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Titlebook: Excel 2016 for Engineering Statistics; A Guide to Solving P Thomas J. Quirk Textbook 20161st edition The Editor(s) (if applicable) and The

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樓主: 多愁善感
31#
發(fā)表于 2025-3-26 21:42:36 | 只看該作者
Joshua Dinaburg,Daniel T. Gottuk confidence interval. You will learn how to estimate the population mean (average) for a group of events or objects at a 95?% confidence level so that you are 95?% confident that the population mean is between a lower limit of the data and an upper limit of the data. The formula for computing this c
32#
發(fā)表于 2025-3-27 01:48:37 | 只看該作者
https://doi.org/10.1007/978-3-030-73267-7. This test compares the mean of your data set against the hypothesized population mean for your data to determine if the difference between these two values is “l(fā)arge enough” to be considered a “significant difference.” The formula is presented, explained, and a practical example is given using you
33#
發(fā)表于 2025-3-27 05:24:37 | 只看該作者
34#
發(fā)表于 2025-3-27 11:25:29 | 只看該作者
35#
發(fā)表于 2025-3-27 17:26:22 | 只看該作者
Andrew F. Blum,R. Thomas Long Jr.model by using . to predict Y instead of a single predictor as we discussed in Chap. . of this book. The resulting statistical procedure is called “multiple correlation” because it uses two or more predictors, each weighed differently in an equation, to predict Y. The job of multiple correlation is
36#
發(fā)表于 2025-3-27 18:21:34 | 只看該作者
https://doi.org/10.1007/978-3-031-24074-4ation mean for the data using either the 95?% confidence interval about the mean (Chap. . of this book) or the one-group t-test of the mean (Chap. . of this book). You have also learned how to test for the difference between the means for two groups of to determine if this difference was a “signific
37#
發(fā)表于 2025-3-27 23:37:52 | 只看該作者
https://doi.org/10.1007/978-3-319-39182-3Applied Engineering Statistics; Applied Statistics; Basic Engineering Statistics; Engineering Statistic
38#
發(fā)表于 2025-3-28 02:53:27 | 只看該作者
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
39#
發(fā)表于 2025-3-28 09:59:36 | 只看該作者
Excel 2016 for Engineering Statistics978-3-319-39182-3Series ISSN 2570-4605 Series E-ISSN 2570-4613
40#
發(fā)表于 2025-3-28 11:06:11 | 只看該作者
Thomas J. QuirkEach chapter presents key steps needed to solve practical, easy-to-understand engineering science problems using Excel. In addition, three practice problems at the end of each chapter enable you to te
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