Statistics: data and sampling

Identify sampling bias.

How to study this source

• How do we reason under uncertainty?

  coreNamed section and worked examples

  Identify sampling bias.

• What can a small dataset tell me, and what can it not?

  core1.2 Data, Sampling, and Variation in Data and Sampling

  Compare sampling methods and explain who a convenience sample leaves out.

Ideas and questions

Read background definitions when a term blocks the argument. Then return to the source and reconstruct its claim in your own words.

Read alongside, read against

• Statistics: centre

  Barbara Illowsky · Susan Dean. Compare assumptions, evidence and scope with the source above. These are editorial companions, not necessarily direct responses.

• Statistics: spread

  Barbara Illowsky · Susan Dean. Compare assumptions, evidence and scope with the source above. These are editorial companions, not necessarily direct responses.

• Probability: terminology

  Barbara Illowsky · Susan Dean. Compare assumptions, evidence and scope with the source above. These are editorial companions, not necessarily direct responses.

• Probability: independent and mutually exclusive events

  Barbara Illowsky · Susan Dean. Compare assumptions, evidence and scope with the source above. These are editorial companions, not necessarily direct responses.

• Probability: two basic rules

  Barbara Illowsky · Susan Dean. Compare assumptions, evidence and scope with the source above. These are editorial companions, not necessarily direct responses.