The Little sas book election of the models are critical. Interpretation of the results can often be difficult and subjective. We assume that readers who are interested in statistical computing already know something about statistics. People who want to use statistical procedures but are unfamiliar with these concepts should consult a statistician, seek out an introductory statistics text, or, better yet, take a course in statistics Modular sections Our goal in writing this book is to make learning SAS as easy and enjoyable as possible. Lets face itSAS is a big topic. You may have already spent some time scratching your head in front of a shelf full of SAS manuals, or staring at a screen full of online documentation until your eyes become blurry. We cant condense all of SAs into this little book, but we can odense topics into short, readable sections This entire book is composed of two-page sections, each section a complete topic. This way, you can easily skip over topics which do not apply to you. Of course, we think every section is important, or we would not have included it. You probably don' t need to know everything in this book, however, to complete your job. By presenting topics in short digestible sections, we believe that learning SAS will be easier and more fun--like eating three meals a day instead of one giant meal a week Graphics Wherever possible, graphic illustrations either identify the contents of the section or help explain the topic. A box with rough edges indicates a raw data file, and a box with nice smooth edges indicates a SAs data set. The squiggles inside the box indicate data-any old data-and a period indicates a missing value. The arrow between boxes of these types means that the section explains how to get from data that look like the one box to data that look like the other. Some sections have graphics which depict printed output. These graphics look like a stack rs with headers printed at the top of the page sAS data set wwM 作W N ww W dataxii The Little SAS Book raw data file SAS data set data SAS output Obs Lions Tigers Bears 1 2 3 4 selection of the models are critical. Interpretation of the results can often be difficult and subjective. We assume that readers who are interested in statistical computing already know something about statistics. People who want to use statistical procedures but are unfamiliar with these concepts should consult a statistician, seek out an introductory statistics text, or, better yet, take a course in statistics. Modular sections Our goal in writing this book is to make learning SAS as easy and enjoyable as possible. Let’s face it
SAS is a big topic. You may have already spent some time scratching your head in front of a shelf full of SAS manuals, or staring at a screen full of online documentation until your eyes become blurry. We can’t condense all of SAS into this little book, but we can condense topics into short, readable sections. This entire book is composed of two-page sections, each section a complete topic. This way, you can easily skip over topics which do not apply to you. Of course, we think every section is important, or we would not have included it. You probably don’t need to know everything in this book, however, to complete your job. By presenting topics in short digestible sections, we believe that learning SAS will be easier and more fun
like eating three meals a day instead of one giant meal a week. Graphics Wherever possible, graphic illustrations either identify the contents of the section or help explain the topic. A box with rough edges indicates a raw data file, and a box with nice smooth edges indicates a SAS data set. The squiggles inside the box indicate data—any old data—and a period indicates a missing value. The arrow between boxes of these types means that the section explains how to get from data that look like the one box to data that look like the other. Some sections have graphics which depict printed output. These graphics look like a stack of papers with headers printed at the top of the page