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Basic Business Statistics: Concepts and applications, 5th EditionНазвание: Basic Business Statistics: Concepts and applications, 5th Edition
Автор: Berenson M.L., Levine D.M., Szabat K.A.
Издательство: Pearson
Год: 2019
Страниц: 889
Язык: английский
Формат: pdf (true)
Размер: 37.6 MB

Extending the teaching foundation of the previous editions, Basic Business Statistics uses a real-world focus. This allows students to visualise how the content can be applied to people and businesses in reality, helping take them look beyond concepts to visualise the theory in a tangible framework. Using language that is more accessible--but no less authoritative--students can spend more time learning the theories with local examples and a variety of features.

Academics are given the flexibility of designing an engaging unit for a mixed cohort of students with courseware that drives technical and soft skills through authentic learning tools and assignments for hybrid, online and face-to-face units.

Part 5 contains additional chapters: Chapter 16 on multiple regression and model building, Chapter 17 on decision making, Chapter 18 on statistical applications in quality and productivity management, Chapter 19 on further non-parametric tests and two brand new chapters: Chapter 20 on business analytics and Chapter 21 on data analysis. This chapter will be especially useful to students who wish to understand how the concepts and techniques studied in this book all fit together. The Part 5 chapters can be found within the MyLab and student download page via our catalogue.

We generally organise the collected data into Microsoft Excel workbooks. The main advantage of using this software is the ease of data analysis. Some powerful data analysis tools include data tables, What-If Analysis, Solver, charting and common statistical functions. Some shortcomings we have encountered using Excel is that data sometimes need to be rearranged depending on the analysis, [there can be] problems with inconsistent or missing data, and output can sometimes be incomplete. These factors increase the likelihood of errors in data analysis; however, for the purposes of corporate finance, Excel is generally sufficient as a means of summarising and analysing the data collected.

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