_Learning Statistics: A Manual for Sociology Students_ helps students learn and retain important statistical concepts. New graduates face numerous challenges when applying statistics in the workplace. This text presents a unique and class-tested set of pedagogical tools that increase learning and retention, and prepare students for real-world application. In the real world decisions are often made in conditions of uncertainty. Decision makers examine data generated through scientific sampling, which is a cost-effective means of generating information. This book addresses the selection, use, and interpretation of statistical tools, in conjunction with the presentation of effective results aimed at supporting practical decision-making. In essence, the book is based on the idea that you learn statistics by doing statistics. The approach of _Learning Statistics_ is three-fold. It is computer-based. It assumes that problems are client-driven and create conditions of uncertainty. It is designed with a conceptual umbrella over empirical assignments. Students will achieve key learning outcomes including: * Grasping the conceptual foundation that underlies inferential statistics; * Understanding basic descriptive and inferential tools within a decision-making framework; * Selecting appropriate statistical tools, such as graphing, correlation, and simple regression, for specific tasks; * Using software packages to support data analysis. This comprehensive text addresses major concepts in classical statistics. It serves as a bridge between the classroom and the office.