The text emphasises four themes to support evidence-based management decision making: 1. Setting the statistical landscape in a management context 2. Interpretative decision making based on patterns revealed by exploratory data analyses 3. Statistical decision making guided by the test-based findings of inferential analyses 4. Predictive decision making using statistical modelling evidence. The thread that links them is the role of data analytics as a management decision-support tool. This fifth edition builds on the strengths of the fourth edition by: - Highlighting newer trends in statistical applications in management practice - Strengthening the Excel-based generation of statistical evidence using a custom-built software product, called X-Static - Enhancing the graphic visualisation of statistical evidence. Target market: - Undergraduate students of Management at universities (BCom, BAcc, etc) - Management diploma students working towards professional qualifications at institutions such as the IMM, CSSA, CIMA, IAC, etc. - Postgraduate students (MBA and PGDip) of Management at business schools.

Relying on the existence, in a complete market, of a pricing kernel, this book covers the pricing of assets, derivatives, and bonds in a discrete time, complete markets framework. It is primarily aimed at advanced Masters and PhD students in finance. - Covers asset pricing in a single period model, deriving a simple complete market pricing model and using Stein's lemma to derive a version of the Capital Asset Pricing Model. - Looks more deeply into some of the utility determinants of the pricing kernel, investigating in particular the effect of non-marketable background risks on the shape of the pricing kernel. - Derives the prices of European-style contingent claims, in particular call options, in a one-period model; derives the Black-Scholes model assuming a lognormal distribution for the asset and a pricing kernel with constant elasticity, and emphasizes the idea of a risk-neutral valuation relationship between the price of a contingent claim on an asset and the underlying asset price. - Extends the analysis to contingent claims on assets with non-lognormal distributions and considers the pricing of claims when risk-neutral valuation relationships do not exist. - Expands the treatment of asset pricing to a multi-period economy, deriving prices in a rational expectations equilibrium. - Uses the rational expectations framework to analyse the pricing of forward and futures contracts on assets and derivatives. - Analyses the pricing of bonds given stochastic interest rates, and then uses this methodology to model the drift of forward rates, and as a special case the drift of the forward London Interbank Offer Rate in the LIBOR Market Model.

"Financial Accounting," 18th Edition, provides a solid foundation in business and accounting with the proven, student-focused presentation by award-winning authors Warren/Jones/Tayler. This edition covers the fundamentals of financial accounting from the perspective of a sole proprietor, while motivating students by showing how accounting is important to business. New content integrates coverage of AI and data analytics, while online appendices offer optional topics for your teaching flexibility. CNOWv2 offers an interactive learning experience that bridges the gap between content, homework and exam performance, allowing students to master essential accounting skills within the context of today's corporate business landscape. The text features updated, real-world examples, data analytics activities using Excel and Tableau and interactive online resources.

Written with the non-mathematician in mind, Camm/Cochran/Fry/Ohlmann's "Quantitative Methods for Business," 14th Edition, equips your students to understand the role that quantitative methods play in decision making. The text introduces how current quantitative methods work and how decision-makers can apply and interpret data. The Problem-Scenario Approach helps readers understand and apply mathematical concepts and techniques to solve business problems. Excel-based coverage incorporates Excel’s histogram charting the use of the XLOOKUP function. Clearer explanations have been added in response to reader feedback. The book features updated Q.M. in Action vignettes that showcase real world applications, homework problems, end-of-chapter cases and revisions to existing problems and cases.