Buch, Englisch, 168 Seiten, Format (B × H): 139 mm x 216 mm, Gewicht: 198 g
Buch, Englisch, 168 Seiten, Format (B × H): 139 mm x 216 mm, Gewicht: 198 g
ISBN: 978-1-4129-1314-0
Verlag: SAGE Publications, Inc
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.
Features and Benefits:
- Covers basic statistics in an accessible fashion without emphasizing computation
- Covers the field more broadly than any other text like it
- Is ideal for readers who do not consider themselves good at math, have little interest in computing statistics, or just want to understand them
- Each concept is presented via impressions from a verse, an illustration, and 300 to 900 words of text.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
Weitere Infos & Material
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