Suppose You Want to Draw a Probability Sample of All

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The Answer is To draw a probability sample of all U.S. intercollegiate athletes competing during the current academic year, we can use different probability sampling designs such as simple random sampling, stratified random sampling, and multistage cluster sampling.

Simple random sampling involves selecting a random sample from the entire population of U.S. intercollegiate athletes. This can be done by assigning a unique identifier to each athlete and using a random number generator to select a sample of athletes.

Stratified random sampling involves dividing the population of athletes into different strata or groups based on certain characteristics such as sport, gender, or division level. Then, a random sample is selected from each stratum to ensure representation from each subgroup.

Multistage cluster sampling involves dividing the population into clusters, such as colleges or universities, and then randomly selecting a sample of clusters. Within each selected cluster, a random sample of athletes is then chosen.

In this case, the best sampling design to use would likely be stratified random sampling. This is because intercollegiate athletes can vary widely in terms of sport, gender, and division level, and using stratified random sampling would ensure that the sample is representative of the entire population of athletes. It would also allow for comparisons to be made between different subgroups of athletes, providing a more comprehensive understanding of the population.

Suppose You Want to Draw a Probability Sample of All

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