An Introduction to Modern Business Statistics
Using the computer to eliminate rote computation and facilitate learning, this book inspires and motivates readers to learn statistics by showing them its great practical importance to their careers. In every chapter, the authors include an ample number of examples and vignettes that illustrate and emphasize skills that enable students to interpret data effectively and to convert data into usable information. This approach enhances students' abilities to make better decisions, thus preparing them to exert greater influence in their future careers. To reinforce the idea that statistics is the linkage that transforms data into useful information, thereby enhancing planning and decision making, almost every numbered example includes introductory language that articulates the importance of the illustration in a functional area of business. The authors use Microsoft Excel, MINITAB, and JMP IN statistical software to execute statistical methods--presenting computer outputs and interpretation first; then illustrating the method using statistical tables. In addition, to promote the learning of fundamentals, the authors also take the users through many methods step-by-step, using examples with very small data sets. Chapter appendices provide clear, detailed instructions on the use of Excel, MINITAB, and JMP IN. Users are not just purchasing a textbook--every new copy of the book is packaged with a student software and data disk. This disk contains Data Analysis Plus Add-ins for Microsoft Excel, as well as all the data sets used in the book formatted for Excel, MINITAB, JMP IN, and ASCII. In addition to the many examples and exercises they included in the First Edition, the authors add approximately 120 exercises based on published articles in academic journals, the popular media, or widely available sources of data. Many of these exercises contain large data sets, and many are revisited is subsequent chapters.
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INTRODUCTION TO STATISTICS
Introduction to Minitab Excel and JMP IN
EXPLORING AND SUMMARIZING DATA 42
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alternative hypothesis analysis of variance appraisers Assume average binomial distribution box plot button CALCULATOR window cells Chapter choose claim click OK column confidence interval continuous random variable corresponding customers data contradict data set data values defective degrees of freedom dialogue box difference dot diagrams enter example expected value Explain Figure forecast frequency gender given Graph the data histogram hypothesis testing illustrate income indicate manager margin of sampling median Minitab normal distribution null hypothesis observed outcomes output P-value parameter policy amounts population or process prediction predictor variables probability distribution procedure process mean quantile value random sample Refer to Exercise regression model relationship represent residuals result run chart sample data sample mean sample proportion sampling distribution sampling error scatter diagram simple events specific standard deviation standard error standard normal statistical inference sum of squares Suppose Table test grades variation