To determine if the student's sample of 15 ice samples from randomly selected coffee drinks is an appropriate, random sample and a good representation of the population, we need to evaluate two main aspects:
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Random Sampling: The student has chosen ice samples from randomly selected coffee drinks. If the selection process was truly random, meaning each drink had an equal chance of being selected without bias, then the sampling can be considered random. However, factors such as time of day, specific drinks chosen, or the method of selection could introduce bias. If she systematically avoids certain times or drinks, that could lead to an unrepresentative sample.
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Representation of the Population: The sample should ideally represent the broader population of ice at the coffee shop. To determine if the sample is a good representation, consider the following:
- Is the sample diverse in terms of different types of coffee drinks (e.g., cold brews, iced lattes, etc.)?
- Does the sample cover different times of day or different shifts (e.g., morning rush, afternoon, etc.) to account for variations in ice handling or cleanliness?
- Are there a sufficient number of samples (15 in this case) to allow for a reasonable degree of confidence in her findings?
In summary, if the student has ensured that her selection process is random and if the chosen samples represent a diverse cross-section of coffee drinks and ice handling practices at the coffee shop, then her sample can be considered both an appropriate, random sample and a good representation of the population. However, if there are biases in her selection or if the sample lacks diversity, it may not adequately represent the overall quality of ice at the coffee shop.