Multivariate Statistical Analysis: A Conceptual IntroductionThis classic book provides the much needed conceptual explanations of advanced computer-based multivariate data analysis techniques: correlation and regression analysis, factor analysis, discrimination analysis, cluster analysis, multi-dimensional scaling, perceptual mapping, and more. It closes the gap between spiraling technology and its intelligent application, fulfilling the potential of both. |
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Page 23
... Relative frequencies . It is often helpful to convert the frequencies of a frequency distribution into relative frequencies , which are nothing more than the observed frequencies converted into percentages based on the total number of ...
... Relative frequencies . It is often helpful to convert the frequencies of a frequency distribution into relative frequencies , which are nothing more than the observed frequencies converted into percentages based on the total number of ...
Page 24
... relative frequencies . Once we have formed a cumulative frequency distribution , it is a simple matter to convert it into a cumulative relative frequency distribution . All we need to do is divide each cumulative frequency by the total ...
... relative frequencies . Once we have formed a cumulative frequency distribution , it is a simple matter to convert it into a cumulative relative frequency distribution . All we need to do is divide each cumulative frequency by the total ...
Page 65
... relative frequency of occurrence of an event in the long run . In this respect , a relative frequency distribution can be viewed as an estimate of the underlying theoretical probability distribution . Table la shows the assignment of ...
... relative frequency of occurrence of an event in the long run . In this respect , a relative frequency distribution can be viewed as an estimate of the underlying theoretical probability distribution . Table la shows the assignment of ...
Contents
FUNDAMENTAL CONCEPTS 1 Introduction | 1 |
Objects variables and scales | 8 |
Frequency distributions | 21 |
Copyright | |
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alternative application approach associated average calculate chapter characteristics cluster color concept consider correlation coefficient criterion variable defined degrees of freedom depending derived determine dimensions discriminant discriminant function discussion distance distribution effects equal equation error estimate example experiment experimental fact factor analysis Figure frequency given groups hypothesis identify important independent individual input instance inter-object interest interpretation interval less levels loading matrix mean measured median multiple named nature objects observations obtained occur original outcomes package pair particular performance population possible prediction predictor variables present probability problem procedure random ratio referred regression analysis relationship relative represent respective sample mean sampling distribution scale scores shape shown shows similarity simple situations space square standard deviation statistical Table technique true understand values variance variation various weights