7.5 Interpreting p-Values

Cards (23)

  • What is a p-value in hypothesis testing?
    Probability of test statistic
  • A common value for α is 0.05.

    True
  • The p-value helps determine if results are statistically significant.

    True
  • If the p-value is less than α, we reject the null hypothesis.
  • Match the p-value relationship with its interpretation:
    p≤αp \le \alpha ↔️ Reject the null hypothesis
    p>αp > \alpha ↔️ Fail to reject the null hypothesis
  • If α = 0.05 and the p-value is 0.03, we reject the null hypothesis.

    True
  • What is the significance level (α) in hypothesis testing?
    Maximum probability of Type I error
  • What type of error occurs if α = 0.05 and the p-value is 0.03?
    Type I error
  • Type I errors are more likely when α is larger.
    True
  • What is the probability of a Type I error if the significance level is 0.05?
    5%
  • The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming the null hypothesis is true
  • A p-value assumes the null hypothesis is true.

    True
  • The significance level is set by the researcher before conducting the test.
  • Steps for interpreting a p-value in hypothesis testing:
    1️⃣ Compare the p-value to α
    2️⃣ Reject the null hypothesis if p < α
    3️⃣ Fail to reject the null hypothesis if p ≥ α
  • What is the decision if the p-value is 0.03 and the significance level is 0.05?
    Reject the null hypothesis
  • If α = 0.05 and the p-value is 0.03, the result is statistically significant.

    True
  • Steps to interpret p-values in hypothesis testing:
    1️⃣ Compare the p-value to the significance level (α)
    2️⃣ If p < α, reject the null hypothesis
    3️⃣ If p ≥ α, fail to reject the null hypothesis
  • The p-value is used to determine the statistical significance of the results.
  • Match the significance level with its interpretation:
    0.05 ↔️ 5% chance of rejecting a true null hypothesis
    0.01 ↔️ 1% chance of rejecting a true null hypothesis
  • What is a Type I error in hypothesis testing?
    Incorrectly rejecting true null hypothesis
  • The significance level (α) is the maximum probability of incorrectly rejecting a true null hypothesis, known as a Type I error
  • What is the interpretation if the p-value is 0.07 and the significance level is 0.05?
    Fail to reject the null hypothesis
  • If α = 0.05 and the p-value is 0.07, we fail to reject the null hypothesis because 0.07 > 0.05