Across
- 1. 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
- 4. When the standard deviation of a statistic is estimated from data, the result is the standard error of the statistic
- 5. If the observed result is not very unlikely to occur when the null hypothesis is true, we should fail to reject H0 and say that we do not have convincing evidence for Ha
- 6. Fixed value α that we use as a cutoff for deciding whether an observed result is too unlikely to happen by chance alone when the null hypothesis is true. The significance level gives the probability of a Type I error
- 10. Occurs if we reject H0 when H0 is true
- 12. 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
- 13. When the Random, 10%, and Normal/Large Sample conditions are met, a C% confidence interval for μ is where t* is the critical value for the t distribution with df = n − 1, with C% of the area between −t* and t*
- 15. Statistic that provides an estimate of a population parameter
- 18. n-1
- 20. Specific value of a point estimator from a sample
Down
- 2. Gives an interval of plausible values for a parameter. The interval is calculated from the data and has the form point estimate ±margin of error or, alternatively, statistic ± (critical value) · (standard deviation of statistic)
- 3. 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 level
- 7. Claim we weight evidence against in a significance test. Often the null hypothesis is a statement of “no difference.”
- 8. The claim that we are trying to find evidence for in a significance test
- 9. The probability, computed assuming H0 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 Ha. The smaller the P-value, the stronger the evidence against H0 and in favor of Ha provided by the data
- 11. 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)
- 14. Procedure for using observed data to decide between two competing claims (also called hypotheses). The claims are often statements about a parameter
- 16. 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
- 17. Draw an SRS of size n from a large population that has a Normal distribution with mean μ and standard deviation σ. The statistic has the t distribution with degrees of freedom df = n − 1. This statistic will have approximately a tn−1 distribution if the sample size is large enough
- 19. Occurs if we fail to reject H0 when Ha is true