Biostatistics Series – 1

Abstract

Statistics is defined as the science of collecting, compiling, presenting, analyzing, and interpreting data to ensure research findings are implementable in curative or public health. This editorial, the first in a biostatistics series, outlines the critical framework for planning data collection based on study design, categorized into experimental and observational approaches. Experimental designs range from pre-experimental and quasi-experimental to true experimental studies, such as dental in-vitro research, which utilizes the three principles of randomization, local control, and replication to establish cause-and-effect relationships. For observational quantitative studies, the focus is on developing validated questionnaires that must undergo rigorous validation—including content, construct, face, and criterion validity—and demonstrate internal consistency, typically measured by a Cronbach’s Alpha score greater than 0.7. Data collection methods vary from direct oral interviews to digital Google forms, each presenting unique limitations such as high dropout rates or Berksonian bias. Furthermore, the editorial details the importance of variables and scales of measurement—Nominal, Ordinal, Interval, and Ratio—which dictate the appropriate first-line statistical analysis, such as mean and standard deviation for quantitative data or proportions for qualitative data. Establishing these foundational statistical principles is vital for researchers to arrive at valid inferences in dental science.