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Here is a specific example to illustrate the difference:

• Discrete random variable: The number of cars that pass by a certain point on a highway in a minute. This is a discrete random variable because it can only take on a finite number of values, such as 0, 1, 2, 3, etc.
• Continuous random variable: The amount of time it takes for a customer to checkout at a grocery store. This is a continuous random variable because it can take on any value within a certain range, such as 1 minute, 2 minutes, 3 minutes, etc.

Here is a scenario when I might use one type of random sampling method in my industry:

• Industry: I work as a data scientist for a company that sells shoes.
• Scenario: I want to estimate the average height of my company’s customers.
• Random sampling method: I would use a simple random sample. This is a method of sampling where every member of the population has an equal chance of being selected.
• Reason for choosing this method: I would choose this method because it is a simple and unbiased way to select a sample. It is also easy to implement and does not require any special equipment.

I would choose this method even if another random sampling method could be used, such as a stratified random sample or a systematic random sample. This is because I believe that a simple random sample is the most unbiased way to select a sample.