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Let

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Let s review some of the statistics you ve learned in your first class: Univariate analyses (single variable) are done both graphically and numerically. – PowerPoint PPT presentation

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Tags: proc | univariate

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Title: Let


1
  • Lets review some of the statistics youve
    learned in your first class
  • Univariate analyses (single variable) are done
    both graphically and numerically. For
    categorical variables, use bar graphs and
    percentages. SAS does this with PROC GCHART and
    PROC FREQ
  • PROC GCHART DATApadgett VBAR marsh
  • title Vertical Bar Graph
  • PROC GCHART DATApadgett HBAR marsh
  • title Horizontal Bar Graph
  • PROC GCHART DATApadgett HBAR plantht
  • title Histogram (sort of)
  • choose your own midpoints with the option
    /midpoints a to b by
  • PROC FREQ DATApadgett TABLES marsh type flower
    run quit

2
  • For quantitative variables, use histograms, stem
    and leaf plots, boxplots (especially for
    comparisons - more later), quantile plots
    (probability plots). SAS does this with PROCs
    UNIVARIATE, MEANS, SUMMARY, TABULATE, REPORT,
    etc. Right now, well concentrate on UNIVARIATE
  • PROC UNIVARIATE DATApadgett VAR plantht
    totmass title Lots of Statistics run quit
  • PROC UNIVARIATE DATApadgett NORMAL PLOT VAR
    plantht totmass title With the NORMAL and PLOT
    options
  • run quit
  • Better histogram is done in UNIVARIATE with the
    HISTOGRAM statement
  • PROC UNIVARIATE DATApadgett VAR plantht
    totmass
  • HISTOGRAM plantht /MIDPOINTS 0 to 150 by 25
    NORMAL
  • INSET MEANMean (7.2)
  • STDStandard Deviation (7.2)/FontCourier
  • POSNW HEIGHT3 run quit

3
  • UNIVARIATE also gives very nice normal quantile
    and normal probability plots
  • PROC UNIVARIATE DATApadgett VAR plantht
    totmass
  • QQPLOT totmass PROBPLOT plantht run quit
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