DESCRIPTIVE AND INFERENTIAL STATISTICS
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Descriptive and Inferential Statistics: Problems and solutions is a handbook that condenses years of teaching experience in undergraduate and graduate statistics courses, offering a clear and structured approach for students, professionals, and academics. Each chapter provides a precise introduction to a statistical method, followed by step-by-step explanations that facilitate not only theoretical understanding but also practical application through solved exercises. The book stands out for adapting exercises to real-world cases in fields such as Business Administration, Marketing, and Digital...
Descriptive and Inferential Statistics: Problems and solutions is a handbook that condenses years of teaching experience in undergraduate and graduate statistics courses, offering a clear and structured approach for students, professionals, and academics. Each chapter provides a precise introduction to a statistical method, followed by step-by-step explanations that facilitate not only theoretical understanding but also practical application through solved exercises. The book stands out for adapting exercises to real-world cases in fields such as Business Administration, Marketing, and Digital Business, making it an essential tool for those aiming to make data-driven decisions. The proposed exercises, along with their detailed solutions, allow readers to evaluate and consolidate their knowledge independently. Designed both for self-study and as a complement to formal instruction, this manual covers fundamental and advanced concepts, from data organization and measures of central tendency to inferential analysis and the application of statistical models. The pedagogical clarity of the text ensures an effective and accessible learning experience, even for those without a strong background in statistics. This book is the ideal companion for those seeking to master statistical tools that are essential for making informed decisions in business and digital environments. Índice: Introduction to Descriptive Statistics.- Measures of Central Tendency.- Concentration Measures: Lorenz Curve and Gini Index.- Measures of Dispersion: Variance and Standard Deviation.- Index Numbers.- Two-Dimensional Statistical Analysis.- Regression Analysis.- Probability.- Random Variables.- Normal Distribution.- Sampling.- Hypothesis Testing.- Standard Normal Distribution Table.
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