This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.

This textbook offers a step-by-step guide through comprehensive financial statement analysis with real-life case studies for students of financial accounting, financial reporting, and financial statement analysis. Structured into five comprehensive sections, it begins by explaining the content of accounting reports themselves and the three primary financial statements (income statement, balance sheet and cash flow statement). It deciphers the notes to financial statements and demonstrates some classical tools such as ratio analysis and multivariable credit risk models that are useful in a retrospective financial statement analysis. It includes simple step-by-step procedures of a prospective (i.e. future-oriented) financial statement simulation and closes with a comprehensive real-life case study that demonstrates a practical application of the analytical tools discussed earlier in the text. Additionally, the textbook includes online appendices consisting of additional comprehensive real-life case studies (of varying degrees of complexity and dealing with different aspects of a practical financial statement analysis), a set of MS Excel files that contain all major calculations included in tables and charts that appear in the core textbook, and a set of webinars in which the most fundamental parts of the core textbook are discussed in the form of the recorded lectures.

This book provides a digestible step-by-step guide to reading corporate financial reports, drawing upon real-life case studies and examples of corporate collapses and accounting scandals, and applying practical tools to financial statement analysis. Appealing to a range of practitioners within corporate finance including investors, managers, and business analysts, this book is the first to specifically address the challenges facing those who are not professional accountants and auditors when examining corporate financial reports. Corporate financial reports are used widely by managers, investors, creditors, and government agencies to examine company performance and evaluate potential risks. However, although seemingly an invaluable source of information for managerial decision-making, financial reports are often based on rough simplifications of a very complex reality. With no way of avoiding deliberate manipulations and fraudulent activity, these statements cannot be relied on completely when selecting stocks or evaluating credit risk, and therefore poor analysis can lead to potentially disastrous investment decisions. The author suggests that in order to effectively interpret corporate financial reports, we must 'read between the lines' to accurately assess a company's economic performance and predict its long-term viability.

This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.