Rowan University Library owns many electronic resources to assist with understanding statistical concepts. All the resources are available to Rowan students, staff and faculty.

- Statistics in Plain English by Timothy C. UrdanCall Number: Available onlineISBN: 0805852417Publication Date: 2005-02-22Chapter 1: Introduction to Social Science Research Principles and Terminology

Chapter 2: Measures of Central Tendency

Chapter 3: Measures of Variability

Chapter 4: The Normal Distribution

Chapter 5: Standardization and z Scores

Chapter 6: Standard Errors

Chapter 7: Statistical Significance, Effect Size, and Confidence Intervals

Chapter 8: Correlation

Chapter 9: t Tests

Chapter 10: One-way Analysis of Variance

Chapter 11: Factorial Analysis of Variance

Chapter 12: Repeated-Measures Analysis of Variance

Chapter 13: Regression

Chapter 14: The Chi-Square Test of Independence

This book presents statistical concepts and techniques in simple, everyday language to help readers gain a better understanding of how they work and how to interpret them correctly. Each self-contained chapter features a description of the statistic including how it is used and the information it provides, how to calculate the formula, the strengths and weaknesses of each technique, the conditions needed for its use, and an example that uses and interprets the statistic. - The Tao of Statistics by Dana K. KellerISBN: 9781483377926Publication Date: 2015-03-19Chapter 1: The Beginning The Question

Chapter 2: Ambiguity Statistics

Chapter 3: Fodder-Data

Chapter 4: Data-Measurement

Chapter 5: Data Structure: levels of Measurement

5A: Nominal

5B: Ordinal

5C: Interval

5D: Ratio

Chapter 6: Simpliying Groups and Clusters

Chapter 7: Counts and Frequencies

Chapter 8: Pictures and Graphs

Chapter 9: Scatterings and Distributions

Chapter 10: Bell Shaped-The Normal Curve

Chapter 11: Lopsidenesses-Skewness

Chapter 12: Averages-Central Tendencies

12A: Mean

12B: Median

12C: Mode

Chapter 13: Two Types-Distributive and Inferential

Chapter 14: Foundations-Assumptions

Chapter 15: Murkiness-Missing Data

Chapter 16: Leeway-Robustness

Chapter 17: Consistency-Reliability

Chapter 18: Truth-Validity

Chapter 19: Unpredictability-Randomness

Chapter 20: Representativeness-Samples

Chapter 21: Mistakes-Errors

Chapter 22: Real or Not-Outliers

Chapter 23: Impediments-Confounds

Chapter 24: Nuisances-Covariates

Chapter 25: Background-Independent Variables

Chapter 26: Targets-Dependent Variables

Chapter 27: Inequality-Standard Deviations and Variance

Chapter 28: Prove-No, Falsify

Chapter 29: The Difference-The Null Hypothesis

Chapter 30: Reductionism-Models

Chapter 31: Risk-Probability

Chapter 32: Uncertainty-p values

Chapter 33: Expectations-Chi Square

Chapter 34: Importance vs. Difference—Substantive vs. Statistical

Chapter 35: Strength-Power

Chapter 36: Impact-Effect Sizes

Chapter 37: Likely Range—Confidence Intervals

Chapter 38: Association-Correlation

Chapter 39: Predictions-Multiple Regressions

Chapter 40: Abundance—Multivariate Analysis

Chapter 41: Differences—t Tests and Analysis of Variance

41A: ANOVA

41B: ANCOVA

41C: MANOVA

41D: MANCOVA

Chapter 42: Differences That Matter—Discriminant Analysis

Chapter 43: Both Sides Loaded—Canonical Covariance Analysis

Chapter 44: Nesting—Hierarchical Models

Chapter 45: Cohesion—Factor Analysis

Chapter 46: Ordered Events—Path Analysis

Chapter 47: Digging Deeper—Structural Equation Models

Chapter 48: Abundance-Big Data

Chapter 49: Scarcity-Small Data

Chapter 50: Fiddling—Modifications and New Techniques

This Second Edition of The Tao of Statistics: A Path to Understanding (With No Math) provides a reader-friendly approach to statistics in plain English. Unlike other statistics books, 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. The Second Edition adds coverage of big data to better address its impact on p-values and other key concepts; material on small data to show readers how to handle data with fewer data points than optimal; and other new topics like missing data and effect sizes. The book's two characters (a high school principal and a director of public health) return in the revised edition, with their examples expanded and updated with reference to contemporary concerns in the fields of education and health. - Using Statistics by Gordon RuggCall Number: Available onlineISBN: 1281331031Publication Date: 2010-01-10Chapter 1 Some introductory concepts;

Chapter 2 Measurement theory;

Chapter 3 Descriptive statistics;

Chapter 4 Patterns in data and presentation of data;

Chapter 5 'None of the above': the role of knowledge representation;

Chapter 6 The sixfold paths: some observations on probability theory;

Chapter 7 Inferential statistics: some introductory thoughts;

Chapter 8 Non-parametric statistics;

Chapter 9 Correlations;

Chapter 10 Parametric statistics;

Chapter 11 Multidimensional statistics

Chapter 12 Some general consideration

Written in an informal style, this book guides the reader gently through the field from the simplest descriptive statistics to multidimensional approaches. It's written in an accessible way, with few calculations and fewer equations, for readers from a broad set of academic disciplines ranging from archaeology to zoology. - The Cambridge Dictionary of Statistics by B. S. EverittCall Number: Available onlineISBN: 0521860393Publication Date: 2006-08-17If you use statistics and need easy access to simple, reliable definitions and explanations of modern statistical concepts, then look no further than this dictionary. Over 3600 terms are defined, covering medical, survey, theoretical, and applied statistics, including computational aspects.
- Statistics: a Very Short Introduction by David J. HandCall Number: Available onlineISBN: 9780199233564Publication Date: 2008-12-15Chapter 1: Surrounded by Statistics

Chapter 2: Simple Descriptions

Chapter 3: Collecting Good Data

Chapter 4: Probability

Chapter 5: Estimation and Inference

Chapter 6: Statistical Models and Methods

Chapter 7: Statistical Computing

Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them.

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