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The Tao of Statistics: A Path to Understanding (With No Math) / Edition 1
     

The Tao of Statistics: A Path to Understanding (With No Math) / Edition 1

by Dana K. Keller
 

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ISBN-10: 1412913144

ISBN-13: 9781412913140

Pub. Date: 08/28/2005

Publisher: SAGE Publications

The Tao of Statistics: A Path to Understanding (With No Math) provides a new approach to statistics in plain English. Unlike other introductions to statistics, this text explains what statistics mean and how they are used, rather than how to calculate them. The book walks readers through basic concepts, as well as some of the most complex statistical models in

Overview

The Tao of Statistics: A Path to Understanding (With No Math) provides a new approach to statistics in plain English. Unlike other introductions to statistics, this text explains what statistics mean and how they are used, rather than how to calculate them. The book walks readers through basic concepts, as well as some of the most complex statistical models in use. Professionals and college students who want to be informed about statistics but do not want to spend a lot of time learning to how compute them should not be without this volume.

Product Details

ISBN-13:
9781412913140
Publisher:
SAGE Publications
Publication date:
08/28/2005
Edition description:
Older Edition
Pages:
168
Product dimensions:
5.50(w) x 8.50(h) x (d)

Related Subjects

Table of Contents

Introduction The Beginning-The Question Ambiguity-Statistics Fodder-Data Data-Measurement Data Structure-Levels of Measurement Nominal Ordinal Interval Ratio Simplifying-Groups & Clusters Counts-Frequencies Pictures-Graphs Scatterings-Distributions Bell Shaped-The Normal Curve Lopsidedness-Skewness Averages-Central Tendencies Mean Median Mode Two Types-Descriptive & Inferential Foundations-Assumptions Wiggle-Room-Robustness Consistency-Reliability Truth-Validity Unpredictable-Random Precision-Sampling Mistakes-Error Real or Not-Outliers Impediments-Confounds Nuisances-Covariates Background-Independent Variables Targets-Dependent Variables Inequality-Standard Deviations & Variance Prove-No, Falsify No Difference-The Null Hypothesis Reductionism-Models Risk-Probability Uncertainty-p Values Expectations-Chi-Square Importance vs. Difference-Substantive vs. Statistical Difference Strength-Power Likely Range-Confidence Intervals Association-Correlation Predictions-Multiple Regression Abundance-Multivariate Analyses Differences-t Tests & Analysis of Variance ANOVA ANCOVA MANOVA MANCOVA Differences That Matter-Discriminant Analyses Both Sides Loaded-Canonical Covariance Analysis Nesting-Hierarchical Models Cohesion-Factor Analysis Ordered Events-Path Analysis Digging Deeper-Structural Equation Models Fiddling-Modifications & New Techniques Epilogue

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