A null hypothesis requires several assumptions, a basic one of which is:

Question

Options

• AThat the variables are significant
• BThe variables are independent
• CThat the sample size is adequate
• DThat the confidence interval is ?2 standard deviations

• A
  11% (3)
• B
  81% (22)
• C
  4% (1)
• D
  4% (1)

Explanation

Null hypothesis testing requires that variables be independent of each other - meaning the outcome of one observation doesn't influence another - because the statistical math underlying tests like chi-square or t-tests is built on this assumption; violating it invalidates the test entirely.

Why the distractors are wrong:

• A is backwards logic - significance is what you're testing for, not a prerequisite assumption.
• C (adequate sample size) is a practical concern for statistical power, not a foundational assumption of the null hypothesis itself.
• D is a misstatement - confidence intervals and standard deviations are output metrics, and the "±2 standard deviations" framing is a rule of thumb for normal distributions, not an assumption of H₀.

Memory tip: Think of "null" as "nothing going on between these things" - for that to be a meaningful baseline, the variables must be free to act on their own, i.e., independent. If they're already linked, testing whether they're linked is meaningless.

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