Mark Gardener

Beginning R is a very good book to learn R. It does one thing and one thing very well - how to do data analysis in R. You need some mathematics and statistics background understand why you are doing ANOVA, for example, and how to interpret its results. But then again, expecting one book to do all is not realistic. The book promises to teach R and as mentioned above, it does it pretty well.

I found the chapters on ANOVA, Regression, and graphs more informative when compared with other similar books.

Most part of the book uses native functions of R. This simplifies the learning process and doesn't overwhelm the user with installation of the plethora of CRAN packages.

I think this can be your first book on R and I for sure learned a few more things in R.… (plus d'informations)

Managing Data Using Excel: Organizing, Summarizing and Visualizing Scientific Data joins others in the 'Research Skills' series and is a top recommendation for any who would use their Excel spreadsheet skills to organize and share scientific data, standing out from the crowd of more general 'how to use Excel' handbooks to address the specific needs of the scientific community.

There are basics here, from how to build a dataset handling variables and notes to summarizing data using averages, creating visual displays with graphs and pivot charts, and using these tables to fine-tune results and displays that export well into datasets and summaries scientists can share.

Exercises are provided to reinforce concepts, while tips and notes compliment the educational process by pointing out common Excel challenges. Plenty of tables and charts pepper the discussions while an index makes it easy to use this is a reference for at-a-glance information.

Plenty of general Excel handbooks document how to create datasets and apply calculations, but the specific focus on scientific data manipulation provided here makes it a top recommendation over any general tutorial.… (plus d'informations)