1 / 8

Review of Inference

Review of Inference. Confidence Interval Estimates Tests of Hypotheses. Estimates of the mean, m. When s is known and X is normal or n > 30 Page 307 Problem 10.24 page 319 When s is unknown and X is normal or n > 30 Page 363 Problem 12.22 page 372. Estimates of the proportion, p.

diella
Télécharger la présentation

Review of Inference

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Review of Inference Confidence Interval Estimates Tests of Hypotheses

  2. Estimates of the mean, m • When s is known and X is normal or n>30 • Page 307 • Problem 10.24 page 319 • When s is unknown and X is normal or n > 30 • Page 363 • Problem 12.22 page 372

  3. Estimates of the proportion, p • When nphat > 5 and n(1-phat) > 5 • Page 383 • Problem 12.65 page 391 • How many people have common sense? • n=1000 Phat = .07

  4. Interpreting confidence intervals • XX % Confidence intervals e.g. 95% • XX % of all randomly selected samples yield an interval that contains m (or p). Thus, the probability is .xx that this interval contains m (or p). • Tradeoffs • Sample size – Confidence - Precision

  5. Tests of hypotheses about m • When s is known and X is normal or n > 30 • Problem 11.28 page 345; 11.37 page 346 • When s is unknown and X is normal or n > 30 • Problem 12.27 page 373; 12.33 page 374

  6. Tests of hypotheses about p • When nphat> 5 and n(1-phat) > 5 • Problem12.66 page 391

  7. Interpreting tests of hypotheses • Reject H0 • Correct decision or Type I error • Probability of Type I error = p-value < a • Type I error is rejecting a true H0 • Fail torejectH0 • Correct decision or Type II error • Probability of Type II error is unknown • Probability of Type II error and a inversely related • Type II error is failing to reject a false H0

  8. Interpreting p-values • P-value < a • Convincing evidence, sufficient to conclude H1 • a < p-value < .50 • Insufficient evidence to conclude H1 at the stated significance level, a • However, data are consistent with H1 • .50 < p-value • No evidence for H1 • Data are consistent with H0

More Related