Question

In: Statistics and Probability

Suppose you want to determine the best time and day for classes for Harvard university students....

Suppose you want to determine the best time and day for classes for Harvard university students.

-What is the population of interest?

-What are the individuals?

-What variables are you interested in and what type are they?

-What are the data types?

-Consider the pros and cons of each available sampling method

Solutions

Expert Solution

- Students of Harvard University is the population of interest

- Individuals are students

- Day and Time are the variables of interest. They are interval variables

- They belong to Date data type which are a type of interval variables

- In a statistical study, sampling methods refer to how we select members from the population to be in the study. Multiple sampling methods are available. Some of them are:

  1. Convenience sample: The researcher chooses a sample that is readily available in some non-random way.
    • Pros: Easy to use
    • Cons: it could be biased
  2. Voluntary response sample: The researcher puts out a request for members of a population to join the sample, and people decide whether or not to be in the sample
    • Pros: Easy to use
    • Cons: it could be biased because the people who choose to respond might have a similar opinion about the questions
  3. Simple random sample: Every member and set of members has an equal chance of being included in the sample. Technology, random number generators, or some other sort of chance process is needed to get a simple random sample.
    • Pros: They are fairly representative
    • Cons: Difficult to execute
  4. Stratified random sample: The population is first split into groups. The overall sample consists of some members from every group. The members from each group are chosen randomly.
    • Pros: A stratified sample guarantees that members from each group will be represented in the sample
    • Cons: Difficult to choose the groups
  5. Systematic random sample: Members of the population are put in some order. A starting point is selected at random, and every nth member is selected to be in the sample.
    • Pros: Easy to execute and fairly representative

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