Using Stata to analyze size frequency of the life cycle of a Mexican desert spider

In biology, the study of the life cycle of plants and animals helps one to understand the phenology of a particular species, which is useful in pest management or in biological conservation. Spiders are one of the most widespread animals on earth. They eat a huge variety of other animals and are good indicators of environmental changes. We studied for the first time the life cycle of an endemic desert spider (Syspira tigrina). Many spider researchers have used the direct estimation of the number of instars to describe the arachnid life cycle. Other methods are based on the analysis of the length-frequency throughout time (indirect methods). Length-frequency distributions are commonly analyzed by histograms. However, this procedure depends on grid origin, and the interval width is discontinuous and uses a fixed interval width. These problems have motivated the interest of statisticians in alternative, more computationally intensive methods. Kernel density estimators (KDEs) do not depend on the origin position and are continuous distribution estimators. In addition, there are several methods for choosing the interval width. In this study, we present in Stata the use of KDEs to examine length-frequency distributions of spider size in combination with the traditional approach using histograms.