Sums and averages: two variables, one scan

Counting adds 1 for each record. Summing adds a value from that record. You can do both in one scan, then divide to get an average.

Trace a small example #

At every stage, Count means “cards seen so far” and Sum means “their maths marks added so far”. At the end, Average = Sum/Count = 229/4 = 57.25.

Count ← 0
Sum ← 0
For each marks card X:
    Count ← Count + 1
    Sum ← Sum + X.mathsMarks
If Count > 0:
    Average ← Sum / Count
Else:
    Report "No observations to average"

Reuse the pattern for the lecture dataset #

The lecture reports 30 marks cards and a maths total of 2171. Their average is 2171/30 ≈ 72.3667. The same scan can accumulate physics marks too: keep MathsSum and PhysicsSum, and update both for every card. Separate variables keep separate meanings.

Tutorial example: average word length #

Use the stored letterCount field rather than the printed card position. Tutorial 1.1 reports 65 word cards and 329 letters in total, giving 329/65 ≈ 5.0615 letters per word. Keep the fractional average: individual word lengths are whole numbers, but their average need not be.

For the seven-word teaching dataset, letter counts are 3,6,5,4,3,4,9. Their sum is 34, so average length is 34/7 ≈ 4.8571. These teaching values are separate from the tutorial’s 65-word dataset.

Common mistakes to catch #

Do not add 1 to Sum when you mean to add the mark. Do not divide before checking Count. Do not reset Sum inside the loop. If you calculate an average with an integer-quotient operation, you may discard a meaningful fractional part; specify the intended division.

Source: Lecture 1.2; Tutorial 1.1 — Tutorial for Lecture 2. Small teaching datasets and diagrams are prepared for these notes; lecture and tutorial totals are identified explicitly.