Michael Smithson is a Professor in the Research School of Psychology at The Australian National University in Canberra, and received his PhD from the University of Oregon. He is the author of Confidence Intervals (2003), Statistics with Confidence (2000), Ignorance and Uncertainty (1989), and Fuzzy Set Analysis for the Behavioral and Social Sciences (1987), co-author of Fuzzy Set Theory: Applications in the Social Sciences (2006) and Generalized Linear Models for Categorical and Limited Dependent Variables (2014), and co-editor of Uncertainty and Risk: Multidisciplinary Perspectives (2008) and Resolving Social Dilemmas: Dynamic, Structural, and Intergroup Aspects (1999). His other publications include more than 170 refereed journal articles and book chapters. His primary research interests are in judgment and decision making under ignorance and uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences.

A good coverage of key statistical concepts that are necessary for undergraduate psychology student. This is written with a refreshing emphasis on the necessity of the ′new statistics′ something that is not covered in many introductory statistical textbooks in more than a cursory way. This is a wonderful book for anyone wishing to approach the fundamentals of statistical techniques while providing themselves a solid grounding in confidence intervals and their benefits.

• Uncertainty and Psychological ResearchVariables and MeasurementExploring, Describing, Displaying and SummarizingResearch Design and ProbabilitySampling Distributions and Confidence IntervalsStatistical Models and Significance TestsPredicting a Quantitative Variable from a Categorical VariableThe t Test and Analysis of VarianceQuantitative PredictorsRegression and CorrelationPredicting Categorical VariablesContingency Tables and Chi-SquareMore Than Two VariablesA Peek at Multivariate AnalysisPutting Statistics into Perspective

Michael Smithson is a Professor in the Research School of Psychology at The Australian National University in Canberra, and received his PhD from the University of Oregon. He is the author of Confidence Intervals (2003), Statistics with Confidence (2000), Ignorance and Uncertainty (1989), and Fuzzy Set Analysis for the Behavioral and Social Sciences (1987), co-author of Fuzzy Set Theory: Applications in the Social Sciences (2006) and Generalized Linear Models for Categorical and Limited Dependent Variables (2014), and co-editor of Uncertainty and Risk: Multidisciplinary Perspectives (2008) and Resolving Social Dilemmas: Dynamic, Structural, and Intergroup Aspects (1999). His other publications include more than 170 refereed journal articles and book chapters. His primary research interests are in judgment and decision making under ignorance and uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences.

A good coverage of key statistical concepts that are necessary for undergraduate psychology student. This is written with a refreshing emphasis on the necessity of the ′new statistics′ something that is not covered in many introductory statistical textbooks in more than a cursory way. This is a wonderful book for anyone wishing to approach the fundamentals of statistical techniques while providing themselves a solid grounding in confidence intervals and their benefits.

• Uncertainty and Psychological ResearchVariables and MeasurementExploring, Describing, Displaying and SummarizingResearch Design and ProbabilitySampling Distributions and Confidence IntervalsStatistical Models and Significance TestsPredicting a Quantitative Variable from a Categorical VariableThe t Test and Analysis of VarianceQuantitative PredictorsRegression and CorrelationPredicting Categorical VariablesContingency Tables and Chi-SquareMore Than Two VariablesA Peek at Multivariate AnalysisPutting Statistics into Perspective

Michael Smithson is a Professor in the Research School of Psychology at The Australian National University in Canberra, and received his PhD from the University of Oregon. He is the author of Confidence Intervals (2003), Statistics with Confidence (2000), Ignorance and Uncertainty (1989), and Fuzzy Set Analysis for the Behavioral and Social Sciences (1987), co-author of Fuzzy Set Theory: Applications in the Social Sciences (2006) and Generalized Linear Models for Categorical and Limited Dependent Variables (2014), and co-editor of Uncertainty and Risk: Multidisciplinary Perspectives (2008) and Resolving Social Dilemmas: Dynamic, Structural, and Intergroup Aspects (1999). His other publications include more than 170 refereed journal articles and book chapters. His primary research interests are in judgment and decision making under ignorance and uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences.

A good coverage of key statistical concepts that are necessary for undergraduate psychology student. This is written with a refreshing emphasis on the necessity of the ′new statistics′ something that is not covered in many introductory statistical textbooks in more than a cursory way. This is a wonderful book for anyone wishing to approach the fundamentals of statistical techniques while providing themselves a solid grounding in confidence intervals and their benefits.

• Uncertainty and Psychological ResearchVariables and MeasurementExploring, Describing, Displaying and SummarizingResearch Design and ProbabilitySampling Distributions and Confidence IntervalsStatistical Models and Significance TestsPredicting a Quantitative Variable from a Categorical VariableThe t Test and Analysis of VarianceQuantitative PredictorsRegression and CorrelationPredicting Categorical VariablesContingency Tables and Chi-SquareMore Than Two VariablesA Peek at Multivariate AnalysisPutting Statistics into Perspective