Using the textbook, explain the difference between probability and nonprobability sampling. Give an example of when you would use each approach.
a) Probability sampling refers to a sampling technique in which every member of the population has a known chance of being included in the sample. This method is used when researchers want to ensure that their sample is representative of the population. An example of when to use probability sampling is in a study measuring the average income of households in a city, where each household has an equal chance of being included in the sample.

b) Nonprobability sampling, on the other hand, does not rely on random selection and therefore does not guarantee that every member of the population has an equal chance of being included in the sample. This method is used when it is difficult or impossible to access a complete list of the population. An example of when to use nonprobability sampling is in a study of homeless individuals in a city, where it is not possible to create a complete list of the population and a convenience sample must be used instead.

c) Another difference between probability and nonprobability sampling is that probability sampling allows researchers to calculate the likelihood of a particular result occurring within a certain range, while nonprobability sampling does not allow for this calculation.

d) In summary, the main difference between probability and nonprobability sampling is the level of randomness and the ability to generalize results to the entire population. Each approach has its own uses depending on the research goals and the characteristics of the population being studied.