**Core Concept**
Stratified sampling is a method of selecting a representative sample from a population by dividing it into distinct subgroups or strata based on specific characteristics, and then randomly sampling from each subgroup. This approach helps to ensure that the sample is representative of the population and reduces sampling bias.

**Why the Correct Answer is Right**
The ideal data for stratified sampling should be in the form of a proportion or percentage, which represents the size of each subgroup within the population. This proportion is used to determine the number of samples to be taken from each subgroup. For example, if the population is divided into three strata, with proportions of 40%, 30%, and 30%, the ideal data would be expressed as 0.4, 0.3, and 0.3, respectively. This allows for the calculation of the sample size for each subgroup, ensuring that the sample is representative of the population.

**Why Each Wrong Option is Incorrect**
* **Option A:** This option is not relevant to stratified sampling, as it does not provide any information about the size of the subgroups within the population.
* **Option B:** This option is incorrect because it does not provide a clear proportion or percentage, making it impossible to determine the sample size for each subgroup.
* **Option C:** This option is incorrect because it provides a value that is not a proportion or percentage, making it unsuitable for stratified sampling.

**Clinical Pearl / High-Yield Fact**
When using stratified sampling, it is essential to ensure that the proportions of each subgroup are accurate and up-to-date, as this will directly impact the representativeness of the sample.

**Correct Answer: D.**