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Published byKristina Clarke Modified over 9 years ago
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Psychology 202a Advanced Psychological Statistics September 3, 2015
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The show so far Last time we talked about: –variables –distributions –grouping –ways of understanding the shape of a distribution
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Peabody Distribution ValuesFrequency 55 – 591 60 – 642 65 – 695 70 – 742 75 – 794 80 – 848 85 – 896 90 – 948 95 – 993 100 – 1041
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Software We saw that functions in R tend to use fairly intuitive names (e.g., sort(), stem()). We were about to introduce SAS and begin a discussion of descriptive statistics. Let’s do that now.
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Ways of understanding shape Graphics. Descriptive statistics.
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Histograms A histogram is a picture of the frequency distribution: –group the data (7 to 15 intervals) –identify real limits and midpoints of intervals –draw “histobars” over the intervals –use informative labels
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Peabody Distribution ValuesFrequency 55 – 591 60 – 642 65 – 695 70 – 742 75 – 794 80 – 848 85 – 896 90 – 948 95 – 993 100 – 1041
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Histograms in R hist(Peabody) R has done a pretty good job: –informative labels –reasonable number of intervals but the limits R chose for the intervals are a little strange help(hist)
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