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Goodness of FIt Test Using TI-84 quiz

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Termini in questo insieme (15)

  • What is the purpose of a goodness-of-fit test?
    A goodness-of-fit test compares observed frequencies to expected frequencies to determine if data fits a claimed distribution.
  • How do you calculate expected values for equally distributed categories?
    Expected values are calculated as e = n / k, where n is the sample size and k is the number of categories.
  • What is the formula for degrees of freedom in a goodness-of-fit test?
    Degrees of freedom are calculated as k - 1, where k is the number of categories.
  • Where do you enter observed frequencies on the TI-84 for a GOF test?
    Observed frequencies are entered in list L1 on the TI-84.
  • Where do you enter expected values on the TI-84 for a GOF test?
    Expected values are entered in list L2 on the TI-84.
  • Which menu option on the TI-84 is used for the chi-square goodness-of-fit test?
    Option D, the chi-square GOF test function, is used for the goodness-of-fit test.
  • What should you check in the TI-84 menu before running the GOF test?
    Ensure observed is set to L1, expected is set to L2, and degrees of freedom match your problem.
  • What statistic does the TI-84 provide after running the GOF test?
    The TI-84 provides the chi-square statistic, p-value, degrees of freedom, and contribution values.
  • What is the significance level (alpha) commonly used in hypothesis testing?
    A common significance level is 0.05, or 5%.
  • How do you interpret a p-value greater than alpha in a GOF test?
    If the p-value is greater than alpha, you fail to reject the null hypothesis, indicating the data fits the claimed distribution.
  • What does it mean to fail to reject the null hypothesis in a GOF test?
    It means there is not enough evidence to conclude the observed frequencies do not match the claim distribution.
  • What is the null hypothesis in a goodness-of-fit test?
    The null hypothesis states that observed frequencies match the claimed distribution.
  • What is the alternative hypothesis in a goodness-of-fit test?
    The alternative hypothesis states that observed frequencies do not match the claimed distribution.
  • What are contribution values in the TI-84 GOF test output?
    Contribution values show what each observed frequency contributes to the chi-square statistic.
  • What conclusion can you draw if flavor preferences are evenly distributed among categories?
    If flavor preferences are evenly distributed, the claim distribution is a good fit for the observed data.