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Dr. Shelley, Greetings. I really enjoyed your graph depicting whether we can trust data and what to do with that information. I believe your intent is to go from left to right. Starting with raw data "was the data created in accordance with a first[-rate data quality program"? That's key whether you should use that as a viable resource in any studies or data analysis. Its pivotal to understand the source of the data is it reputable and well-established organization or individual? Has the data collected using reliable methods, such as surveys, sensors, or established data collection processes. When we think data collection processes have to assess the methodology used for data collection. Were proper sampling techniques employed? Its also vital to check for any biases in the data collection process, as they can lean to skewed results. The next thing to evaluate is data quality and consistency have to examine data for completeness, accuracy, and consistency. Are there missing values, outliers, or errors? Does it adhere to standardized formats and units of measurement. I suppose all this would tie in where you stated "no" is it in accordance with first-rate data quality program if not can you identify data of high quality through your own research? You stated "scrub" a small sample by correcting or eliminating data. Other things that may need to be considered from data quality and consistency is data documentation, verification, governance & security, and transparency. Are there comprehensive documentation that accompanies the data such as metadata, dictionaries, and other variables. Cross-reference of data with other trusted sources or existing datasets to identify discrepancies is important. Data governance and security need to check if data has undergone security measures to protect against unauthorized access or tampering. These I would think are key aspects when we think is data trust worthy if not what are other factors that can support it? Thank you. ~Jessica
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