Unit 08 · lesson

Evidence Check: Write the Evidence Memo

Assume an analysis found that one group in a fictional dataset has a higher average outcome than another.

Your evidence

Write a data evidence memo with these headings:

Question
Finding
Evidence
Uncertainty
Alternative explanation
Limitation
Recommended next step

Keep the finding to one sentence. The rest of the memo should explain why that sentence is or is not defensible.

Check your reasoning

Communication is not the victory lap after analysis. It is where unsupported certainty becomes visible.

Done when

A reader can tell what you found, why you think it is true, what else could explain it, and what you would investigate next.

1. Dataset

Fictional robot test runs. No student or personal data.

run	model	sec	battery	°C	done
R-101	Atlas	52	88	22	yes
R-102	Atlas	57	79	23	yes
R-103	Nova	64	74	24	yes
R-104	Nova	71	—	27	no
R-105	Pulse	48	92	21	yes
R-106	Pulse	55	84	25	yes
R-107	Atlas	68	69	29	no
R-107	Atlas	68	69	29	no

2. Quick chart

ViewY

Change the variables before deciding what the data “says.” The same rows can support different questions.

3. Editable Pandas analysis

Runs locally in your browser. First use downloads Pandas and its verified dependencies from Robotnix.

import pandas as pd

rows = [
    {"run_id": "R-101", "model": "Atlas", "duration_s": 52, "battery_pct": 88, "ambient_c": 22, "completed": True},
    {"run_id": "R-102", "model": "Atlas", "duration_s": 57, "battery_pct": 79, "ambient_c": 23, "completed": True},
    {"run_id": "R-103", "model": "Nova", "duration_s": 64, "battery_pct": 74, "ambient_c": 24, "completed": True},
    {"run_id": "R-104", "model": "Nova", "duration_s": 71, "battery_pct": None, "ambient_c": 27, "completed": False},
    {"run_id": "R-105", "model": "Pulse", "duration_s": 48, "battery_pct": 92, "ambient_c": 21, "completed": True},
    {"run_id": "R-106", "model": "Pulse", "duration_s": 55, "battery_pct": 84, "ambient_c": 25, "completed": True},
    {"run_id": "R-107", "model": "Atlas ", "duration_s": 68, "battery_pct": 69, "ambient_c": 29, "completed": False},
    {"run_id": "R-107", "model": "Atlas ", "duration_s": 68, "battery_pct": 69, "ambient_c": 29, "completed": False},
]
df = pd.DataFrame(rows).drop_duplicates("run_id")
df["model"] = df["model"].str.strip()

summary = df.groupby("model").agg(
    runs=("run_id", "count"),
    mean_duration=("duration_s", "mean"),
    completion_rate=("completed", "mean"),
).round(2)

print(summary)
print("\nWrite one bounded finding and one limitation from this evidence.")

Output

Run the analysis to see evidence.

Ready. Predict before you run.

Runtime boundary: Robotnix serves the core Pyodide runtime and the SHA-256-verified Pandas dependency set. This workbench does not expose pip, micropip, a shell, filesystem projects, cloud credentials, or arbitrary package installation.