The purpose of this report is to examine the data from an observational study of abalone in Tanzania. The intent of the underlying abalone research was to identify a new method for predicting the age of a regional abalone population through physical measurements. Such a technique would significantly increase the speed and efficiency in which biologists could identify abalone age. Today, age is best determined by counting the number of shell rings via a microscope. Unfortunately, the data from this study was unsuccessful.
The researchers concluded that further information was required, such as weather patterns ND geographic location, as both variables affect food availability. The content within this report will explore in further detail why the study was not successful by examining the statistical characteristics of key variables. RESULTS Us Mary of Data To assess the abalone research data, a simple random sample of 500 observations were taken from the original abalone data file, which contained 4,141 observations.
To begin, an initial summary table and matrix plot were constructed to assess the characteristics of the observational variables. Table 1 . 1, which is provided below, outlines the observational variables in further detail. Upon an initial assessment of the data, the first thing that stood out was the size Of the abalone measurements, which are extremely small. In looking at the initial set of 4,141 observations, there appears to be an abalone with a height of O mm, which indicates an improper recording took place, leading me to be slightly skeptical of the data.