Introduction to Business Data Processing PDF Download
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Author: Lawrence Orilia Publisher: McGraw-Hill Companies ISBN: Category : Business Languages : en Pages : 776
Book Description
Introduces Computers & Business Data Processing in a Nontechnical Form. Covers Subjects from Flowcharting & Languages to Computerized Crime & Word Processing
Author: Lawrence Orilia Publisher: McGraw-Hill Companies ISBN: Category : Business Languages : en Pages : 776
Book Description
Introduces Computers & Business Data Processing in a Nontechnical Form. Covers Subjects from Flowcharting & Languages to Computerized Crime & Word Processing
Author: Adam Fleischhacker Publisher: ISBN: Category : Languages : en Pages : 298
Book Description
This up-to-date business analytics textbook (published in July 2020) will get you harnessing the power of the R programming language to: manipulate and model data, discover and communicate insight, to visually communicate that insight, and successfully advocate for change within an organization. Book Description A frequent teaching-award winning professor with an analytics-industry background shares his hands-on guide to learning business analytics. It is the first textbook addressing a complete and modern business analytics workflow that includes data manipulation, data visualization, modelling business problems with graphical models, translating graphical models into code, and presenting insights back to stakeholders. Book Highlights Content that is accessible to anyone, even most analytics beginners. If you have taken a stats course, you are good to go. Assumes no knowledge of the R programming language. Provides introduction to R, RStudio, and the Tidyverse. Provides a solid foundation and an implementable workflow for anyone wading into the Bayesian inference waters. Provides a complete workflow within the R-ecosystem; there is no need to learn several programming languages or work through clunky interfaces between software tools. First book introducing two powerful R-packages - `causact` for visual modelling of business problems and `greta` which is an R interface to `TensorFlow` used for Bayesian inference. Uses the intuitive coding practices of the `tidyverse` including using `dplyr` for data manipulation and `ggplot2` for data visualization. Datasets that are freely and easily accessible. Code for generating all results and almost every visualization used in the textbook. Do not learn statistical computation or fancy math in a vacuum, learn it through this guide within the context of solving business problems.
Author: Gábor Békés Publisher: Cambridge University Press ISBN: 1108483011 Category : Business & Economics Languages : en Pages : 741
Book Description
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Author: Lawrence Orilia
Author: Lawrence Orilia
Author: Lawrence Orilia
Author: Adam Fleischhacker
Author: Gary B. Shelly
Author: Robert R. Arnold
Author: Beryl Robichaud
Author: Gábor Békés
Author: Robert J. Thierauf
Author: Fred Hulme
Author: Stuart S. Fink