Society needs more from social sciences than they have delivered. One reason for falling short is that social science methods have depended excessively on regression and other statistical approaches, neglecting logical model building. Science is not only about the empirical “What is?” but also very much about the conceptual “How should it be on logical grounds?” Statistical approaches are essentially descriptive, while quantitatively formulated logical models are predictive in an explanatory way. This book contrasts the predominance of statistics in today's social sciences with predominance of ... More

Society needs more from social sciences than they have delivered. One reason for falling short is that social science methods have depended excessively on regression and other statistical approaches, neglecting logical model building. Science is not only about the empirical “What is?” but also very much about the conceptual “How should it be on logical grounds?” Statistical approaches are essentially descriptive, while quantitatively formulated logical models are predictive in an explanatory way. This book contrasts the predominance of statistics in today's social sciences with predominance of quantitatively predictive logical models in physics. It shows how to construct predictive models and gives social science examples. Only secondary school mathematics is often needed, plus willingness to simplify reality outrageously. The book also shows how to use and report basic statistical analysis in more informative ways, including emphasis on symmetric regression.