## Statistical Analysis: An Interdisciplinary Introduction to Univariate & Multivariate MethodsThis 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. |

### Contents

THE NATURE OF STATISTICAL ANALYSIS 1 Introduction | 3 |

Data | 4 |

Objectives of statistical analysis | 5 |

Copyright | |

213 other sections not shown

### Common terms and phrases

alternative analysis analysis of variance application approach assigned associated average blocks calculate chapter characteristics cluster consider contrasts correlation coefficient criterion variable degrees of freedom depending determine difference discriminant effects equal equation error estimate example expected experiment experimental fact factor Figure frequency function given groups hypothesis identify importance independent individual interested interpretation interval less loading mean measure multiple namely nature normal objects observations obtained outcomes package paired parameter performance population possible preceding prediction predictor variables presented probability problem procedure proportion random ratio referred reject relationship relative represent respective resulting sample mean sampling distribution scale scores shown significance level simple situation space squared standard deviation standard error statistical successes Table technique treatment true variance variation various weights