1 / 19

Formula for a Specific Confidence Interval For a Proportion

Formula for a Specific Confidence Interval For a Proportion. √. √. ^. ^. ^. ^. ( ). ( ). p · q n. p · q n. ^. ^. p – z α /2 < p < p + z α /2. Hint: Put the entire fraction in parentheses. ^. ^. ( ). p · q n. ^.

bary
Télécharger la présentation

Formula for a Specific Confidence Interval For a Proportion

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. Formula for a Specific Confidence Interval For a Proportion √ √ ^ ^ ^ ^ ( ) ( ) p · q n p · q n ^ ^ p – zα/2 < p < p + zα/2 Hint: Put the entire fraction in parentheses ^ ^ ( ) p · q n ^ You’re using p-values which are rounded to 3 decimals, so your answer should be rounded to 3 decimals

  2. (Set up each formula and round to THREE DECIMAL PLACES!!) Example 3: A Today Poll of 1015 adults found that 132 approved of the Job Congress was doing in 1995. Find the 95% confidence interval of the true proportion of adults who felt this way. ^ 132 1015 ^ C.I. = n = p = = .13 q = 95% zα/2 = 1015 0.87 1.96 √ √ ^ ^ ^ ^ ( ) ( ) p · q n p · q n ^ ^ p – zα/2 < p < p + zα/2 √ √ ( ) ( ) .13 · .87 1015 .13 · .87 1015 .13 – 1.96 < p < .13 + 1.96 .13 – 0.021 < p < .13 + 0.021 .109 < p < .151

  3. Formula for the Minimum Sample Size Needed For an interval estimate of population proportion 2 ( ) zα/2 E ^ ^ n = p ∙ q Where E is the maximum error of estimate. ALWAYS ROUND UP TO THE NEXT WHOLE NUMBER

  4. Example 5: An educator desires to estimate, within 0.03, the true proportion of high school students who study at least one hour each school night. He wants to be 98% confident. How large a sample is necessary?A) A previous study showed that 60% surveyed spent at least one hour each school night studying. ^ ^ .6 q = p = .4 E = 0.03 C.I. = 98% zα/2 = 2.33 2 2 ( ) ( ) zα/2 E 2.33 0.03 ^^ n = p ∙ q = .6 ∙ .4 = 1447.71 = 1448  ROUND UP!!

  5. Example 5: An educator desires to estimate, within 0.03, the true proportion of high school students who study at least one hour each school night. He wants to be 98% confident. How large a sample is necessary?B) If no estimate of the sample proportion is available, how large should the sample be? ^ ^ .5 q = p = .5 E = 0.03 C.I. = 98% zα/2 = 2.33 2 2 ( ) ( ) zα/2 E 2.33 0.03 ^^ n = p ∙ q = .6 ∙ .4 = 1508.03 = 1509  ROUND UP!!

  6. p 350 – 351 # 4 – 14 even (omit 6), 15, 16, 19, 20

  7. ^ ^ 1. a) p = .5 q = .5 ^ ^ b) p = .45 q = .55 ^ ^ c) p = .462 q = .538 ^ ^ d) p = .583 q = .417 ^ ^ e) p = .453 q = .547

  8. ^ ^ 2. a) p = .12 q = .88 ^ ^ b) p = .29 q = .71 ^ ^ c) p = .65 q = .35 ^ ^ d) p = .53 q = .47 ^ ^ e) p = .67 q = .33

  9. 4. √ √ ( ) ( ) .27 · .73 100 .27 · .73 100 .27– 1.65 < p < .27+ 1.65 .27 – 0.073 < p < .27 + 0.073 .197 < p < .343

  10. 8. √ √ .431 · .569 763 .431 · .569 763 .431– 1.75 < p <.431+ 1.75 .431 – 0.031 < p < .431 + 0.031 .400 < p < .462

  11. 10. √ √ .575 · .425 80 .575 · .425 80 .575– 1.96 < p <.575+ 1.96 .575 – 0.108 < p < .575 + 0.108 .467 < p < .683

  12. 12. √ √ .45 · .55 500 .45 · .55 500 .45– 1.65 < p < .45+ 1.65 .45 – 0.037 < p < .45 + 0.037 .413 < p < .487

  13. 14. √ √ .56 · .44 1000 .56 · .44 1000 .56– 1.96 < p < .56+ 1.96 .56 – 0.031 < p < .56 + 0.031 .529 < p < .591

  14. 15a. 2 ( ) 2.58 .02 n = .25 · .75 n = 3120.188  3121

  15. 15b. 2 ( ) 2.58 .02 n = .5 · .5 n = 4160.25  4161

  16. 16a. 2 ( ) 1.65 .05 n = .29· .71 n = 224.225  225

  17. 16b. 2 ( ) 1.65 .05 n = .5· .5 n = 272.25  273

  18. 19. 2 ( ) 1.96 .03 n = .5· .5 n = 1067.111  1068

  19. 20. 2 ( ) 1.96 .02 n = .27· .73 n = 1892.948  1893

More Related