Quantitative methods an introduction for business management ebook

Start your free trial. Book description An accessible introduction to the essential quantitative methods for making valuable business decisions Quantitative methods-research techniques used to analyze quantitative data-enable professionals to organize and understand numbers and, in turn, to make good decisions. Show and hide more. Table of contents Product information. Blitzstein, Jessica Hwang Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding ….

Get it now. In Chapter 1 we have seen that this is needed, for instance, to figure out the best mix of products. Building a relationship linking managerial levers and the resulting outcome is essential in tackling any decision problem. In other cases, our aim is somewhat more instrumental. In statistical model building, we want to find a mathematical representation that yields the best fit between the empirically observed data and the predictions of the model.

Author : Richard E. Trueman Publisher: N. This title includes chapters that focus on a selection of statistical techniques, illustrated with examples from across business, marketing, economics, finance, and public administration, that may appeal to students across the business spectrum.

This applications-oriented text clearly introduces current quantitative methods, how they work, and how savvy decision makers can most effectively apply and interpret data. A strong managerial orientation motivates learning by weaving relevant, real-world examples throughout. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, linear regression, and a discussion of time series that includes both classical topics and more challenging models.

The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics.

Finally, the book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis.

The book promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guide for financial and business professionals, as well as readers looking to reinforce their analytical skills.