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SPACETRC / DISCOVERY AND RESEARCH

Scientific Data Literacy

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SPACETRC / OPEN LEARNING LAB

Scientific Data Literacy

Work with units, missing values, uncertainty and reproducibility.

3 LEARNING TRACKS12 SHORT LESSONSTR / EN
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A lesson is recorded as practised when its answer is correct and you have written a reflection of at least 20 characters. This checks participation and basic understanding; it is not a qualification or accredited certificate.

Before you begin 3 questions
What is the mean of [9, blank, 11] when the missing value is excluded?
Does an equal mean show that two datasets have the same distribution?
Which package best supports an independent rerun?
01

LEARNING OBJECTIVE

Keep numbers with units

Handle unit conversion and missing data explicitly.

Not yet practised

A number without a unit does not adequately describe a physical quantity. A conversion expresses the same quantity in another unit.

A missing measurement is not zero. Mark blank cells separately and report how many samples were used or excluded.

WORKED EXAMPLE / MODEL2 h × 3600 s/h = 7200 s

2 hours = 7,200 seconds. [9, blank, 11] contains two valid samples; the mean is 10 without replacing the blank by zero.

What is the mean of [9, blank, 11] when the missing value is excluded?
Explore the primary source: NIST · SI units ↗
02

LEARNING OBJECTIVE

Summarize a distribution

Show that centre and spread convey different information.

Not yet practised

The mean summarizes the centre of a dataset. Datasets with the same mean can have different spreads.

Inspect measurement context before removing an outlier. Spread and measurement uncertainty are not assumed to be identical.

WORKED EXAMPLE / MODELx̄ = Σxi/n; aralık/range = xmax − xmin[9,10,11] and [1,10,19] both have a mean of 10, but their ranges are 2 and 18.

Does an equal mean show that two datasets have the same distribution?
Explore the primary source: NIST · Measures of location ↗
03

LEARNING OBJECTIVE

Include uncertainty in the result

Explain what an uncertainty interval means and its limits.

Not yet practised

An uncertainty statement accompanies values attributed to a measurement. Repeats, calibration and method effects may contribute separately.

State the interval type and calculation conditions. Overlap between two intervals is not, by itself, a test of equality.

WORKED EXAMPLE / MODELSonuç / result = değer / value + tanımlı belirsizlik / stated uncertainty

Intervals drawn for 2.0 ± 0.2 and 2.3 ± 0.2 may overlap. That drawing alone does not prove that two methods give equal results.

If you report ±0.2, what should accompany it?
Explore the primary source: NIST · Measurement uncertainty ↗
04

LEARNING OBJECTIVE

Make an analysis reproducible

Reconstruct a result from the same inputs and steps.

Not yet practised

Keep the data version, row selection, transformations and calculation settings with a shared result. A screenshot may not preserve enough to rerun the method.

Identify a changed file as a new version. An independent rerun helps others inspect the method.

WORKED EXAMPLE / MODELVeri + sürüm + yöntem + ayarlar → yeniden inceleme / Data + version + method + settings → inspection

Include source URL, data-file date, selected time interval, unit conversion and the formula in your report package.

Which package best supports an independent rerun?
Explore the primary source: Zenodo · DOI versioning ↗
Check your learning 3 questions
What is the mean of [9, blank, 11] when the missing value is excluded?
Does an equal mean show that two datasets have the same distribution?
Which package best supports an independent rerun?

The same short self-check before and after practice helps you review what changed. It does not measure expertise independently.

Turn practice into a research report.

Write a question, record your inputs, compare results and discuss uncertainty.

Start this project

YOUR WORK / YOUR COPY

Keep a portable learning portfolio.

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Download offline study pack ↓

Study pack: release 4.0.0 · content dated 24 October 2026 · self-contained lessons, exercises, project templates and source-labelled sample data. Unzip and open index.html. No external API is required.

SPACETRC / KNOWLEDGE

Follow your curiosity.