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5.6: Computing a Cumulative Distribution (Section 4.2.2)

  • Page ID
    8731
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    Let’s compute a cumulative distribution for the SleepHrsNight variable in NHANES. This looks very similar to what we saw in the previous section.

    # create summary table for relative frequency of different
    # values of SleepHrsNight 
    
    SleepHrsNight_cumulative <- 
      NHANES_unique %>%
      # drop NA values for SleepHrsNight variable
      drop_na(SleepHrsNight) %>%
      # remove other variables
      dplyr::select(SleepHrsNight) %>%
      # group by values
      group_by(SleepHrsNight) %>%
      # create summary table
      summarize(AbsoluteFrequency = n()) %>%
      # create relative and cumulative frequencies
      mutate(
        RelativeFrequency = AbsoluteFrequency / sum(AbsoluteFrequency),
        CumulativeDensity = cumsum(RelativeFrequency)
      )
    
    kable(SleepHrsNight_cumulative)
    SleepHrsNight AbsoluteFrequency RelativeFrequency CumulativeDensity
    2 9 0.00 0.00
    3 49 0.01 0.01
    4 200 0.04 0.05
    5 406 0.08 0.13
    6 1172 0.23 0.36
    7 1394 0.28 0.64
    8 1405 0.28 0.92
    9 271 0.05 0.97
    10 97 0.02 0.99
    11 15 0.00 1.00
    12 17 0.00 1.00

    5.6: Computing a Cumulative Distribution (Section 4.2.2) is shared under a not declared license and was authored, remixed, and/or curated by Russell A. Poldrack via source content that was edited to conform to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.