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Class Average Calculator

Analyze class scores with explicit averaging models, quartiles, spread, grade bands, curve scenarios and exportable evidence — all locally in your browser.

Wave165 · class-score distribution, averaging-model & curve evidence

Class Average & Assessment Distribution Studio

Paste percentages, raw earned/possible scores or named rows; choose the averaging model explicitly; then inspect spread, grade bands, outliers, curve what-ifs and per-row evidence locally in your browser.

local · model-aware · distribution-audited
Accepted row forms
88 · 42/50 · Ava | 88 · Ava | 42/50 | 1.5

Missing markers: missing, absent; excluded markers: excused, exempt.

Weights are used only in custom-weight mode. Pooled-points mode requires every included row to use earned/possible form.

Local TXT/CSV import is capped at 1 MB.
Ready.

1. Class summary

Displayed class average—
Median—
Included scores—
Population SD—
Pass rate—
Min–max—
IQR—
Active model—

2. Grade thresholds & distribution

BandCountShare
Outlier evidence appears here.
Input validation appears here.

3. Distribution evidence

Score histogram

Box plot

StatisticValue

4. Per-row evidence

#LabelPercentBandΔ meanz-scoreEmpirical percentileRaw pointsWeight

5. Curve what-if — scenario only

Scenario mean—
Scenario pass rate—
Scenario maximum—
Scenario A count—

6. Compare another class without storing raw scores

Pin a class summary, then load another dataset to compare mean, median and pass-rate deltas without preserving raw scores.

7. Audit, export & repeat use

Recent local numeric summaries

History stores only N, aggregate statistics and model name; it does not store labels or score rows. The settings-only share URL excludes class data and history.

Truth boundary. “Class average” can mean different calculations. Equal-student mean gives every included student one vote; pooled raw points weights rows by possible points; custom-weight mode follows the explicit row weights. Those values can legitimately differ. Missing-work, extra-credit, curves, rounding and official grade bands are school/course policies, so this Studio exposes assumptions rather than claiming an official gradebook result. The 1.5×IQR outlier flag is descriptive evidence, not a reason to remove a student score. All analysis stays in this browser.
Education grade-planning cluster

Match the gradebook model before trusting the target

Separate question-count tests, pure points, weighted categories, final-exam weighting and GPA scales. Then reconcile the calculator with the syllabus rule actually used by the class.

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Practical guide and verification

Know what is being averaged

A simple class average treats every entered score equally. If assignments, sections or students carry different weights, use a weighted calculation instead of averaging already-averaged groups without considering their sizes.

Missing work and exclusions

Decide how absent, excused or ungraded work is represented before calculating. Leaving an item out and entering a zero have very different meanings, so the input convention should match the grading policy.

Common mistake

The average of two group averages is not generally the overall average unless the groups contain the same number of observations. Combine the underlying counts or use weighted means when section sizes differ.

Mean and median answer different questions

The mean uses every score and is sensitive to very high or low values; the median reports the middle of the ordered list. Range and standard deviation describe spread. Review all of them when one outlier could make the class average look unrepresentative.

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