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Mindmap: Garbage in, Garbage out | Class 6 to 12 NCERT Mindmaps for UPSC Preparation PDF Download
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FAQs on Mindmap: Garbage in, Garbage out - Class 6 to 12 NCERT Mindmaps for UPSC Preparation
| 1. What is the meaning of "garbage in, garbage out"? |  |
| 2. How does the principle of "garbage in, garbage out" apply to data analysis? | |
Ans. In data analysis, the principle of "garbage in, garbage out" emphasizes the importance of ensuring the quality and accuracy of input data. If the input data is flawed, incomplete, or incorrect, it will lead to unreliable and misleading analysis results.
| 3. What are the consequences of ignoring the principle of "garbage in, garbage out" in decision making? | |
Ans. Ignoring the principle of "garbage in, garbage out" in decision making can have significant negative consequences. It can lead to making decisions based on flawed or unreliable information, resulting in poor outcomes, financial losses, missed opportunities, and damaged reputation.
| 4. How can we ensure that we don't fall into the trap of "garbage in, garbage out" in data-driven decision making? | |
Ans. To avoid falling into the trap of "garbage in, garbage out" in data-driven decision making, it is crucial to implement data quality assurance measures. This includes verifying the accuracy and reliability of the input data, performing data cleansing and validation, and regularly monitoring and updating the data sources.
| 5. What are some practical tips for improving data quality and minimizing the risk of "garbage in, garbage out"? | |
Ans. Some practical tips for improving data quality and minimizing the risk of "garbage in, garbage out" include implementing data governance practices, using standardized data collection methods, conducting regular data audits, investing in data quality tools and technologies, and providing training and awareness programs for data users and stakeholders.
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