Exam 4 - NHST (reject or fail to reject)
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45 Terms
Q: What is the null hypothesis (H₀)?
A: The default assumption that there is no effect, no difference, or no relationship.
Q: What is the alternative hypothesis (H₁ or Hₐ)?
A: The researcher's claim that an effect, difference, or relationship exists.
Q: What does "null" mean?
A: Nothing has changed; no effect; no difference
Q: What does the alternative hypothesis represent?
A: The possibility that something has changed or an effect exists.
Q: Which hypothesis always contains an equality?
A: The null hypothesis (H₀).
Q: Which symbols can appear in H₀? (null)
A: =, ≤, or ≥
Q: Which symbols can appear in H₁? (alternative)
A: ≠, <, or >
Q: Can the alternative hypothesis ever contain "="?
no
Q: Can the null hypothesis ever contain only ">" or "<"?
no
Q: A researcher wants to determine whether two means are different. What are the hypotheses?
H₀: μ = μ
H₁: μ ≠ μ
Q: A researcher wants to determine whether a treatment increases a score. What are the hypotheses?
H₀: μ ≤ comparison value
H₁: μ > comparison value
Q: A researcher wants to determine whether a treatment decreases a score. What are the hypotheses?
H₀: μ ≥ comparison value
H₁: μ < comparison value
Q: If the claim is "different," what symbol belongs in H₁?
A: ≠
Q: If the claim is "greater than" or "increases," what symbol belongs in H₁?
>
Q: If the claim is "less than" or "decreases," what symbol belongs in H₁?
<
Q: What are the only two decisions made after hypothesis testing?
Reject H₀
Fail to reject H₀
Q: Do we ever "accept H₀"?
A: No. We only fail to reject H₀
Q: What does rejecting H₀ mean?
A: There is sufficient evidence to support H₁
Q: What does failing to reject H₀ mean?
A: There is not enough evidence to support H₁.
Q: What is a Type I error?
A: Rejecting a true H₀ (false positive).
Q: What is a Type II error?
A: Failing to reject a false H₀ (false negative).
: Which Greek letter represents the probability of a Type I error?
A: α (alpha)
Q: Which Greek letter represents the probability of a Type II error?
A: β (beta)
Q: Which error is a false positive?
A: Type I error.
Q: Which error is a false negative?
A: Type II error.
Q: If H₀ is true and you reject it, what occurred?
A: Type I error.
Q: If H₀ is false and you fail to reject it, what occurred?
A: Type II error.
Q: If H₀ is true and you fail to reject it, what occurred?
A: Correct decision.
Q: If H₀ is false and you reject it, what occurred
A: Correct decision.
Q: "No effect" refers to which hypothesis?
A: H₀.
Q: "No difference" refers to which hypothesis?
A: H₀.
Q: "No relationship" refers to which hypothesis?
A: H₀.
Q: "There is an effect" refers to which hypothesis?
A: H₁
Q: "There is a difference" refers to which hypothesis?
A: H₁.
Q: "There is a relationship" refers to which hypothesis?
A: H₁.
: Which hypothesis represents the researcher's claim?
A: H₁ (alternative hypothesis).
Which hypothesis represents the status quo or default assumption?
H₀ (null hypothesis).
A researcher believes a new medication lowers blood pressure. Write H₀ and H₁.
H₀: μ ≥ current mean blood pressure
H₁: μ < current mean blood pressure
Q: A researcher believes a new study method improves exam scores. Write H₀ and H₁.
A:
H₀: μ ≤ current mean score
H₁: μ > current mean score
Q: A researcher wants to know whether a new diet changes cholesterol levels in either direction. Write H₀ and H₁
H₀: μ = current mean cholesterol
H₁: μ ≠ current mean cholesterol
Q: A study concludes a treatment works, but in reality it has no effect. What happened
A: Type I error.
Q: A study concludes there is no evidence a treatment works, but the treatment actually does work. What happened?
A: Type II error.
Q: A researcher rejects H₀ when H₀ is actually true. What occurred?
A: Type I error.
Q: A researcher fails to reject H₀ when H₀ is actually false. What occurred?
A: Type II error.
Q: What four outcomes should I memorize?
Reality | Decision | Result |
|---|
H₀ is true | Reject H₀ | Type I Error |
H₀ is true | Fail to reject H₀ | Correct |
H₀ is false | Reject H₀ | Correct |
H₀ is false | Fail to reject H₀ | Type II Error |