How Does the Analysis of Existing Data Differ from Experiments

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The Answer is Analysis of existing data, experiments, and surveys are three distinct research methodologies used in various fields to gather and analyze information. Each method has its own characteristics in terms of units of analysis and reactive measurement.

(a) Units of Analysis:

- Analysis of Existing Data: The units of analysis in existing data are determined by the nature of the data that was previously collected. This data could have been collected for different purposes and might include individuals, groups, organizations, countries, or any other defined units. Researchers using existing data must work within the constraints of the data, which means they may not have control over how or what units were analyzed in the original data collection process.

- Experiments: In experiments, the units of analysis are typically individual subjects (human or animal) or groups that are deliberately manipulated by the researcher. The researcher assigns subjects to different conditions in a controlled environment to observe the effects of the manipulation. The units of analysis are chosen to match the research question and are often homogenous to ensure that the observed effects are due to the experimental manipulation and not other variables.

- Surveys: In surveys, the units of analysis are usually individuals, households, or sometimes organizations, depending on the survey's focus. Researchers design survey instruments to collect data directly from these units through questions and responses. The units of analysis in surveys are selected to represent a larger population, allowing for generalization of the findings.

(b) Reactive Measurement:

- Analysis of Existing Data: Reactive measurement is typically not a concern when analyzing existing data because the data has already been collected, often for purposes other than the current research question. The subjects of the data were not influenced by the research process itself, which means their behavior was not altered in response to being studied.

- Experiments: Reactive measurement can be a significant issue in experiments. Subjects may change their behavior because they are aware that they are being studied, a phenomenon known as the Hawthorne effect. Researchers must design experiments carefully to minimize these reactive effects, such as using control groups, blind or double-blind procedures, and ensuring that subjects are not aware of the specific hypotheses being tested.

- Surveys: Surveys can also be susceptible to reactive measurement. Respondents may provide socially desirable answers, try to guess the purpose of the survey, or alter their responses based on how they perceive the survey or the researcher. To reduce these effects, survey designers can use techniques such as ensuring anonymity, framing questions neutrally, and using validated questionnaires.

In summary, the analysis of existing data, experiments, and surveys each have distinct approaches to units of analysis and reactive measurement. Existing data analysis is constrained by the nature of the data, experiments control and manipulate the units of analysis in a controlled setting, and surveys collect data directly from a sample of the population. Reactive measurement is a concern primarily in experiments and surveys, where the awareness of being studied can influence the responses or behavior of the subjects.

How Does the Analysis of Existing Data Differ from Experiments

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