wtf is analt5010-week2?

This repository contains a student assignment for a statistics course called ANLT5010 at Capella University, focused on analyzing invoice payment times for a fictional hospital called Cengaly Hospital. The scenario is that a company named Vila Health rolled out a new billing system meant to shorten how long it took patients to pay their invoices, which had previously often taken more than forty days, and this project uses statistics on a random sample of invoices to check whether the new system actually worked. The analysis uses a sample of 65 invoices drawn from a larger pool of 15,025 invoices processed during the first two months after the new billing system went live. Calculated results show an average payment time of about 18.11 days and a median of 17 days, with a maximum of 29 days across the sample, meaning every invoice in this sample was paid well within the old 40 day benchmark. The data shows a moderate rightward skew and is close to a normal, mesokurtic shape, and there is a very strong positive correlation of about 0.99 between how large an invoice is and how long it takes to be paid. Overall, the sample suggests roughly a 55 percent improvement in payment speed compared to the old system. The repository organizes the invoices into seven day range groups of three days each for a frequency distribution, visualized as a histogram image, with the 16 to 18 day range containing the largest single share of invoices at just over 35 percent. The files included cover the final written assignment as both a PDF and a Markdown document, the original invoice dataset as a CSV file, and three separate Python scripts: one that performs all the statistical calculations, one that generates the histogram chart, and one that assembles the formatted PDF report. To reproduce the analysis, you need Python 3.x with the matplotlib and reportlab libraries installed, after which you can run the analysis script, the histogram script, and the PDF generation script in sequence. Based on these results, the assignment's conclusion recommends deploying the new billing system across the whole hospital system. The author notes that Claude was used to assist with the analysis and the accompanying essay.