University of Cebu-Banilad Library

Includes bibliographical references.

Contents: Preface — Introduction — Chapter 1 Basic concepts of statistics — Chapter 2 Data collection and quality — Chapter 3 Descriptive statistics — Chapter 4 Probability concepts — Chapter 5 Inferential statistics — Chapter 6 Regression analysis — Chapter 7 Time series analysis — Chapter 8 Non-parametric statistics — Chapter 9 Quality control and six sigma — Chapter 10 Business analytics and data mining — Bibliography.

"In today's data-driven business landscape, the ability to analyze and interpret vital discipline that empowers decision-makers with quantitative tools to make can gain insights that drive operational efficiencies, enhance customer satisfaction, choices. professionals and ultimately boost profitability.

fundamental concepts of statistics and their practical application in business This textbook serves as a comprehensive guide for understanding the settings. We begin with a foundational overview of key statistical concepts, defining important terms, and discussing the significance of statistics in effective decision-making.

Chapter 1 categorizes data into qualitative and quantitative types, explores measurement scales (nominal, ordinal, interval, and ratio), and distinguishes between descriptive and inferential statistics while clarifying the relationship between populations and samples. Chapter 2 emphasizes the significance of data collection methods in ensuring high-quality data, detailing techniques that enhance designing effective surveys. accuracy, completeness, consistency, and timeliness, as well as best practices for

Chapter 3 focuses on descriptive statistics, highlighting various types of

descriptive analysis and effective data visualization techniques for clear and impactful presentation. In Chapter 4, foundational probability concepts are introduced, covering essential principles, rules, and applications relevant to business statistics, including probability distributions, the Central Limit Theorem, and the Law of Large Numbers. Chapter 5 advances to inferential statistics, explaining estimation methods, hypothesis testing, and the critical roles of p-values and significance levels in validating decisions based on sample data.

Moving forward, Chapter 6 discusses regression analysis, including simple and multiple regression techniques, with an emphasis on interpreting outputs for business applications. Chapter 7 presents time séries analysis, examining its components (trend, seasonality, cyclic patterns, and irregular fluctuations) and forecasting techniques such as moving averages and exponential smoothing to aid strategic planning. Chapter 8 covers non-parametric statistics, differentiating between parametric and non-parametric tests and introducing common tests like the Chi-Square Test and the Mann-Whitney U Test for non-normally distributed data." —Preface

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