Modernization Data Analysis and Visualization for Food Safety Research Outcomes

Abstract

Appropriate data collection and using reliable and accurate procedures are the first steps in conducting an experiment that will provide trustworthy outcomes. It is key to perform an assertive statistical analysis and data visualization for a correct interpretation and communication of results. A clear statistical summary and presentation of the data is critical for the reader to easily process and comprehend experimental results. Nowadays, there are a series of different tools to perform proper statistical analysis and create elaborate graphs that will help readers to understand the data, identify trends, detect outliers, evaluate statistical outputs, etc. However, researchers that are beginning to navigate experiments do not frequently encounter a guide that can provide basic principal concepts to begin their statistical analysis and data presentation. Therefore, the objective of this article is to provide a guide or manual to analyze and presents results focused on different types of common food safety experiments, including method comparisons, intervention studies, pathogen presence experiments, bio-mapping, statistical process control, and shelf life experiments. This review will provide information about data visualization options and statistical analysis approaches for different food safety experiments. In addition, basic concepts about descriptive statistics and possible solutions for issues related to microbiological measurements will be discussed.