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>> Have you encountered many/any box-and-whisker plots in the course of your work? On other dashboards?
I’ve encountered box-and-whisker plots in my work, but to be entirely honest, have always had a difficult time deciphering what’s what. I’ve found the leading diagram on this site, with explanations, particularly helpful and a useful reference/reminder:
https://flowingdata.com/wp-content/uploads/2008/02/box-plot-explained.gif
As for where, most commonly I’ve seen box-and-whisker plots used in presentations of clinical trial data in study reports, manuscripts, and medical journals. Closest I’ve seen to use within a dashboard, although not a dashboard, has been in abstracts and/or on research posters.>> What about histograms?
Until this course, I’d not tracked the difference between a histogram and a bar graph. Imagine I’ve seen them, yet not known they were their own entity.
>> If you have little or no prior experience with them, do you think they are easy to understand? If not, can you think of some alternate ways to display distribution data?
Box-and-whisker plots are likely tough to follow, especially for the first-timers or readers who are familiar, but have less experience with them. That said, I think histograms do a nice job of presenting distribution data, albeit with fewer criteria. Side-by-side histograms, as a rough means of comparison could be leveraged. If too cumbersome and/or there is not enough space, that’s where box-and-whisker plots allow you the flexibility of presenting distribution data in parallel for ease of comparison.
>> Which is the best type of graph to show ranking?
Bar chart.>> If we rank claims from most to least frequent, which service category would be at the top of the list (most frequent)?
Northern: Curative Care Visits (524)
Eastern: Curative Care Visits (589)>> Which would be at the bottom?
Northern: Equal frequencies for Inpatient Nursery/NICU, Inpatient Obstetrics, and Inpatient Surgery (3 each)
Eastern: Equal frequencies for Inpatient Medical and Inpatient Obstetrics (2 each)>> Is this true for both Eastern and Northern Zones, or do the rankings differ?
Most frequent claims service category is the same for both Northern and Eastern Zones, however least frequent claims service category varies between Northern and Eastern zones, but for the only overlap being Inpatient Obstetrics.>>Which type of graph do you think is best for showing Flores del Mundo’s membership trends over the course of the year?
– Based on Few’s work, I’d propose a line graph with points, given the ability to highlight the trend over time. As he notes, “lines do a great job of showing the shape of data as it flows and changes from point to point… the movement of values up and down through time”.>>Does your answer change if you’re graphing total membership versus employee/spouse/dependent?
– I’d move from line graph with points, to a bar graph here. Intent would be to demonstrate part-to-whole, with stacked bars to display employee, spouse, and dependent member data over time.>>Does your answer change if you want to show Eastern and Northern on the same graph?
– Here another time series where a bar graph, but without stacking, would be useful, placing Eastern and Northern data side-by-side for each time interval (be it monthly or quarterly).Hi all –
Look forward to learning with and from this group!
Considering if the WHO Local Maternity Dashboard is *really* a dashboard, I would suggest not. Citing the lecture from above, and the references noted in ‘Why Dashboards?’, I’m coming back to:
– at-a-glance
– strategic
– actionable
– visualized
The Maternity Dashboard does not allow for at-a-glance viewing (data-intensive, mix of absolute values and percentages, did not know where to look first), was only questionably strategic (did not lead me to much of a predefined conclusion, other than an over-target perinatal mortality possibly related to C-section rates and/or admissions to SCBU, however I’m unknowingly drawing that conclusion as the reader), only potentially actionable (again, the reader would draw a conclusion of their own, where this is more so a report than a dashboard), and the visualization was overwhelming (lots of color, could not see the shape of the data over time, difficult to note what data, if any, should be leveraged for comparison). In the absence of categorical data and quantitative relationships, it left me with many questions and turning back to the problem statement and conclusion for answers.Best,
Ian
