Xcelsius updating data
Rather, the problem has to do with two slices are “Non-Institutional Population” and “Civilian Labor Force.” “Non-Institutional Population” represents everyone who could be working, whether they want a job or not, while “Civilian Labor Force” represents those people who either have a job or are actively looking for one.In other words, the “Civilian Labor Force” is a subset of the “Non-Institutional Population”, not a separate segment that combines with it to make up some whole.The application provides a pie chart for comparing the America’s non-institutional population to the civilian labor force and two gauges for comparing employment and unemployment rates.Neither pie charts nor gauges of this type support effective comparisons, and in this case, because of fundamental design problems, comparisons between slices of the pie or the two gauges actually mislead.
For instance, if you need to analyze sales data, you can use the sales data template.
Because they omit quantitative scales, we can’t compare the employment or unemployment rates based on the positions of the pointer. They could start and end at different values—we have no way of telling.
Take a moment to see if you can figure out the values that are associated with each of the tick marks. We’re forced to read the values printed as text, which we could do more quickly using the original tables.
The employment data comes from a 53 page PDF file filled with tables of numbers, prepared by the Bureau of Labor Statistics.
What’s sad is that the original PDF file, with its many tables (one per state) is actually much more useful for data analysis than the analytical application that Business Objects has built.
If the employment rate in the above screenshot were calculated the same way as the unemployment rate, it would be 95.4% instead of 63%.