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Viser: R for Microsoft Excel Users - Making the Transition for Statistical Analysis
R for Microsoft® Excel Users Vital Source e-bog
Conrad Carlberg
(2016)
R for Microsoft® Excel Users Vital Source e-bog
Conrad Carlberg
(2016)
R for Microsoft® Excel Users Vital Source e-bog
Conrad Carlberg
(2016)
R for Microsoft Excel Users
Making the Transition for Statistical Analysis
Conrad Carlberg
(2016)
Sprog: Engelsk
Detaljer om varen
- 1. Udgave
- Vital Source 90 day rentals (dynamic pages)
- Udgiver: Pearson International (November 2016)
- ISBN: 9780134571898R90
Bookshelf online: 90 dage fra købsdato.
Bookshelf appen: 90 dage fra købsdato.
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Detaljer om varen
- 1. Udgave
- Vital Source 180 day rentals (dynamic pages)
- Udgiver: Pearson International (November 2016)
- ISBN: 9780134571898R180
Bookshelf online: 180 dage fra købsdato.
Bookshelf appen: 180 dage fra købsdato.
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Detaljer om varen
- 1. Udgave
- Vital Source 365 day rentals (dynamic pages)
- Udgiver: Pearson International (November 2016)
- ISBN: 9780134571898R365
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: 5 år fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
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Detaljer om varen
- Paperback: 272 sider
- Udgiver: Pearson Education (November 2016)
- ISBN: 9780789757852
Drawing on his immense experience helping organizations apply statistical methods, Carlberg reviews how to perform key tasks in Excel, and then guides you through reaching the same outcome in R--including which packages to install and how to access them. Carlberg offers expert advice on when and how to use Excel, when and how to use R instead, and the strengths and weaknesses of each tool.
Writing in clear, understandable English, Carlberg combines essential statistical theory with hands-on examples reflecting real-world challenges. By the time you've finished, you'll be comfortable using R to solve a wide spectrum of problems--including many you just couldn't handle with Excel.
- Smoothly transition to R and its radically different user interface - Leverage the R community's immense library of packages - Efficiently move data between Excel and R - Use R's DescTools for descriptive statistics, including bivariate analyses - Perform regression analysis and statistical inference in R and Excel - Analyze variance and covariance, including single-factor and factorial ANOVA - Use R's mlogit package and glm function for Solver-style logistic regression - Analyze time series and principal components with R and Excel