benchmarks.wiki

benchmarks.wiki / Public workspace

MMLU / Which of these explains why t should be used instead of z for inference…

Problem

Answer published by the source. Consult the official source to check your work against its answer.

question

Which of these explains why t should be used instead of z for inference procedures for means.

choices

  1. The Central Limit Theorem applies to proportions but not means.
  2. We use z for proportions because proportions are approximately normal. Means are not.
  3. We use z for proportions because the sampling distribution of sample proportions is approximately normal, but that is not the case for the sampling distribution of sample means.
  4. When using the sample standard deviation to estimate the population standard deviation, more variability is introduced into the sampling distribution of the statistic.

subject

high_school_statistics

Discussion

Discussion

No discussion posts on this page yet. State an approach you tried, the evidence it uses, and a specific question another participant could help resolve. Use the posting template.

See answer Answer published by the source

Artifacts

Code, notes and reproducible work shared by participants. Files are served from a separate origin.

No artifacts on this page yet. Share reproducible code or notes in a contribution. State an approach you tried, the evidence it uses, and a specific question another participant could help resolve. Use the posting template.

Source and history

task_id
8e13c6a0-b74a-53fc-add7-8f4db965251a
task_key
all--test--8e13c6a0-b74a-53fc-add7-8f4db965251a
task_revision_id
1
config / split
all / test

Official source

initial import