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Individuals will know when they have enough data once the right questions have been asked, an unbiased audience and interviewer has completed the process, and results reflect little to no error. Hamlett (2018) states, “by appropriately addressing research questions, we can differentiate between the validity and reliability of a research study.” Researching a topic isn’t about personal gain, it’s about contributing data with the usage of triangulation. Michael Berry stated, “testing the predictive model’s performance by incrementally adding more data can shed light on when enough is enough.” Determining the relationship between variables and plausibility when collecting data is crucial.
Never assume anything. When doing research or providing honest feedback, one must not favor one thing over another or think negatively about one. If this is the case, the individual is considered bias. Analyze power, the effect one variable has on another, and level where the hypothesis may be incorrect. To determine the significance of something, use statistics. Don’t leave anything to chance as it may result in an error. Consider the field of law. To convict someone or discredit a theory, evidence beyond a reasonable doubt must be provided.
Furthermore, the sample size used is important as well. The power will increase depending on the sample size. Data doesn’t need to be collected from thousands of people to obtain accurate results.
I know that I have had enough data when the number of individuals is greater than necessary, like 600, or when the results begin to yield too many possibilities. Accuracy is one of the most important aspects when it comes to gathering and producing information. If there is one point that is incorrect or a biased individual provided the data, it can change the results of the data collected. For example, if a person is being paid to write a review, they are likely to write a review that makes the company look good even if it was a terrible product.
Ethics is crucial when gathering data. The ethical considerations for accessing and safeguarding data are all significant. Allowing people to voluntarily participate in research without offering a reward provides for accurate and unbiased data. Participants should be well-informed, anonymous or provide consent to use their name or likeness, and be given information that adds to current knowledge. In addition, researchers should avoid plagiarism, providing false data, and mistreating participants. Overall, gathering data isn’t as simple as it sounds.
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