標題: Titlebook: Excel 2016 for Engineering Statistics; A Guide to Solving P Thomas J. Quirk Textbook 20161st edition The Editor(s) (if applicable) and The [打印本頁] 作者: 多愁善感 時間: 2025-3-21 19:53
書目名稱Excel 2016 for Engineering Statistics影響因子(影響力)
書目名稱Excel 2016 for Engineering Statistics影響因子(影響力)學科排名
書目名稱Excel 2016 for Engineering Statistics網(wǎng)絡(luò)公開度
書目名稱Excel 2016 for Engineering Statistics網(wǎng)絡(luò)公開度學科排名
書目名稱Excel 2016 for Engineering Statistics被引頻次
書目名稱Excel 2016 for Engineering Statistics被引頻次學科排名
書目名稱Excel 2016 for Engineering Statistics年度引用
書目名稱Excel 2016 for Engineering Statistics年度引用學科排名
書目名稱Excel 2016 for Engineering Statistics讀者反饋
書目名稱Excel 2016 for Engineering Statistics讀者反饋學科排名
作者: 怎樣才咆哮 時間: 2025-3-21 21:25
Random Number Generator,from which you want to take a random sample. You will learn how to use Excel to create frame numbers for generating random numbers, why a set of duplicate frame numbers is important, and the Excel commands needed to sort the frame numbers into a random sequence. In addition, you will learn how to pr作者: 競選運動 時間: 2025-3-22 04:26 作者: botany 時間: 2025-3-22 06:08
One-Group t-Test for the Mean,. 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作者: FLIP 時間: 2025-3-22 11:09
Two-Group t-Test of the Difference of the Means for Independent Groups,nd one measurement “number” on each of these. This chapter asks you to change gears and deal with the situation in which you are measuring two groups of instead of only one group. The nine steps for hypothesis-testing using the two-group t-test are presented, including the decision rule for either a作者: 帶子 時間: 2025-3-22 13:48 作者: 帶子 時間: 2025-3-22 20:42 作者: 調(diào)整 時間: 2025-3-22 22:51 作者: 隱藏 時間: 2025-3-23 04:02 作者: Brocas-Area 時間: 2025-3-23 08:03 作者: BUST 時間: 2025-3-23 10:58 作者: 要素 時間: 2025-3-23 16:16
2570-4605 ractice problems at the end of each chapter enable you to te.This book shows the capabilities of Microsoft Excel in teaching engineering statistics effectively. Similar to the previously published .Excel 2013 for Engineering Statistics., this book is a step-by-step exercise-driven guide for students作者: Lignans 時間: 2025-3-23 21:26 作者: DEAF 時間: 2025-3-24 01:59
2570-4605 chniques necessary in their courses and work..Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand engineering problems. Practice problem978-3-319-39182-3Series ISSN 2570-4605 Series E-ISSN 2570-4613 作者: 跳脫衣舞的人 時間: 2025-3-24 05:17 作者: Lethargic 時間: 2025-3-24 07:31
Joshua Dinaburg,Daniel T. Gottuk test, and you will be given specific explanations of how to write both the result and the conclusion of a hypothesis test. Alternative ways to summarize the result of a hypothesis test are also presented. Three practice problems are given at the end of the chapter to test your Excel skills, and the作者: intolerance 時間: 2025-3-24 13:58
https://doi.org/10.1007/978-3-030-73267-7 the 95?% confidence interval about the mean (Chap. .) and the one-group t-test is explained. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem is presented in the作者: LEER 時間: 2025-3-24 17:37
John Gales,René Champagne,Michael Kinseytical example. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem is presented in the Practice Test given in Appendix B along with its answer in Appendix C of this 作者: Flawless 時間: 2025-3-24 19:52
Characteristic Set of Buildings,th the Excel steps needed to create a chart summarizing the relationship between the two variables. You will learn how to use Excel to draw the “best-fit line” through the data points on a scatterplot and how to determine the equation for this line so that you can use this equation to predict one va作者: Graduated 時間: 2025-3-25 00:57 作者: ineptitude 時間: 2025-3-25 04:23 作者: Fecal-Impaction 時間: 2025-3-25 10:45 作者: 博愛家 時間: 2025-3-25 12:48 作者: DEFER 時間: 2025-3-25 17:41
One-Group t-Test for the Mean, the 95?% confidence interval about the mean (Chap. .) and the one-group t-test is explained. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem is presented in the作者: BLANC 時間: 2025-3-25 23:06 作者: 填料 時間: 2025-3-26 00:15 作者: 流利圓滑 時間: 2025-3-26 04:50 作者: 吊胃口 時間: 2025-3-26 10:41
One-Way Analysis of Variance (ANOVA),ups to see if they are “significantly different from each other.” If this overall ANOVA test is produces a significant result, you will learn how to test the hypotheses comparing any two groups using an ANOVA t-test formula. This formula is presented, explained, and a practical engineering example i作者: Prognosis 時間: 2025-3-26 15:16 作者: conduct 時間: 2025-3-26 18:39 作者: 類似思想 時間: 2025-3-26 21:42
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作者: Limerick 時間: 2025-3-27 01:48
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作者: 動作謎 時間: 2025-3-27 05:24 作者: Throttle 時間: 2025-3-27 11:25 作者: 身心疲憊 時間: 2025-3-27 17:26
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 作者: Spongy-Bone 時間: 2025-3-27 18:21
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作者: ABOUT 時間: 2025-3-27 23:37
https://doi.org/10.1007/978-3-319-39182-3Applied Engineering Statistics; Applied Statistics; Basic Engineering Statistics; Engineering Statistic作者: Schlemms-Canal 時間: 2025-3-28 02:53
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 財產(chǎn) 時間: 2025-3-28 09:59
Excel 2016 for Engineering Statistics978-3-319-39182-3Series ISSN 2570-4605 Series E-ISSN 2570-4613 作者: Priapism 時間: 2025-3-28 11:06
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作者: 強壯 時間: 2025-3-28 16:06 作者: Implicit 時間: 2025-3-28 20:31
Reliability Prediction and Modellingve measure of how close a design comes to meeting the design objectives and permits comparisons between different design proposals to be made. It has already been emphasised that reliability prediction is an imprecise calculation, but it is nevertheless a valuable exercise for the following reaons:作者: Breach 時間: 2025-3-29 00:02
