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This month we highlight these 3 books:
They're all FREE, so help yourselves...
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An essential guide to the trouble spots and oddities of R. In spite of the quirks exposed here, R is the best computing environment for most data analysis tasks. R is free, open-source, and has thousands of contributed packages. It is used in such diverse fields as ecology, finance, genomics and music. If you are using spreadsheets to understand data, switch to R. You will have safer -- and ultimately, more convenient -- computations.
The emphasis of this text is on the practice of regression and analysis of variance. The objective is to learn what methods are available and more importantly, when they should be applied.
This book is not for beginners. It presumes some knowledge of basic statistical theory and practice, such as statistical inference like estimation, hypothesis testing and confidence intervals. A basic knowledge of data analysis is presumed. Some linear algebra and calculus is also required..
This is a simple introduction to time series analysis using the R statistics software (have you spotted the pattern yet?). It includes instruction on how to read and plot time series, time series decomposition, forecasting, and ARIMA models
Related Udemy Video Courses
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