This preview shows pages 1–3. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: 8 of 13 1.3 Testing a claim when is unknown 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 One Sample tTest, alpha=0.05, Two Tailed (NOTE: CLT must apply.) h Power n = 1000 n = 250 n = 100 n = 50 n = 30 n = 20 n = 10 n = 5 sig . l e v e l = 0.01 power = 0.8 alternative = one . sided Thus, required sample size is n = 19. Since our original sample only used n = 10, our power was much less than 0.8. OC CURVES FOR TTEST Operating Characteristic Curves. Definition 1.3 OC curves for various hypothesis tests provide a simple method for quickly estimating the required sample size (adhoc) necessary to achieve a desired power for a given hypothesis test. They are also used to estimate the actual Type II error (poshoc) once a study has been conducted. Now we will repeat our previous example using OC curves. Anthony Tanbakuchi MAT167 Testing a claim about a population mean 9 of 13 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 One Sample tTest, alpha=0.01, Two Tailed (NOTE: CLT must apply.) h Power n = 1000 n = 250 n = 100 n = 50 n =...
View
Full
Document
 Spring '11
 Tanbakuchi
 Statistics

Click to edit the document details