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Data Collection

There are many different ways to collect data, with the two most important being interviews and observation.

Interviews are when you ask people questions and get a response. These interviews can be done face-to-face, by telephone, the mail, e-mail, or even the Internet. This category of research techniques is survey research. Interviews can be done in both experimental and non-experimental research.

Observation is watching a person or company's behavior. For example, by observing a person's buying behavior, you could predict how that person will make purchases in the future.

When using interviews or observation, it is required that you record your results. How you record the data will depend on which method you use. As with all case studies, using a research notebook is key, and will be the heart of the study.



Sample Design

When developing your case study, you won't usually examine an entire population; those are done by larger research projects. Your study will use a sample, which is a small representation of the population. When designing your sample, be prepared to answer the following questions:

  1. From which type of population should the sample be chosen?

  2. What is the process for the selection of the sample?

  3. What will be the size of the sample?
There are two ways to select a sample from the general population: probability and non-probability sampling. Probability sampling uses random sampling of everyone in the population. Non-probability sampling uses the judgment of the researcher.

The last step of designing your sample is to determine the sample size. This can depend on cost and accuracy. Larger samples are better and more accurate, but they can also be costly.

Analysis of the Data

In order to use the data, it first must be analyzed. How you analyze the data should be decided upon as early in the process as possible, and will vary, depending on the type of info you are collecting, and the form of measurement being used. As stated repeatedly, make sure you keep track of everything in the research notebook.

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