Chapter 8 and 9 Vocabulary

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Across
  1. 3. the data comes from a well- designed random sample or randomized experiment.
  2. 6. if we fail to reject H when H is true.
  3. 8. the claim that we are trying to find evidence for in a significance test.
  4. 9. the value of that statistic from a sample.
  5. 10. 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.
  6. 11. gives an interval of plausible values for a parameter.
  7. 14. both np and n(1-p) are at least 10.
  8. 16. the alternative hypothesis is two-sided if it states that the parameter is different from the null value (it could be either smaller or larger).
  9. 18. when the standard deviation of a statistic is estimated from data, the result is the standard error of the statistic.
  10. 19. the difference between the point estimate and the true parameter value will be less than the margin of error in C% of all samples, where C is the confidence interval.
  11. 20. 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.
Down
  1. 1. claim we weight evidence against in a significance test. Also known as a statement of "no difference".
  2. 2. procedure for using observed data to decide between two competing claims ( also called hypotheses). The claims are often statements about a parameter.
  3. 4. an alternative hypothesis that states that a parameter is larger than the null hypothesis value or that states that the parameter is smaller than the null value.
  4. 5. study designs that involve making two observations on the same individual or one observation on each of two similar individuals result in paired data.
  5. 7. df= n-1
  6. 12. measures how far a sample statistic diverges from what we would expect if the null hypothesis H were true, in standardized units.
  7. 13. a statistic that provides an estimate of a population parameter.
  8. 15. the probability that a test will reject H at a chosen significance level when a specified alternative value of the parameter is true.
  9. 17. if we reject H when H is true.