Basic & Clinical Biostatistics |
From inside the book
Results 1-3 of 75
Page 109
... limits is traditional , but other limits , such as 99 % and 90 % , can be employed as well . We will use 90 % for this example . - For the eight patients , there are 8 – 1 = 7 degrees of freedom ; and the value of t from Table A - 3 for ...
... limits is traditional , but other limits , such as 99 % and 90 % , can be employed as well . We will use 90 % for this example . - For the eight patients , there are 8 – 1 = 7 degrees of freedom ; and the value of t from Table A - 3 for ...
Page 114
... limits . confidence interval must be determined or a per- formed before we can say whether the means are dif- ferent ... limits are or 00 ( 2.131 ) ( 429 ± ( 2.131 ) 294.7 √16 272.0 and 586.0 mg / 24 h ) For subjects without carcinoid ...
... limits . confidence interval must be determined or a per- formed before we can say whether the means are dif- ferent ... limits are or 00 ( 2.131 ) ( 429 ± ( 2.131 ) 294.7 √16 272.0 and 586.0 mg / 24 h ) For subjects without carcinoid ...
Page 319
... limits of 99 and 101 . c . 95 % confidence limits are 101 + ( 1.96 ) ( 3 / √36 ) = 101 ± 0.98 , or 100.02 and 101.98 . d 95 % confidence limits for n = 144 are 101 ± ( 1.96 ) ( 3 / √144 ) = 101 ± 0.49 , or 100.51 and 101.49 . The ...
... limits of 99 and 101 . c . 95 % confidence limits are 101 + ( 1.96 ) ( 3 / √36 ) = 101 ± 0.98 , or 100.02 and 101.98 . d 95 % confidence limits for n = 144 are 101 ± ( 1.96 ) ( 3 / √144 ) = 101 ± 0.49 , or 100.51 and 101.49 . The ...
Contents
Preface | 1 |
Dividing the reference section at the end of the book into five categories to facilitate your | 4 |
OBJECTIVE | 15 |
Copyright | |
17 other sections not shown
Other editions - View all
Common terms and phrases
actual analysis appropriate authors blood calculated called cancer Chapter characteristics cholesterol clinical coefficient column compared comparisons conclusion confidence intervals correlation decision described determine developed difference discussed disease distribution divided effect equal error estimate evaluate examine example expected factors Figure formula frequency given gives graphs greater hypothesis illustrate important included increase independent indicates interest involves less levels limits mean measure methods months myocardial infarction needed negative nominal normal distribution null observations obtain occur outcome patients percentage perform permission physicians plot population positive possible predict Presenting Problem pressure probability procedure proportion questions random ratio regression rejection relationship reported risk sample scale scores selected sensitivity significant specific square standard deviation statistical Step subjects Table term tion treatment trials variables weight women zero