Result: A scientific research has a beginning and an end; the results are simply the end of particular research & what found in the study
Presenting the results:
─Present the results of the study, in logical order; using tables, maps and graphs as necessary.
─Explain the results and show how they help to answer the research questions posed in the Introduction.
─Evidence does not explain itself; the results must be presented and then explained.
2. Discussion: Help to interpret and describe the significance of your findings and to explain any new understanding or insights that emerged as a result of your study of the problem.
Summarize the results
Outline their interpretation in light of the known literature
While deciding about the method of data collection to be used for the study, the researcher should keep in mind
two types of data viz., primary and secondary.
The primary data are those which are collected afresh and for the first time, and thus happen to be original in
character.
The secondary data, on the other hand, are those which have already been collected by someone else and which
have already been passed through the statistical process.
The researcher would have to decide which sort of data he would be using (thus collecting) for his study and
accordingly he will have to select one or the other method of data collection.
What is data collection?
The process by which the researcher collects the information needed to answer the research problem.
In collecting the data, the researcher must decide:
Which data to collect
How to collect the data
Who will collect the data
When to collect the data
The selection of data collection method should be based on the following:
The identified hypothesis or research problem
The research design
The information gathered about the variables
2. Data presentation
For quantitative: Tables are devices for presenting datasimply from masses of statistical data
─Charts and Diagrams
─Statistical Maps
─Statistical Averages
─Measures of Dispersion
For qualitative: Qualitative data conventionally are presented by using illustrative quotes.
─Quotes are “raw data” and should be compiled and analyzed, not just listed
─There should be an explanation of how the quotes were chosen and how they are labeled
Data presentation in research
3. Research Data analysis
Quantitative Data
Cross-tabulation: Cross tabulation is a method to quantitatively analyze the relationship between multiple variables.
Trend analysis: Trend analysis is based on the idea that what has happened in the past gives the researcher an idea of what will happen in the future.
Research Data analysis by architect Kaleab M
Qualitative data: The most commonly used data analysis methods are:
─ Content analysis: This is one of the most common methods to analyze qualitative data.
the study of documents & communication artifacts
includes texts of various formats, pictures, audio or video.
─ Narrative analysis: This method is used to analyze content from various sources, such as:
Historical research enables you to explore and explain the meanings, phases, and characteristics of a phenomenon or process at a particular point of time in the past
─Refers to research in the discipline of history.
─The aim is to identify appearances of your chosen phenomenon in a temporally defined situation and environment.
─It is also suitable in other disciplines as it enables you to focus on exploring the historical appearances of phenomena.
─Qualitative analysis is the norm, but quantitative analysis can also explain the past.
2. Qualitative & quantitative Research
Qualitative research:
─Involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences.
─It can be used to gather in-depth insights into a problem or generate new ideas for research.
Quantitative research:
─Quantitative research is the process of collecting and analyzing numerical data.
─It can be used to:
find patterns and averages,
make predictions,
test causal relationships,
and generalize results to wider populations.
3. Correlational research
Correlational research is a type of non-experimental research method
─a researcher measures two variables
─understands and assesses the statistical relationship between them
─no influence from any extraneous variable
4. Experimental Research
There are two basic types of research design:
─True experiments
─Quasi-experiments
The purpose of both is to examine the cause of certain phenomena
All the important factors that might affect the phenomena of interest are completely controlled
It is not possible or practical to control all the key factors (quasi-experimental research is needed)
Similarities between true and quasi-experiments:
─Study participants are subjected to some type of treatment or condition
─Some outcome of interest is measured
─The researchers test whether differences in this outcome are related to the treatment
5. Modeling and simulation (M&S)
Is the use of models (e.g., physical, mathematical, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for technical or other decision making.
Modeling and simulation procedureModel verification and validation architecture
6. logical argumentation
logical argumentationlogical argumentation
7. Case studies Research
A researchapproach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context.
It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences.
Used mainly used qualitative data but sometimes collect quantitative data
According to Yin (2014), a case study research typically includes multiple data collection techniques and data are collected from multiple sources.
