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.Keep the small buzzer, because it looks neater on the bottle cap
  2. B.Switch to the large buzzer, because a larger buzzer is always the better choice
  3. C.Switch to the large buzzer, because its trials of 8, 9, and 8 s beat 10 s
  4. D.Change the bottle color, because that might help people notice it
Show the worked solution ▾

Answer: C. Switch to the large buzzer, because its trials of 8, 9, and 8 s beat 10 s

  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:
  • A: 'Looks neater' is not in the data, and the small buzzer missed the target.
  • B: The right buzzer here is the large one, but the reason must be the measured times.
  • D: Bottle color was never tested, so the data cannot support changing it.

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

A version records alarm times of 11, 9, and 10 seconds. The target is an average under 10 seconds. Does this version pass?

Reviewed
  1. A.No, the average is exactly 10 s, which is not under 10 s
  2. B.Yes, because two of the three trials came in at 10 s or faster
  3. C.No, because the average is 11 s, which is above the target
  4. D.Yes, the average is 10 s, which satisfies a target of under 10 s
Show the worked solution ▾

Answer: A. No, the average is exactly 10 s, which is not under 10 s

  1. Step 1: Add the trials: 11 + 9 + 10 = 30.
  2. Step 2: Divide by the count: 30 divided by 3 trials gives an average of 10 s.
  3. Step 3: Read the target wording: The target says under 10 s. Exactly 10 s is not under 10 s.

Why it's right: The three trials average exactly 10 s. A target of under 10 s is not met by a value that lands on 10 s.

Why the others miss:
  • B: The target is set on the average, not on how many individual trials clear it.
  • C: 11 s is the slowest single trial, not the average of the three.
  • D: Under 10 s excludes 10 s itself, so landing on the line is a fail.

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.
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.