The Book Advanced Business Statistics Has Attempted To Achieve Two Objectives, That Is, To Make The Subject Matter Very Clear And Understandable To The Students And To Put The Collection Of Numerical Problems In A Systematic Manner At One Place. It Will Fully Meet The Needs Of The Students Of Various Examinations Like M.Com., D.C.M.A., I.C.W.A., C.A., M.B.A., Etc.
An accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more streamlined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae. The author—an expert in the field—offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are introduced through examples, and the text is designed to be accessible to readers with a variety of backgrounds. To enhance learning, most of the mathematical formulae and notation appears in technical appendices at the end of each chapter. This important resource: Offers a comprehensive guide to understanding business statistics targeting business and economics students and professionals Introduces the concepts and techniques through concise and intuitive examples Focuses on understanding by moving distracting formulae and mathematical notation to appendices Offers intuition, insights, humor, and practical advice for students of business statistics Features coverage of sampling techniques, descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis tests, and regression Written for undergraduate business students, business and economics majors, teachers, and practitioners, A Guide to Business Statistics offers an accessible guide to the key concepts and fundamental principles in statistics.
Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.
This Book Has Been Written In Such A Way That The Study Of Statistics Is Made Interesting And It Has Been Oriented Towards Application Of Statistical Techniques To A Variety Of Real Life Problems. Most Of The Existing Books Discuss Application Of Statistical Techniques To Problems Such As Height And Weight, Ages Of Husband And Wife, Etc. There Is Hardly Any Book Which Is Contextually Relevant For Teaching Statistics At The Undergraduate Level. An Attempt Has Been Made In This Book To Bridge This Gap.Authors Have Introduced Varied Real Life Examples By Including A Large Number Of Solved Examples To Illustrate How Statistical Techniques Can Actually Be Applied To A Wide Variety Of Real Life Problems. Many Illustrations Have Been Drawn From Various University Examinations Also. In Addition, To Provide An Opportunity Of Students To Gain More Skills To Apply The Concepts, Large Number Of Problems Have Been Included At The End Of Each Chapter. The Book Contains Fifteen Chapters And The Concepts Have Been Discussed In A Simple Language. The Book Is Meant For Undergraduate Students Of All Indian Universities. It Will Also Serve As A Text For The Professional Examinations, Including Ca And Costing.
The spread of sophisticated computer packages and the machinery on which to run them has meant that procedures which were previously only available to experienced researchers with access to expensive machines and research students can now be carried out in a few seconds by almost every undergraduate. Understanding and Using Advanced Statistics provides the basis for gaining an understanding of what these analytic procedures do, when they should be used, and what the results provided signify. This comprehensive textbook guides students and researchers through the transition from simple statistics to more complex procedures with accessible language and illustration.
Statistics for Business is meant as a textbook for students in business, computer science, bioengineering, environmental technology, and mathematics. In recent years, business statistics is used widely for decision making in business endeavours. It emphasizes statistical applications, statistical model building, and determining the manual solution methods. Special Features: This text is prepared based on "self-taught" method. For most of the methods, the required algorithm is clearly explained using flow-charting methodology. More than 200 solved problems provided. More than 175 end-of-chapter exercises with answers are provided. This allows teachers ample flexibility in adopting the textbook to their individual class plans. This textbook is meant to for beginners and advanced learners as a text in Statistics for Business or Applied Statistics for undergraduate and graduate students.
In this edition, efforts have been made to assist readers in converting data into useful information that can be used by decision-makers in making more thoughtful, information-based decisions.
Show students why business statistics is an increasingly important business skill through a student-friendly pedagogy. In this fourth Canadian edition of Business Statistics For Contemporary Decision Making authors Ken Black, Tiffany Bayley, and Ignacio Castillo uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today's workplace.
