Explanation
The best sampling method for the data analyst's need is C. Stratified sampling.
Stratified sampling is a type of probability sampling that involves dividing the population into homogeneous groups or strata based on some characteristic, such as state, and then randomly selecting a proportional number of individuals from each stratum. Stratified sampling ensures that every group is adequately represented in the sample, and reduces the sampling error and variability12 Systematic sampling is not correct, because it involves selecting every nth individual from the population, starting from a random point. Systematic sampling does not guarantee that every state will have a similar proportion of data in the sample, and may introduce bias or error if there is a hidden pattern or order in the population12 Convenience sampling is not correct, because it involves selecting individuals who are easily accessible or available to the researcher. Convenience sampling is a type of non-probability sampling that does not involve random selection, and may result in a biased or unrepresentative sample12 Random sampling is not correct, because it involves selecting individuals from the population at random, without any grouping or stratification. Random sampling may not produce a sample that has a similar proportion of data from every state, especially if the population is large or heterogeneous. Random sampling may also have a higher sampling error and variability than stratified sampling12

Explanation
Discrete data is a type of data that can only take certain values, usually whole numbers or integers. Discrete data can be counted, but not measured. For example, the number of students in a class, the number of books in a library, or the number of phone calls that a call center receives in a day are all examples of discrete data.
Discrete data is different from continuous data, which can take any value within a range, and can be measured with precision. For example, the height of a person, the weight of a fruit, or the temperature of a room are all examples of continuous data. Therefore, the correct answer is D. References: [Discrete vs Continuous Data:
Definition and Examples - Statistics How To], [Discrete Data - Definition and Examples | Math Goodies]

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Explanation
Mean and mode are measures of central tendency, which describe the typical or most common value in a distribution of data. Mean is the arithmetic average of all the values in a dataset, calculated by adding up all the values and dividing by the number of values. Mode is the most frequently occurring value in a dataset.
Other measures of central tendency include median, which is the middle value when the data is sorted in ascending or descending order.