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What Is Data Interpretation?

Data interpretation is the analysis of scientific measurements and observations to develop evidence for answering a question, according to VisionLearning.com. Weather forecasts, for instance, are the end result of data interpretation, according to the site.

  1. Spreadsheets

    • Electronic spreadsheets are often used as a tool for data interpretation, according to the University of Wisconsin-Eau Claire. These spreadsheets can sort, graph and search data.

    Qualitative Data

    • Qualitative data can be more time-consuming to interpret than quantitative data, according to the University of Wisconsin. Researchers must actively look for contradictions, get many perspectives and collect different kinds of data to avoid bias.

    Descriptive Statistics

    • Descriptive statistics may help with the interpretation of data. They can describe the ways data relate to each other, such as their median, deviation and variation.

    Inferential Statistics

    • Inferential statistics let researchers make inferences about populations of data based on smaller populations. This may involve using the population's mean or standard deviation to test hypotheses.

    Consideration

    • Absolute honesty is imperative to getting accurate results from your data interpretation, according to the University of Wisconsin.

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