Final answer:
The ratio data in the provided dataset is the Item cost, which allows for meaningful calculation of differences and ratios due to its quantitative continuous nature and a true zero point.
Step-by-step explanation:
The ratio data in a dataset containing purchase details of a shoe manufacturing company pertains to measurable quantities for which comparisons in terms of multiples or fractions make sense. In the given list, the component that represents ratio data is Item cost. The item cost can be classified as quantitative continuous data because it can have an infinite number of values within a range and it has a true zero point, meaning that an item can have no cost, and we can make meaningful ratios. For example, one item might be twice as expensive as another.
Item Number is considered quantitative discrete data as it represents countable items. The Rank of suppliers would be qualitative or categorical data since it represents order without a measurable magnitude. Arrival Date, although it involves numbers, is not considered ratio data because time scales typically do not have a meaningful zero point in the context of ratio comparisons.
Ratio data is the most informative level of measurement, which allows for the calculation of meaningful differences and ratios between data points. For instance, when dealing with multiple choice statistics exam scores that are machine-graded, where the scores range from 0 to 100, we can order the scores, calculate differences, and establish ratios because the scale has a true zero point and the differences and ratios have meaning.