title: “Part samples”
author: “Leonardo Guerrero”
date: “2026-06-02”
output: html_document
diameter_data = read.csv(” https://raw.githubusercontent.com/tmatis12/datafiles/main/diameter.csv“)
The csv file shows a random sample of diameters. The data contains 100 measurements randomly sampled.
Diameter is a key measurement in manufacturing because it helps determine whether a part meets design requirements. If a part is too large, it may not fit into the sub assembly. If it is too small, it may fit loosely or fail to perform its intended function. For this reason, manufacturers often collect sample measurements to monitor quality.
This data could be used as a part of a quality control process. In which it could help identify whether the manufacturing process is stable and whether the are being produced within an acceptable range.
This data set is useful because it gives information about the diameters of 100 randomly sampled parts. By looking at the measurements, we can better understand whether the parts are being produced close to the expected size. The data helps show the center, spread, and overall pattern of the part diameters.