Sample size

Sample size refers to the number of individuals or entities selected from a population for a research study. It should be large enough to provide reliable results and detect meaningful effects. Factors to consider when determining the sample size include the size of the population, desired level of precision, statistical power, expected effect size, and sampling method. Researchers use statistical techniques to calculate an appropriate sample size, ensuring that it represents the population adequately and yields reliable findings. Expert Statistical

Pilot study

A pilot research study is a small-scale preliminary investigation conducted before a full-scale research project. Its main purposes are to assess feasibility, test research design and procedures, identify logistical considerations, determine sample size, refine research instruments, and improve data analysis approaches. By conducting a pilot study, researchers gain valuable insights and make necessary adjustments to enhance the quality and effectiveness of the main study.

pilot study

Data Analysis

Data analysis refers to the process of inspecting, cleaning, transforming, and interpreting raw data to extract meaningful insights, identify patterns, and draw conclusions. It involves applying various techniques and methods to organize, analyze, and interpret data in order to answer research questions, test hypotheses, or uncover relationships and trends within the data.It is a crucial part of the research process, as it allows researchers to derive insights, validate hypotheses, support decision-making, and contribute to knowledge in various fields. By effectively analyzing data, researchers can uncover valuable information and make informed conclusions that drive further research or inform practical applications. Expert Statistical

Structural Equation Modeling (SEM)

Structural equation modeling (SEM) is a statistical technique used to analyze complex relationships between variables and test theoretical models. It combines aspects of factor analysis and regression analysis to examine both the measurement and structural aspects of a model simultaneously. SEM allows for the examination of complex relationships among multiple variables and provides insights into the underlying theoretical structure of a model. It can be used in various fields, including social sciences, psychology, education, and business, to analyze complex data sets and test theoretical frameworks. SEM enables researchers to assess both the measurement and structural aspects of a model, making it a powerful tool for hypothesis testing and theory development.

Interpretation of results

Interpretation of results refers to the process of analyzing and making sense of the findings obtained from data analysis in a research study. It involves understanding the implications, significance, and meaning of the results within the context of the research objectives, research questions, and theoretical framework. It is crucial to approach the interpretation of results with caution, considering the limitations of the study and the possibility of alternative explanations. The interpretation should be guided by rigorous analysis, a deep understanding of the research context, and an objective evaluation of the evidence. Clear and transparent reporting of the interpretation of results helps ensure the validity, reliability, and reproducibility of the research findings.

Quantitative, Qualitative & Mixed Methods

Quantitative and qualitative research are two distinct approaches to studying phenomena in social sciences, each with its own characteristics and methodologies. Mixed methods research combines elements of both quantitative and qualitative approaches to gain a more comprehensive understanding of a research topic. The choice between quantitative, qualitative, or mixed methods research depends on the research objectives, the nature of the research questions, and the specific context of the study. Researchers should carefully consider the advantages, limitations, and appropriateness of each approach in relation to their research goals.
qualitative & quantitative