Systematic review and meta-analysis are often confused and used interchangeably albeit having distinct differences between them. Both are reviews of high quality evidence that form a part of literature review.  What is a Systematic review?  A systemic review seeks to find answer to a defined question by collecting and synthesizing high quality evidence from different studies. It is an exhaustive summary of all scientific evidence substantiated to a particular question. Systematic reviews came to be as a way to improve the quality of literature review. Systematic review applies to all types of research, both qualitative and quantitative. Systematic review evolved in the health care industry and clinical trials, but has since found its application in variety of fields like social sciences, astronomy, etc. What is a Meta-analysis?   Meta-analysis integrates statistically similar studies using statistical principles to achieve an estimate of common po...

Reacquaint yourself with simple yet important data analysis tools to transition from abstract numbers to quantifiable success. In today’s digital era, we are inundated with information—it’s overwhelming. Leaders at the top helm make decisive decisions daily. Sorting through avalanche of data to assist management’s decision making is the key. Objective is to sort and  interpret  and report findings. Toward this end, tools or techniques for statistical data analyses achieve this objective. Buzzwords we hear today are big data, hadoop, and AI; however, rudimentary tools need to be deployed to their maximum capability, which is not the case in most firms. Propel your  data analysis   program by mastering the following 5 basic techniques. Review these mundane statistical techniques, yet so vital. Techniques Merits Demerits 1. Hypothesis Testing Hypothesis tests are used in multiple disciplines such as science, research, economics, etc. Popularly kn...

Significance of Quantitative Statistical Data Analysis Statistical Data analysis in quantitative research  generally involves varied statistical techniques such as regression analysis, multivariate analysis, significance testing, and so on. These can be efficiently performed by expert analysts having quantitative skills and extensive knowledge in statistics. Data can statistically be inferred only after performing the  Quantitative Data Analysis . You have to turn raw numbers into meaningful data in  Quantitative Data Analysis  by applying critical and rational thinking. As same figure within a data-set may be interpreted in different ways, it becomes vital to apply careful and fair judgment.  Data analysis in quantitative research  must be performed by professionals having relevant experience and skill. “Statistics is the grammar of science.” Karl Pearson Quantitative Research Methods for PhD Students – the Challenges: It is usual for...