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Titlebook: Excel 2019 for Educational and Psychological Statistics; A Guide to Solving P Thomas J. Quirk Textbook 2020Latest edition The Editor(s) (if

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11#
發(fā)表于 2025-3-23 10:13:43 | 只看該作者
Textbook 2020Latest editiontics effectively. Similar to the previously published?.Excel 2016 for Educational and Psychological Statistics., it is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical education and psychology problems..Excel, a widely available compute
12#
發(fā)表于 2025-3-23 17:50:08 | 只看該作者
2570-4605 hat should be happening on the reader‘s computer monitor, enNewly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching educational and psychological statistics effectively. Similar to the previously published?.Excel 2016 for Educational and Psyc
13#
發(fā)表于 2025-3-23 18:58:57 | 只看該作者
14#
發(fā)表于 2025-3-24 00:23:39 | 只看該作者
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發(fā)表于 2025-3-24 04:17:27 | 只看該作者
16#
發(fā)表于 2025-3-24 06:33:44 | 只看該作者
One-Group t-Test for the Mean,difference between 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 fo
17#
發(fā)表于 2025-3-24 14:43:56 | 只看該作者
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發(fā)表于 2025-3-24 17:40:56 | 只看該作者
19#
發(fā)表于 2025-3-24 22:19:47 | 只看該作者
Multiple Correlation and Multiple Regression,eded to write the multiple regression equation for the data. Finally, the Excel commands needed to find the correlation between all of the variables is explained so that you can create a “correlation matrix” for your data set. You will learn how to read this correlation matrix to determine the corre
20#
發(fā)表于 2025-3-25 02:22:16 | 只看該作者
One-Way Analysis of Variance (ANOVA),see if they are “significantly different from each other.” If this overall ANOVA test 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 example is used delineating the
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