Final answer:
An ordinal variable represents order information in datasets with categories that have a meaningful order. Number of times per week is quantitative discrete data, and duration is quantitative continuous data. A histogram is used for continuous data and can help identify potential outliers.
Step-by-step explanation:
A variable where the values represent order information is known as ordinal data. Ordinal data is one of the levels of measurement in statistics and represents categories with a meaningful order or ranking among them, but the differences between the categories may not necessarily be consistent or have a measurable distance. For instance, class ranks such as freshman, sophomore, junior, and senior are ordinal because they indicate a progression but without a precise difference between the ranks.
Number of times per week would be classified as quantitative discrete data because these data take on only certain numerical values and result from counting. For example, if you count the number of phone calls you receive for each day, you will end up with discrete values such as zero, one, two, three, etc.
The duration of an event would be considered quantitative continuous data because it can take on any value within a given range and can be measured more precisely. For example, the length of time spent exercising could be 30 minutes, 30.5 minutes, 30.75 minutes, and so on. These data can be represented on a continuous scale.
For data represented in a histogram, it is essential to differentiate between continuous and discrete data because a histogram is suitable for displaying continuous data, where it helps to show the distribution of the data values. When constructing a histogram, it is also important to note potential outliers which can be identified using specific formulas to check whether the end values fall outside the expected range of the dataset.