Across
- 3. The claim about the population that we are trying to find evidence for.
- 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.
- 10. Measures how far sample statistic diverges from what we would expect if the null hypothesis were true, in standardized units.
- 11. An interval of plausible values for a parameter value.
- 13. The standard deviation of a statistic is estimated from data.
- 15. It states that the parameter is different from the null hypothesis value.
- 17. We reject H(not) when H(not) is true.
- 18. We fail to reject H(not) when H(a) is true.
- 19. The claim we weigh evidence against in a statistical test.
- 20. The difference between the point estimate and the true parameter value will be less than the margin of error.
Down
- 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. 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.
- 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.
- 5. It describes how far X(bar) will typically be from _ in repeated SRSs of size N.
- 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).
- 7. We reject the null hypothesis and conclude that there is convincing evidence in favor of the alternative hypothesis.
- 8. A statistic that provides an estimate of a population parameter.
- 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.
- 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.
- 16. The value of that statistic from a sample.