Validity of Data

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When obtaining data, it is important to check the validity of your dataset, or in other words, ensuring your data are of high quality so you can move on to the explore and analyze phase. 

Here is a checklist you can use to ensure the validity of your data 

Source credibility:

⏹ Authorship: Is the data provided by a reputable author or organization? What are the credentials of the author or organization?

⏹ Publication date: Is the data current and up-to-date?

Methodology:

⏹ Sample size: Was the data collected from a large enough sample?

⏹ Sampling method: Was the sampling method unbiased and representative?

⏹ Data collection: Were the data collection methods clearly described and appropriate?

Objectivity:

⏹ Bias: Are there any apparent biases in the data or its presentation?

⏹ Conflicts of interest: Are there any potential conflicts of interest that could influence the data?

Accuracy:

⏹ Consistency: Are the data consistent with other reputable sources?

⏹ Error rate: Are there any obvious errors or inconsistencies in the data?

Relevance:

⏹ Scope: Is the data relevant to the research question or topic?

⏹ Context: Is the data presented within a meaningful context?

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