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 12
... equal . All we can infer from the ordinal scale is that one object ranks above another with respect to the given ... equal differences between ordinal values do not necessarily nor logically have equal quantitative meaning . They could ...
... equal . All we can infer from the ordinal scale is that one object ranks above another with respect to the given ... equal differences between ordinal values do not necessarily nor logically have equal quantitative meaning . They could ...
Page 40
... equal to the original mean times the constant value . In symbols , Max CMx CX = • Dividing a constant value c into each of a set of scores x results in a mean which is equal to the original mean divided by the constant value . In ...
... equal to the original mean times the constant value . In symbols , Max CMx CX = • Dividing a constant value c into each of a set of scores x results in a mean which is equal to the original mean divided by the constant value . In ...
Page 82
... equal chance of being drawn . Since , in the case of random sampling , every possible sample of a given size that can be drawn from the population has an equal chance of being our selected sample , we will be able to make inferences ...
... equal chance of being drawn . Since , in the case of random sampling , every possible sample of a given size that can be drawn from the population has an equal chance of being our selected sample , we will be able to make inferences ...
Contents
FUNDAMENTAL CONCEPTS 1 Introduction | 1 |
Objects variables and scales | 8 |
Frequency distributions | 21 |
Copyright | |
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Common terms and phrases
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