it is impossible to define the category numerically or to rank it.

Rather these data simply count the number of occurrences in each category of a variable.

For virtually all analyses the categories should be unambiguous and discrete; in other words, having one particular feature, such as a car being a hatchback, excludes all other features for that variable. This prevents questions arising as to which category an individual case belongs.

Quantitative Data Although, these data are purely descriptive, you can count them to establish which category has the most and whether cases are spread evenly between categories (Morris 2003).

Some statisticians (and statistics) also separate descriptive data where there are only two categories. These are known as dichotomous data, as the variable is divided into two categories, such as the variable gender being divided into female and male.

Ranked (or ordinal) data are a more precise form of categorical data.

Quantitative Data

Designing Diagrams and TablesFor both diagrams and tables

Does it have a brief but clear and descriptive title?

Are the units of measurement used stated clearly?

Are the sources of data used stated clearly?

Are there notes to explain abbreviations and unusual terminology?

Does it state the size of the sample on which the values in the table are based?Designing Diagrams and TablesFor diagrams

Does it have clear axis labels?

Are bars and their components in the same logical sequence?

Is more dense shading used for smaller areas?

Have you avoided misrepresenting or distorting the data Is a key or legend included (where necessary)?

Designing Diagrams and TablesFor tables

Does it have clear column and row headings?

Are columns and rows in a logical sequence?

Designing Diagrams and TablesIt best to begin exploratory analysis by looking at individual variables and their components.

The key aspects you may need to consider will be guided by your research question(s) and objectives, and are likely to include (Sparrow 1989):

specific values; highest and lowest values; trends over time; proportions; distributions.

Designing Diagrams and TablesOnce you have explored these, you can then begin to compare and look for relationships between variables, considering in addition (Sparrow 1989):

conjunctions (the point where values for two or more variables intersect);

totals;

interdependence and relationships.Difference

37Qualitative analysis processThere is no standardized procedure for analysing qualitative data. Despite this, it is still possible to group data into three main types of processes:

Summarising (condensation) of meanings;Summarising, therefore, involves condensing the meaning of large amounts of text into fewer words.Categorization (grouping) of meanings;Involves two activities: developing categories and, subsequently, attaching these categories to meaningful chunks of data. Through doing this you will begin to recognize relationships and further develop the categories you are using to facilitate this.Structuring (ordering) of meanings using narrative.Narrative structuring ensures that the data are organised both temporally and with regard to the social or organizational contexts of the research participant (Kvale 1996). This form of analysis focuses upon the stories told during the interviewsGetting started with writingPractical hints

Create time for your writingWrite when your mind is freshFind a regular writing placeSet goals and achieve themUse word processingGenerate a plan for the reportFinish each writing session on a high pointGet friends to read and comment on your workStructuring your research reportSuggested structure

AbstractIntroductionLiterature reviewMethodResultsDiscussionConclusionsReferences AppendicesThe nature of researchThere is no one best way for undertaking all research.

Thank You very much and Good Luck