Multivariate Statistical Analysis: A Conceptual Introduction |
From inside the book
Results 1-3 of 45
Page 29
... occurs equally often . Interestingly , this type of distribution is not as common as one might think . More often data assumes an unequal distribution of occurrence ; i.e. , with certain values tending to occur more frequently than ...
... occurs equally often . Interestingly , this type of distribution is not as common as one might think . More often data assumes an unequal distribution of occurrence ; i.e. , with certain values tending to occur more frequently than ...
Page 62
... occur on both tosses . Also we could have a Tail occur on both tosses . And then we could have a Head and a Tail . But wait ! We defined our outcomes of interest specifically as being the ordered sequence of landings , therefore a ...
... occur on both tosses . Also we could have a Tail occur on both tosses . And then we could have a Head and a Tail . But wait ! We defined our outcomes of interest specifically as being the ordered sequence of landings , therefore a ...
Page 67
... occur if any one of the simple outcomes which comprise it occurs . Thus , in the die rolling experiment , the composite outcome " odd value ” will have occurred when any of the simple outcomes defining it - 1 , 3 , or 5 - occurs . The ...
... occur if any one of the simple outcomes which comprise it occurs . Thus , in the die rolling experiment , the composite outcome " odd value ” will have occurred when any of the simple outcomes defining it - 1 , 3 , or 5 - occurs . The ...
Contents
FUNDAMENTAL CONCEPTS 1 Introduction | 1 |
Objects variables and scales | 8 |
Frequency distributions | 21 |
Copyright | |
96 other sections not shown
Other editions - View all
Common terms and phrases
alternative analysis of variance application associated average calculated central tendency chapter cluster analysis composite outcomes concept confidence interval consider correlation analysis correlation coefficient criterion groups criterion variable cutoff score degrees of freedom determine dichotomous discriminant analysis discriminant function equal example experimental variable F ratio factor analysis factor loadings frequency distribution groups variance high loading hypothesis identify individual input variables inter-object similarity interaction interpretation loading on Factor measured median multiple correlation non-risks normal distribution number of observations number of variables occur package color pair population variance prediction random variables regression analysis regression equation regression line relationship represent respective rotation sample mean sample space sample statistics sampling distribution scale set of objects set of variables shelf space shown in Figure similarity matrix simple outcomes spice sales squared deviations standard deviation standard error statistical analysis Table technique test scores tion variance estimate variation