Final answer:
When constructing bins for a frequency distribution of quantitative data, it is generally recommended to follow principles such as having equal interval widths, excluding the lower limit from the bin and including the upper limit, avoiding overlap of bin limits, and ensuring that the last value of a class is also the first value of the subsequent class.
Step-by-step explanation:
When constructing bins for a frequency distribution of quantitative data, it is generally recommended to follow the following principles:
- Bins should have equal interval widths: This means that the width of each bin should be the same. For example, if you have a range of data from 0 to 100 and you want to create 5 bins, each bin would have a width of 20.
- The lower limit is excluded from the bin and the upper limit is included: This means that when a data value falls on the lower limit of a bin, it is not counted in that bin. But when a data value falls on the upper limit of a bin, it is included in that bin.
- The bin limits should not overlap: This means that the range of each bin should not overlap with the range of other bins. Each data value should only be placed in one bin.
- The last value of a class should also be the first value of the subsequent class: This means that the upper limit of one bin should be the same as the lower limit of the next bin, to ensure there are no gaps or overlaps between bins.