The author includes motivating examples to inspire readers to generate programming solutions. Upper-level undergraduates, bning graduate students, and professionals involved in generating programming solutions for data-analytic problems will benefit from this book. The ideal background for a reader is some background in regression modeling and introductory experience with computer programming.

The coverage of statistical programming in the second edition includes

 Getting data into the SAS system, eeering new features, and formatting variables

 Writing readable and well-documented code

 Structuring, implementing, and debugging programs that are well documented

 Creating solutions to novel problems

 Combining data sources, extracting parts of data sets, and reshaping data sets as needed for other analyses

 Generating general solutions using macros

 Customizing output

 Producing insight-inspiring data visualizations

 Parsing, processing, and analyzing text

 Programming solutions using matrices and connecting to R

 Processing text

 Programming with matrices

 Connecting SAS with R

 Covering topics that are part of both base and certification exams.



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