Chapter 8 and 9 Vocabulary

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Across
  1. 3. The claim about the population that we are trying to find evidence for.
  2. 9. Multiplier that makes the interval wide enough to have the stated capture rate. The critical value depends on both the confidence level C and the sampling distribution of the statistic.
  3. 10. Measures how far sample statistic diverges from what we would expect if the null hypothesis were true, in standardized units.
  4. 11. An interval of plausible values for a parameter value.
  5. 13. The standard deviation of a statistic is estimated from data.
  6. 15. It states that the parameter is different from the null hypothesis value.
  7. 17. We reject H(not) when H(not) is true.
  8. 18. We fail to reject H(not) when H(a) is true.
  9. 19. The claim we weigh evidence against in a statistical test.
  10. 20. The difference between the point estimate and the true parameter value will be less than the margin of error.
Down
  1. 1. T interval for a mean when the random 10% and normal/large sample conditions are met, a C% confidence interval for __ is where t is the critical value for the t distribution with df=n-1, with C% of the area between -t and t.
  2. 2. The power of a test against a specific alternative is the probability that the test will reject H(not) at a chosen significance level __ when the specified alternative value of the parameter is true.
  3. 4. It states that a parameter is larger than the null hypothesis value or it states that the parameter is smaller than the null value.
  4. 5. It describes how far X(bar) will typically be from _ in repeated SRSs of size N.
  5. 6. The probability, computed assuming H(not) is true, that the statistic would take a value as extreme as or more extreme than the one actually observed, in the direction specified by H(a).
  6. 7. We reject the null hypothesis and conclude that there is convincing evidence in favor of the alternative hypothesis.
  7. 8. A statistic that provides an estimate of a population parameter.
  8. 12. Draw an SRS of size N from a large population that has a normal distribution with mean_ and standard deviation _ the statistic has the T distribution with degrees of freedom df=n-1. The statistic will have approximately a t(n-1) distribution if the sample size is large enough.
  9. 14. Success rate of the method for calculating the confidence interval. In C% of all possible samples, the method would yield an interval that captures the true parameter value.
  10. 16. The value of that statistic from a sample.