Stratified random sampling is a data analysis technique that involves dividing a population into different groups or strata, and then taking a random sample from each in proportion to the strata's size in relation to the population. Doing so produces a more representative group for the variable being studied. Insurance companies use this technique to better estimate expected loss and thereby determine premiums for their policies.
For example, suppose an automobile insurance company wants to determine the average number of car accidents male high school seniors in Maryland experience. Selecting samples from various high schools throughout the state based on the principles of stratified random sampling would provide a more accurate estimate and thereby a premium more reflective of the risk.
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