54 | | https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/find-sample-size/#CI1 |
55 | | https://stats.stackexchange.com/questions/207584/sample-size-choice-with-binary-outcome |
56 | | https://www.statisticshowto.datasciencecentral.com/z-alpha2-za2/ |
57 | | |
58 | | N (NZ pages where isMRI comes out true) = 4360 |
59 | | solving for n, the sample size |
60 | | confidence level = 90% |
61 | | m, margin of error = 5% |
62 | | |
63 | | From the "z alpha/2" table, for 90% confidence, we get a z alpha/2 value of 1.6449 (or 1.645). |
64 | | |
65 | | Then the sample size, n, we need is = 1.6449^2 * 4360 / ( 1.6449^2 + (4 * 4359) * 0.05^2) = 255 (rounded up) |
66 | | |
67 | | |
68 | | For N = 681, |
69 | | sample size n is = 1.6449^2 * 681 / ( 1.6449^2 + (4 * 680) * 0.05^2) = 194 (rounded up) |
70 | | |
71 | | |
72 | | sample size for NZ: 255 (90% confidence with 5% margine of error, Including a finite correction factor) |
73 | | sample size for US: 194 |
| 51 | https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/find-sample-size/#CI1 |
| 52 | https://stats.stackexchange.com/questions/207584/sample-size-choice-with-binary-outcome |
| 53 | https://www.statisticshowto.datasciencecentral.com/z-alpha2-za2/ |
| 54 | |
| 55 | N (NZ pages where isMRI comes out true) = 4360 |
| 56 | solving for n, the sample size |
| 57 | confidence level = 90% |
| 58 | m, margin of error = 5% |
| 59 | |
| 60 | From the "z alpha/2" table, for 90% confidence, we get a z alpha/2 value of 1.6449 (or 1.645). |
| 61 | |
| 62 | Then the sample size, n, we need is = 1.6449^2 * 4360 / ( 1.6449^2 + (4 * 4359) * 0.05^2) = 255 (rounded up) |
| 63 | |
| 64 | |
| 65 | For N = 681, |
| 66 | sample size n is = 1.6449^2 * 681 / ( 1.6449^2 + (4 * 680) * 0.05^2) = 194 (rounded up) |
| 67 | |
| 68 | |
| 69 | sample size for NZ: 255 (90% confidence with 5% margine of error, Including a finite correction factor) |
| 70 | sample size for US: 194 |