John Hay
John Hay Biomedical
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Principles of Biomedical Technology (Principles of Biomedical Science)
Unit 4: Unit 4.1 Innovation, Inc.PBS 4.1Biotechnology Research and Experiments

Iterate From Data

Use evidence and design criteria to iterate from data.

Builds on (2 levels back)inferred · high confidence
  • Criteria and constraints: Design work needs success targets and limits before testing.
  • Evidence-based iteration: Changes should trace to data, feedback, or a failed criterion.

Prerequisites are inferred: pending teacher review.

Re-learn the skill with worked practice and clear examples.

Use a trial-results table to pick the change the DATA supports.

Step 1: Compare the rows
When the table compares two versions, read both rows of measured values.
BuzzerTrial 1 (s)Trial 2 (s)Trial 3 (s)
Small buzzer131413
Large buzzer898
Trial results table comparing two buzzer sizes by alarm time.
Step 2: Pick the data-backed change
Choose the change that the faster row in the data supports: not a guess about a part the table never tested.
Practice

A team tests a small buzzer and a large buzzer; the target is under 10 seconds. Using the trial results, which change does the DATA justify?

Reviewed
BuzzerTrial 1 (s)Trial 2 (s)Trial 3 (s)
Small buzzer131413
Large buzzer898
Trial results table comparing two buzzer sizes by alarm time.
  1. A.Switch to the large buzzer, because its trials (8, 9, 8 s) meet the under-10-second target
  2. B.Keep the small buzzer, because it looks neater
  3. C.Change the bottle color, because that might help
  4. D.Switch to the large buzzer, because larger is always better
Show the worked solution ▾

Answer: A. Switch to the large buzzer, because its trials (8, 9, 8 s) meet the under-10-second target

  1. Step 1: Read both rows: Small buzzer: 13, 14, 13 s. Large buzzer: 8, 9, 8 s.
  2. Step 2: Compare to the target: Only the large buzzer's trials are all under 10 s, so the data supports switching to it.

Why it's right: The large buzzer's measured times (8, 9, 8 s) all beat the 10-second target, so the data justifies switching to it.

Why the others miss:
  • B: 'Looks neater' is not in the data, and the small buzzer missed the target.
  • C: Bottle color was never tested, so the data does not support it.
  • D: The reason should be the measured times, not 'larger is always better'.

Aligned to Biotechnology Research and Experiments · reading level ~grade 9

Where you'd see this
  • A student picks the version the trial data supports instead of guessing.
Careers that use this
Biomedical Engineer: Chooses the design change the trial numbers support, not a hunch.
Video library
Watch: Iterate From Data
Improve your designs with ITERATION
CharliMarieTV · 5:32
Guided notes

Fill these in as you work through the lesson.

Big idea: Iterating from data means reading the trial-results table and choosing the change the numbers actually support.
Key terms: write the meaning
  • Trial (one measured run of the test):  
  • Target (the value you must meet):  
  • Data-backed change (a change the numbers support):  
  • Trade-off (balancing two targets at once):  
The rule

Read every   in the table, compare each value to the  , then choose the change the   supports.

Check yourself
  1. What does each trial measure? 
  2. Which version meets the target? 
  3. Does the change come from the data or a guess? 
Work one example

Given two buzzer rows (13/14/13 vs 8/9/8) and a 10 s target, pick the buzzer the data supports.