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Titlebook: Excel 2016 for Physical Sciences Statistics; A Guide to Solving P Thomas J. Quirk,Meghan H. Quirk,Howard F. Horton Textbook 20161st edition

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樓主: Lincoln
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發(fā)表于 2025-3-27 01:02:31 | 只看該作者
32#
發(fā)表于 2025-3-27 02:19:22 | 只看該作者
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發(fā)表于 2025-3-27 06:26:25 | 只看該作者
Neuroleptanalgesia in Ophthalmic Surgeryation 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 to determine if this difference was a “significant
34#
發(fā)表于 2025-3-27 11:35:18 | 只看該作者
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發(fā)表于 2025-3-27 17:29:18 | 只看該作者
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
36#
發(fā)表于 2025-3-27 20:50:37 | 只看該作者
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發(fā)表于 2025-3-27 23:55:06 | 只看該作者
One-Group t-Test for the Mean,is 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 your ca
38#
發(fā)表于 2025-3-28 03:08:39 | 只看該作者
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
39#
發(fā)表于 2025-3-28 07:02:29 | 只看該作者
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發(fā)表于 2025-3-28 12:32:25 | 只看該作者
Multiple Correlation and Multiple Regression,l 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 weighted differently in an equation, to predict Y. The job of multiple correlation is to
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