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Data, probability and statistics I · Lesson 07 / 12

Who entered the sample?

The table starts with route A. Choosing the first five rows is easy but leaves out route B. Size is not a sample’s only feature.

Learning paths18 min

Let's discover together

  1. 1

    Load Missions and compare All with First rows, size 5. The first uses the whole table; the second exploits its order. Calculate and record the selected ids, not just the displayed mean.

  2. 2

    Pseudorandom shuffles the table and selects without replacement: each row appears at most once. A seed makes the simulation repeatable. Changing the seed changes the selection, not the population of interest.

  3. 3

    Random selection reduces dependence on personal choice when the selection frame covers relevant cases. It cannot recover people or events absent from that frame. A particular random sample can also be unbalanced by chance.

  4. 4

    A volunteers-only survey may exclude people who did not see it or did not want to respond. More responses from the same group do not automatically fix selection. Report method, size, coverage and nonresponse before generalizing.

Evidence lab

Experiment with fictional deliveries at Aurora station. Analysis runs in this browser. Nothing entered here is sent to the server.

The workshop resets when you leave or reload. Download data and report to keep your work, or send the report to the activity editor, which keeps a draft in this browser. Completion and XP belong to the account.

Header id,group,minutes; one delivery per row; unique id; groups A/B; decimal point; duration 0–1440 with up to two decimal places. Blank means unknown. Up to 100 rows. No quotes or decimal commas. Use invented data.

Selection uses the entered table, including missing values. A draw does not guarantee representativeness. The same seed reproduces selection; it cannot recover cases outside the table.

Make a prediction and analyze the table.

Virtual bag: model with replacement

There are four equally likely tokens; choose how many are blue. Each token returns before the next draw. This is a deterministic simulation, without prizes, money or real observations.

Repeating the seed repeats the sequence. More draws do not guarantee a closer result in every run and do not validate the real-world model.

Two rules, the same accuracy

Ten fictional cases: nine normal and one failure. Rules defined for this example; no AI training or real equipment testing. Same number correct, different consequences.

Two rules, the same accuracy
RuleCorrect / totalMissed failuresFalse alarms

Your investigation report

Official links and next step

✦
YOUR MISSION

Distinguish convenience, random selection and population coverage.

Now it's your turn

Discovery workshop

Predict, check, explain

Distinguish convenience, random selection and population coverage.
Build your answers and check when you are ready.
A moment to understand

Which limitation remains after drawing a sample?

I need a hint

Large, random and suitable samples are not synonyms. Method and population bound the conclusion.

Loading your journey…

Take it with you

Describe a fictional plan to observe mornings and afternoons without selecting only friends. State the selection frame, possible omissions and a rule fixed before seeing results. Do not collect personal information.

At your own pace

My files and GitHub

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Student guide

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