Biostatistical AnalysisPopulations and samples. Measures of central tendency. Measures of dispersion and variability. Testing of goodness of fit. Contingency tables. The normal distribuition. One-sample hypotheses. Two-sample hypotheses; Paired-sample hypotheses. Multisample hypotheses. Multisample hypotheses. The analysis of variance. Multiple comparasion. Two factor analysis of variance. Data transformations. Multiway factorial analysis of variance. Nested (hierarchial) analysis of variance. Simple linear regression. Comparing simple linear regression equations. Simple linear correlation. Polynomial regression. The binomial distribution. The posion distribution and randomness. Circular distributions. Descriptive statistics. Circula4 distribution. Hypotheses testing. |
From inside the book
Results 1-3 of 28
Page 43
... Type I error ( also called an α error , or an error of the first kind ) . On the other hand , if H , is in fact false , our test may occasionally not detect this fact , and we shall have reached an erroneous conclusion by not rejecting ...
... Type I error ( also called an α error , or an error of the first kind ) . On the other hand , if H , is in fact false , our test may occasionally not detect this fact , and we shall have reached an erroneous conclusion by not rejecting ...
Page 44
... Type I error are associated with higher probabilities of committing a Type II error , and the only way to reduce both types of error simultaneously is to increase n . Thus , for a given a , larger samples will result in statistical test ...
... Type I error are associated with higher probabilities of committing a Type II error , and the only way to reduce both types of error simultaneously is to increase n . Thus , for a given a , larger samples will result in statistical test ...
Page 188
... error DF for the analysis of variance ) , and k ( the total number of means being tested ) . The significance level , a , is the probability of encountering at least one Type I error ( i.e. , the probability of falsely rejecting at ...
... error DF for the analysis of variance ) , and k ( the total number of means being tested ) . The significance level , a , is the probability of encountering at least one Type I error ( i.e. , the probability of falsely rejecting at ...
Contents
Populations and Samples | 14 |
Measures of Dispersion and Variability | 27 |
Testing for Goodness of | 40 |
Copyright | |
36 other sections not shown
Common terms and phrases
analysis of variance ANOVA B₁ B₂ binomial distribution binomial test calculated cells Chapter chi-square coding computed confidence interval confidence limits contingency table correlation coefficient CRITICAL VALUES data of Example degrees of freedom demonstrated in Example determine difference employed equal estimate expected frequencies F DISTRIBUTION factor females H₁ hypothesis testing interaction males Mann-Whitney Mann-Whitney test mean angle mean square measure median Mmmmm multiple comparison multiple regression n₁ n₂ nonparametric normal approximation normal distribution null hypothesis number of data observed obtained P₁ P₂ parameter population means population regression probability procedure proportion R₁ random ranks ratio regression coefficients reject H replication residual sample statistics Section shown in Example species standard error sum of squares TABLE B.4 cont total number total SS transformation two-sample Type I error v₁ weight X₁ zero μ₁ μ₂ σ² ΣΧ