We follow customised research methodology for individual project as per the requirement. However, the research methodology consists of the following few components:
Problem Statement: The research methodology starts with defining the problem statement.
Making a hypothesis: The development of hypothesis is a technical work depends on researcher’s experience.
The hypothesis is to draw the positive and negative cause and effect aspects of a problem. Hypothesis narrows down the area of a research and keep the researcher in the right path.
Research design: Research design can be done using various type of methods as per the requirements of the problem statement.
Experimental Research Design: A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomisation, and manipulation.
- This research design can be further categorised into the following –
Informal experimental design –
After only design.
• After only with control design.
• Before and after without control design.
• Before and after with control design.
- Formal experimental design –
Completely randomised design.
• Randomised block design. – In the statistical theory of the design of experiments, blocking is the arranging of experimental units in groups (blocks) that are similar to one another. Typically, a blocking factor is a source of variability that is not of primary interest to the experimenter. An example of a blocking factor might be the sex of a patient; by blocking on sex, this source of variability is controlled for, thus leading to greater accuracy.
- Latin square design: In experimental design, a Latin square is an n × n array filled with n different symbols, each occurring exactly once in each row and exactly once in each column.
- Factorial design :
In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or “levels”, and whose experimental units take on all possible combinations of these levels across all such factors. A full factorial design may also be called a fully crossed design. Such an experiment allows the investigator to study the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable.
An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome. The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.
Empirical Research can be defined as “research based on experimentation or observation (evidence)”. Such research is conducted to test a hypothesis.
The word empirical means information gained by experience, observation, or experiment. The central theme in scientific method is that all evidence must be empirical which means it is based on evidence. In scientific method the word “empirical” refers to the use of working hypothesis that can be tested using observation and experiment.
Empirical data is produced by experiment and observation.
- Capture contextual data and complexity
- Identify and learn from the collective experience of others from the field
- Identification, exploration, confirmation and advancing the theoretical concepts.
- Further improve educational design.
The sample of a study can have a profound impact on the outcome of a study. In this lesson, we’ll look at the procedure that will help in drawing a sample.
Sample size is being selected based on the confidence level we want to achieve through the study.
The confidence level tells you how sure you can be. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the confidence interval. The 95% confidence level means you can be 95% certain; the 99% confidence level means you can be 99% certain. Most researchers use the 95% confidence level.
When you put the confidence level and the confidence interval together, you can say that you are 95% sure that the true percentage of the population is between 43% and 51%. The wider the confidence interval you are willing to accept, the more certain you can be that the whole population answers would be within that range.
Data analysis & interpretation:
Data is analysed and interpretation is done after data collection. Recommendation is made based on the analysis
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What is Research Methodology?
Research helps in measuring reputation performance against business return. It helps to identify the key drivers that have most impact on creating value.