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Begin with a question.
Investigate with data.

Lessons, explained exercises, real observation samples and your research report. This file works without an internet connection.

Download your work as JSON to keep your own backup.

60 MINUTES / SUGGESTED STUDY

Astronomy Foundations

Investigate a scientific question through light, spectra, transits and observation records.

LESSON 1

Use light as a measure

Objective: Distinguish distance from light-travel time.

An image reaches us after light has travelled. Distance and travel time are different quantities; compare them only after keeping the units consistent.

This exercise assumes a constant distance and the speed of light in vacuum. The actual distance between Earth and a spacecraft may change.

t = d / c

A worked example

Model example: a 300,000 km distance / 300,000 km/s speed = 1 s. These rounded inputs illustrate the relationship only.

What happens to travel time when distance doubles at constant speed? It halves It doubles It stays unchanged

Answer and explanation

It doubles · Since t = d/c, time is proportional to distance at fixed c.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.JPL · Astrodynamic parameters ↗The source link requires an internet connection.

LESSON 2

Measure a spectral shift

Objective: Calculate a dimensionless shift from wavelengths.

Compare a spectral line’s laboratory and observed wavelengths. Interpreting the shift depends on its physical context.

Here we calculate only z. It is not automatically a distance or a velocity valid in every regime. The line must first be identified correctly.

z = (λobs − λrest) / λrest

A worked example

Teaching inputs: 500 nm → 505 nm. z = (505 − 500)/500 = 0.01. Both wavelengths use the same unit.

A 500 nm line is measured at 505 nm. What is z? 5 0.01 505

Answer and explanation

0.01 · The difference is 5 nm and the reference is 500 nm: 5/500 = 0.01. The units cancel.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NASA · Spectroscopy 101 ↗The source link requires an internet connection.

LESSON 3

Read a transit light curve

Objective: Separate a measured dip from a simple radius model.

A transit may cause a dip as an object passes between the observer and a star. Other effects can also produce a single decrease.

For a uniformly bright stellar disc and a small dark planet, depth is approximately the square of the radius ratio. Limb darkening and noise affect real analysis.

δ = 1 − Fin/Fout; Rp/Rs ≈ √δ

A worked example

If normalized flux falls from 1.00 to 0.99, the model depth is 0.01. In the simple model, Rp/Rs ≈ √0.01 = 0.10.

Which radius ratio corresponds to a 1% depth in this simple model? 0.01 0.10 1.00

Answer and explanation

0.10 · The square root of 0.01 is 0.10. This does not establish a planet’s mass or life.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NASA · What is a transit? ↗The source link requires an internet connection.

LESSON 4

Preserve observation provenance

Objective: Record a dataset’s time, instrument and processing.

A graph becomes interpretable with its source and processing steps. Observation and download dates may differ.

Recording product identifier, time system, unit, quality flag and processing version lets another person inspect the same selection.

Gözlem ≠ erişim ≠ işleme / Observation ≠ retrieval ≠ processing

A worked example

Keep observation time, retrieval time and product identifier in separate fields instead of reporting only “downloaded on 24 October”.

Which information best helps locate the same observation? Only the graph colour Product identifier, source and observation time Only the downloader’s name

Answer and explanation

Product identifier, source and observation time · Identifier and time lead back to the source data record.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.MAST · Data archive ↗The source link requires an internet connection.

Check your understanding

Revisit these questions before and after studying. Consider your reasoning together with your answers; this section does not issue a formal qualification.

What happens to travel time when distance doubles at constant speed? It halves It doubles It stays unchanged

Answer and explanation

It doubles · Since t = d/c, time is proportional to distance at fixed c.

A 500 nm line is measured at 505 nm. What is z? 5 0.01 505

Answer and explanation

0.01 · The difference is 5 nm and the reference is 500 nm: 5/500 = 0.01. The units cancel.

Which information best helps locate the same observation? Only the graph colour Product identifier, source and observation time Only the downloader’s name

Answer and explanation

Product identifier, source and observation time · Identifier and time lead back to the source data record.

60 MINUTES / SUGGESTED STUDY

Scientific Data Literacy

Work with units, missing values, uncertainty and reproducibility.

LESSON 1

Keep numbers with units

Objective: Handle unit conversion and missing data explicitly.

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.

2 h × 3600 s/h = 7200 s

A worked example

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? 6.67 10 0

Answer and explanation

10 · (9 + 11)/2 = 10. A blank cell is not a measured zero.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NIST · SI units ↗The source link requires an internet connection.

LESSON 2

Summarize a distribution

Objective: Show that centre and spread convey different information.

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.

x̄ = Σxi/n; aralık/range = xmax − xmin

A worked example

[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? Yes, always No; examine spread as well Only if the sample count is odd

Answer and explanation

No; examine spread as well · A central value alone does not determine shape and spread.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NIST · Measures of location ↗The source link requires an internet connection.

LESSON 3

Include uncertainty in the result

Objective: Explain what an uncertainty interval means and its limits.

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.

Sonuç / result = değer / value + tanımlı belirsizlik / stated uncertainty

A worked example

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? Interval type, unit and calculation method Only a colour No explanation is needed

Answer and explanation

Interval type, unit and calculation method · An uncertainty value is interpreted with its definition and method.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NIST · Measurement uncertainty ↗The source link requires an internet connection.

LESSON 4

Make an analysis reproducible

Objective: Reconstruct a result from the same inputs and steps.

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.

Veri + sürüm + yöntem + ayarlar → yeniden inceleme / Data + version + method + settings → inspection

A worked example

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? Only an image of the result Data version, method and settings Only a title

Answer and explanation

Data version, method and settings · Inputs and processing steps allow the same selection to be reconstructed.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.Zenodo · DOI versioning ↗The source link requires an internet connection.

Check your understanding

Revisit these questions before and after studying. Consider your reasoning together with your answers; this section does not issue a formal qualification.

What is the mean of [9, blank, 11] when the missing value is excluded? 6.67 10 0

Answer and explanation

10 · (9 + 11)/2 = 10. A blank cell is not a measured zero.

Does an equal mean show that two datasets have the same distribution? Yes, always No; examine spread as well Only if the sample count is odd

Answer and explanation

No; examine spread as well · A central value alone does not determine shape and spread.

Which package best supports an independent rerun? Only an image of the result Data version, method and settings Only a title

Answer and explanation

Data version, method and settings · Inputs and processing steps allow the same selection to be reconstructed.

60 MINUTES / SUGGESTED STUDY

Space Engineering Foundations

Connect orbits, energy, mass and testable requirements.

LESSON 1

Model a circular orbit

Objective: Distinguish altitude from distance to the centre.

In a circular two-body model, speed depends on distance from the centre. Use radius, rather than altitude above the surface, in the equation.

This model omits drag, Earth’s oblateness and manoeuvres. An educational calculation is not a mission position.

r = R + h; v = √(μ/r)

A worked example

With R = 6,378.137 km, h = 400 km and μ = 398,600.4418 km³/s², r = R+h and v is about 7.67 km/s.

What does r mean in v = √(μ/r)? Only altitude above the surface Distance from Earth’s centre Satellite length

Answer and explanation

Distance from Earth’s centre · In this gravity model r is distance from the centre; add altitude to R.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.ESA · Types of orbits ↗The source link requires an internet connection.

LESSON 2

Build an energy budget

Objective: Calculate the difference between power and energy.

Power is the rate of energy use. A mission budget separates loads and operating durations into individual rows.

Our simple budget assumes constant power. Battery efficiency, temperature, ageing and engineering qualification are outside this calculation.

E(Wh) = P(W) × t(h)

A worked example

A 5 W instrument operated for 2 hours uses 10 Wh. Operating it for 20 minutes uses about 1.67 Wh.

What energy is used by a 5 W device over two hours? 2.5 Wh 10 Wh 10 W

Answer and explanation

10 Wh · 5 × 2 = 10 Wh. W is power; Wh is energy.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NASA · Small spacecraft power subsystems ↗The source link requires an internet connection.

LESSON 3

Examine mass ratio

Objective: Distinguish ideal delta-v from real flight.

In the ideal rocket equation, initial-to-final mass ratio appears inside a logarithm. With specific impulse in seconds and standard gravity in m/s², delta-v is in m/s.

This relationship omits drag and gravity losses. It does not by itself qualify a vehicle for flight.

Δv = Isp · g0 · ln(m0/mf)

A worked example

For Isp = 300 s, g0 = 9.80665 m/s² and m0/mf = 2, ideal Δv is approximately 2,039 m/s.

At the same Isp, what is ideal Δv when m0/mf is 1? Zero Equal to Isp Infinite

Answer and explanation

Zero · ln(1)=0. With no expelled propellant mass, the model gives zero ideal velocity change.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NASA Glenn · Ideal rocket equation ↗The source link requires an internet connection.

LESSON 4

Write a testable requirement

Objective: Connect a success criterion to a measurement and test.

Stating what must be achieved, under which conditions and by which method makes a design goal easier to inspect.

This exercise uses a simple sensor mission. Testing a requirement and assessing fitness for intended use address different questions.

Gereksinim + koşul + ölçüt + yöntem / Requirement + condition + criterion + method

A worked example

Instead of “collect good data”, write: “The model sensor shall produce 60 timestamped samples during a 10-minute teaching trial; verify by counting output rows.”

Which statement is more testable? Make an excellent satellite Produce 60 timestamped samples in 10 minutes Change the future

Answer and explanation

Produce 60 timestamped samples in 10 minutes · The sample count, duration and verification method can be specified.

In your own words, state an assumption behind this method and one effect that could change the result. I read the lesson and considered my own explanation.NASA · Systems Engineering Handbook appendix ↗The source link requires an internet connection.

Check your understanding

Revisit these questions before and after studying. Consider your reasoning together with your answers; this section does not issue a formal qualification.

What does r mean in v = √(μ/r)? Only altitude above the surface Distance from Earth’s centre Satellite length

Answer and explanation

Distance from Earth’s centre · In this gravity model r is distance from the centre; add altitude to R.

What energy is used by a 5 W device over two hours? 2.5 Wh 10 Wh 10 W

Answer and explanation

10 Wh · 5 × 2 = 10 Wh. W is power; Wh is energy.

Which statement is more testable? Make an excellent satellite Produce 60 timestamped samples in 10 minutes Change the future

Answer and explanation

Produce 60 timestamped samples in 10 minutes · The sample count, duration and verification method can be specified.

QUESTION · METHOD · RESULT

Plan your first investigation.

Measure a known planetary transit

Inspect a dated observation selection; report the dip, method and limitations.

How can I measure the dip in the selected light curve?

Open the transit selection in Data Studio; record source and time system.
Choose out-of-transit and in-transit intervals and explain the selection.
Inspect flux ratio, data gaps and outliers.
Report method and uncertainty; do not claim a new discovery.

Use these criteria to review your work

Question and prediction: Explain what you measure and what you expect.
Method and data: Record source, units, selection and calculations so they can be followed.
Result and evidence: Connect the conclusion to a graph or measurement.
Uncertainty and next step: State limitations and what another measurement could add.

NASA · Exoplanet Watch ↗The source link requires an internet connection.

Investigate a geomagnetic time series

Examine change and sampling intervals in NOAA’s dated Kp product.

How does the Kp product change during the chosen interval?

Open the Kp selection and record its date and source definition.
Choose two intervals; report sample counts and missing records.
Show the observed difference in a table or plot.
Do not infer a long-term climate conclusion from one event; state limitations.

Use these criteria to review your work

Question and prediction: Explain what you measure and what you expect.
Method and data: Record source, units, selection and calculations so they can be followed.
Result and evidence: Connect the conclusion to a graph or measurement.
Uncertainty and next step: State limitations and what another measurement could add.

NOAA SWPC · Planetary K-index ↗The source link requires an internet connection.

From shadow to angle: reconstruct a method

An explicit geometry exercise inspired by historical measurement traditions.

How can I estimate altitude angle from a vertical stick’s shadow?

Open the vertical-stick model in the instrument lab.
State the level-ground and vertical-stick assumptions; choose a measurement or labelled model input.
Record stick height and shadow length in the same unit.
Calculate altitude and discuss alignment and length-reading errors.

Use these criteria to review your work

Question and prediction: Explain what you measure and what you expect.
Method and data: Record source, units, selection and calculations so they can be followed.
Result and evidence: Connect the conclusion to a graph or measurement.
Uncertainty and next step: State limitations and what another measurement could add.

QDL · Al-Biruni manuscript record ↗The source link requires an internet connection.

PACKAGED ARCHIVE SAMPLES

Inspect the data with its source.

The CSV files below are small selections from observation sources. The plot displays selected columns; it is not an independent validation of a scientific discovery.

Kepler-8: observed transit light curve

Quality-filtered, median-scaled PDC light curve from Kepler quarter 0 observations of the known Kepler-8 b system.

Source: NASA Kepler / STScI MAST · KIC 6922244 · Q0 ↗
Usage information: Public domain · NASA Kepler / STScI MAST acknowledgement retained
Observation range: 2009-05-02T00:40:13.639Z → 2009-05-11T18:06:13.939Z
Retrieved at: 2026-10-24
SHA-256: 496813d1b9cff371c9799a1b67731b36883829ab4ab1269e006b780f64884b06
Processing: Of 476 source rows, 453 rows with finite TIME, PDCSAP_FLUX and PDCSAP_FLUX_ERR and SAP_QUALITY=0 were retained. Flux and errors were divided by median 49778.21484375 e−/s; times and order were retained. No folding, smoothing, detrending or new physical fit was performed. CSV values are rounded to the shown decimal precision.

X Y

First 40 rows. The CSV file contains the complete sample.
time_bkjd	relative_flux	relative_flux_error
120.53979406207	1.0002383228	0.0001783512
120.56022845695	1.0000117710	0.0001795209
120.58066275172	0.9997001543	0.0001798123
120.60109724637	1.0002692411	0.0001790063
120.62153164102	1.0001217902	0.0001797401
120.64196593544	0.9998442309	0.0001799080
120.66240032986	0.9998932766	0.0001795127
120.68283482416	1.0001028782	0.0001796994
120.70326911835	1.0001047616	0.0001794421
120.72370351241	0.9997278553	0.0001798088
120.74413800637	0.9999176033	0.0001798240
120.76457230021	1.0000772175	0.0001796182
120.78500669404	1.0001788402	0.0001799140
120.80544108764	1.0000010986	0.0001795938
120.84630987473	0.9997664641	0.0001796718
120.86674426810	0.9999123456	0.0001795586
120.88717876136	1.0003104395	0.0001794206
120.90761305449	1.0002241191	0.0001792326
120.92804744752	1.0001653428	0.0001797053
120.94848194042	1.0000646618	0.0001792410
120.96891623332	1.0000573638	0.0001793693
120.98935062600	1.0003089485	0.0001788842
121.00978491867	1.0003448892	0.0001790693
121.03021941122	1.0000079258	0.0001792349
121.05065380366	0.9997296602	0.0001792842
121.07108819599	0.9938769807	0.0001792068
121.09152258819	0.9915901966	0.0001796106
121.11195698040	0.9909270206	0.0001794225
121.13239137238	0.9913668622	0.0001787781
121.15282566423	0.9913658421	0.0001788844
121.17326015609	0.9957597854	0.0001792247
121.19369454783	0.9998936690	0.0001794203
121.21412883945	1.0001804096	0.0001797470
121.23456333096	1.0001450967	0.0001794153
121.25499772235	0.9997372721	0.0001797618
121.27543201362	1.0000908718	0.0001799709
121.29586640478	0.9996581712	0.0001793833
121.31630089583	0.9998228078	0.0001793564
121.33673528687	0.9999838345	0.0001797304
121.35716957768	0.9999994507	0.0001798273

Columns and units

time_bkjd [day · BJD − 2454833 · TDB] · FITS TIME column; not a UTC timestamp.
relative_flux [relative flux] · PDCSAP_FLUX divided by the selected-point median.
relative_flux_error [relative flux] · Source PDCSAP_FLUX_ERR divided by the same median.
quality_flag [flag] · SAP_QUALITY; only zero-flag rows in this selection.

NOAA: dated Kp selection

Retained 56-record selection of the NOAA Kp product for 17–23 October 2026; not a live feed.

Source: NOAA / Space Weather Prediction Center ↗
Usage information: NOAA public data · preserve attribution and consult source terms
Observation range: 2026-10-17T00:00:00Z → 2026-10-23T21:00:00Z
Retrieved at: 2026-10-24
SHA-256: 143b66f177151c86dbec7efacf29b52bff8980033bf8636874dd173ed8da042e
Processing: Source time_tag was interpreted as UTC and converted to hours from the first record. Kp and station_count were copied to CSV without alteration. Missing measurements were not filled with zero. Later provider updates do not change this retained version.

X Y

First 40 rows. The CSV file contains the complete sample.
hours_since_start_utc	kp	station_count
0	2.0	8
3	1.0	8
6	0.67	8
9	0.67	8
12	0.67	8
15	2.67	8
18	3.0	8
21	1.0	8
24	2.0	8
27	2.33	8
30	2.0	8
33	1.67	8
36	0.33	8
39	1.33	8
42	1.67	8
45	0.33	8
48	0.33	8
51	0.33	8
54	0.33	8
57	1.0	8
60	0.33	8
63	0.33	8
66	0.67	8
69	0.67	8
72	1.0	8
75	1.0	8
78	1.0	8
81	2.0	8
84	2.0	8
87	2.67	8
90	2.67	8
93	3.0	8
96	3.67	8
99	4.0	8
102	2.0	8
105	2.33	8
108	1.67	8
111	3.33	6
114	3.67	6
117	4.67	6

Columns and units

hours_since_start_utc [hour since 2026-10-17 00:00 UTC] · Hours elapsed from the first source UTC timestamp.
kp [Kp index · dimensionless] · NOAA Kp product; values may be provisional and revised.
station_count [count] · Station count reported by the source.

YOUR OWN WORK

Build your research report.

Notes are not sent from this file to a server. Export the report to keep your own copy. Distinguish source measurements from your interpretation.

My question and predictionData, instrument, dates and unitsMy methodResults and plot explanationUncertainties and limitationsSources and versionsNext measurement / questionMy contribution and changes

Begin with a question.Investigate with data.

Astronomy Foundations

Use light as a measure

Measure a spectral shift

Read a transit light curve

Preserve observation provenance

Check your understanding

Scientific Data Literacy

Keep numbers with units

Summarize a distribution

Include uncertainty in the result

Make an analysis reproducible

Check your understanding

Space Engineering Foundations

Model a circular orbit

Build an energy budget

Examine mass ratio

Write a testable requirement

Check your understanding

Plan your first investigation.

Measure a known planetary transit

Investigate a geomagnetic time series

From shadow to angle: reconstruct a method

Inspect the data with its source.

Kepler-8: observed transit light curve

NOAA: dated Kp selection

Build your research report.

Begin with a question.
Investigate with data.