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Data Manipulation in SAS

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Data Manipulation in SAS

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    1. Data Manipulation in SAS Mike Juhan Susan Felege

    2. Why SAS? That was our topic! Disadvantages Expensive Additional software packages/ tutorials = License Renewal Advantages Powerful Statistical package Commonly used

    3. Types Of Data Manipulation There are many Basic Transformations log/ ln Inverse Resample Bootstrapping Jackknife Create subsets of data Rename variables

    4. Data Sets VPA Basal areas at turkey locations Stem density counts (trees per acre) Rabbits Fictitious dataset of rabbit pop tracked over 175 generations Age-specific survival rates Case 2000 ‘some animal’ example Population projections

    5. Our Goals Import data from Access Rename variables Conditional statements New dataset with an extra column (do block) Sub-datasets Histogram (gchart) Basic log transformation Jackknife (macro, do loop) Plots (gplot) Proc IML (arrays and do loop)

    6. Importing Data from Access Import Wizard

    8. Renaming of VariablesRenaming of Variables

    9. Conditional statementsConditional statements

    15. Jackknife data rabbits; input generation pop; y=pop; x1=generation; datalines; 1 62 2 79 3 89 4 84 5 59 6 86 7 92 8 58 9 94 86 … 175 91 ;

    20. Population Projection

    23. Helpful Resources Applied Statistics and the SAS Programming Language (Cody and Smith 1997) The Little SAS Book (Delwiche and Slaughter) The Web (Google) utexas website UCLA website

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