Why and When Statistics is Required, and How to Simplify Choosing Appropriate Statistical Techniques During Ph.D. Program in India?

Abstract

Purpose: The purpose of this article is to explain the key reasons for the existence of statistics in doctoral-level research, why and when statistical techniques are to be used, how to statistically describe the units of analysis/samples, how to statistically describe the data collected from units of analysis/samples; how to statistically discover the relationship between variables of the research question; a step-by-step process of statistical significance/hypothesis test, tricks for selecting an appropriate statistical significance test, and most importantly which is the most user-friendly and free software for carrying out statistical analyses. In turn, guiding Ph.D. scholars to choose appropriate statistical techniques across various stages of the doctoral-level research process to ensure a high-quality research output.

Design/Methodology/Approach: Postmodernism philosophical paradigm; Inductive research approach; Observation data collection method; Longitudinal data collection time frame; Qualitative data analysis.

Findings/Result: As long as the Ph.D. scholars can understand i) they need NOT be an expert in Mathematics/Statistics and it is easy to learn statistics during Ph.D.; ii) the difference between measures of central tendency and dispersion; iii) the difference between association, correlation, and causation; iv) difference between null and research/alternate hypotheses; v) difference between Type I and Type II errors; vi) key drivers for choosing a statistical significance test; vi) which is the best software for carrying out statistical analyses. Scholars will be able to (on their own) choose appropriate statistical techniques across various steps of the doctoral-level research process and comfortably claim their research findings.

Originality/Value: There is a vast literature about statistics, probability theory, measures of central tendency and dispersion, formulas for finding the relationship between variables, and statistical significance tests. However, only a few have explained them together comprehensively which is conceivable to Ph.D. scholars. In this article, we have attempted to explain the reasons for the existence, objectives, purposes, and essence of ‘Statistics’ briefly and comprehensively with simple examples and tricks that would eradicate fear among Ph.D. scholars about ‘Statistics’. 

Paper Type: Conceptual.