What This Document Is
This document outlines an extra credit exercise – Assignment 7S – for CSCI 599, a Special Topics course at the University of Southern California, focusing on Personal Project Management Process (PPMP) alongside the Personal Software Process (PSP). It appears to be a practical application of previously learned concepts, centered around refining statistical prediction techniques used in software project estimation. The assignment builds upon earlier work, specifically referencing Spreadsheet 3S and data found in Appendix A8. It’s designed as a hands-on exercise to deepen understanding of project planning and estimation methodologies.
Why This Document Matters
This assignment is crucial for students enrolled in CSCI 599 who are looking to solidify their grasp of software project estimation and improve their practical skills in applying statistical methods. It’s particularly valuable for those interested in roles involving software development, project management, or quality assurance. Successfully completing this exercise will demonstrate an ability to translate theoretical knowledge into a functional tool for predicting project outcomes. It’s ideal for students seeking to enhance their portfolio with demonstrable project management skills.
Common Limitations or Challenges
This document details the *requirements* of the assignment, but it does not provide pre-built solutions or step-by-step instructions for completing the spreadsheet. Students will need a strong understanding of linear regression, statistical prediction intervals, and spreadsheet software (like Excel) to successfully implement the required modifications. It assumes prior completion of related exercises and familiarity with the course materials. Access to the referenced appendices and previous spreadsheets is also necessary.
What This Document Provides
* Detailed specifications for modifying an existing spreadsheet (Spreadsheet 3S).
* A clear objective: to enhance a linear regression model using relative error instead of absolute error.
* Specific requirements for calculating and displaying prediction intervals (90% and 70%).
* Guidance on visualizing the regression line and prediction intervals.
* Testing instructions referencing specific data tables (Table D8).
* A list of required forms and templates related to the PPMP process.
* References to relevant course materials (Appendices A7 & A8).
