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Grades  
Updated Mar 22, 2012 by wingles....@gmail.com

#Compute the final grades, class average and class statistics of an entire class over its students

Introduction

The Overall design is meant to gather all information over a course load and it's students involved. We track the A's,B's, C's, D's and overall course GPA. Highest Grade, Mean Grade, and Lowest Grade. Also covered in the background of the algorithm we compute the Zscore and stdDeviation of the course and it's students. We do this in an Object Oriented fashion.

Objects

The objects that were used and considered for use were Students and course. We go over these here.

Student is focused over students information. Class focused on the overall given course.

Student:

  • Student ID
  • Studnet TA
  • Student Unique course number
  • Student LetterGrade
  • Student Scores_List
  • Student Zscore

Class

  • Class Number of Events
  • Class List of Max Values
  • Class List of Weights
  • Class Max Grade
  • Class Min Grade
  • Class Mean Grade
  • Class StdDev
  • Class Count of Letter Values
  • Class Count of Letter Percentages

Details of Functions

We use three main functions to tackle all of the computation and grade distribution.

Grade_Read

  • InputStream Reader
  • Course Variable referenced
  • Students Vector List referenced

Grades_eval

  • Course Variable referenced
  • Students Vector List referenced

Grades_Print

  • OutputStream Writer
  • Course Variable referenced
  • Students Vector List referenced

Grade_solve

  • InputStream Reader
  • OutputStream Writer

Details of Algorithm

Grades_Read

Reads line by line and parses the information to it's proper storage container. After doing this, the function returns true to continue we the process, or if there was nothing to be read in, return false to exit

Course

  • First Line is number of events
  • Second Line is the list of Max Values for each event
  • Third Line is the List of Weight for each event
  • Nth Line is a student, We go through the each student and store each token of information to the proper student container.

Students

  • First Token is Student ID
  • Second Token is Unique Number
  • Third token is TA assigned to Student
  • nth token there after is a students grade for an event.

Grades Eval

Iterates through each of the nessecary container computing the course statistics. We begin by first computing a students total with the equation

total = (score for event i / num of events) x (event weight)

As we find each students total, we track the high and the low grades, letter Grade for the course, and sum up for the mean grade. When finished we find the true mean grade.

Iterate through of the LetterGrades and compute the class GPA.

Standard Deviation for Z-Score

When we find the mean and the total grades for each student, we iterate back through each of the students giving them each their z-Score for the class. But first we needed to find the Standard Deviation.

stdev = sqrt (sum-mation(grade - average)^2)/ n-1 )

Finally After giving each student their zscore, we sort Students, by zscore for a proper print. We included algorithms.h.

Grade Print

Print we use iomanip.h to organize the information being printed out to the computer screen as asked to display.

  • Num_events
  • Max Values
  • Weights
  • Statistics
  • Students Info
    • ID, UNIQUE, TA, SCORES(many), FINAL GRADE, ZSCORE, LETTER GRADE

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