Data may be unreliable due to issues such as bias in data collection methods, where certain groups are overrepresented or underrepresented, leading to skewed results. Additionally, errors in data entry or processing can introduce inaccuracies, while outdated information can fail to reflect current trends or conditions. Lastly, a lack of transparency in the methodology used to gather the data can raise questions about its validity and reliability.
The reason for organizing, analyzing and classifying data is find out the data relates. The relationship between the elements of a data will form the basis of the information.
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To integrate has two separate meanings. It might mean simply that different sets of data are put together. It can also refer to a mathematical process which is part of the calculus.
One reason I can think of why you might not be able to find the mean of numerical data would be if there were missing data points.
Lost data can not be regained. There may be techniques to infer the missing data from the rest of that data but it would be domain specific and you may not be able to derive meaningful statistics from such a data set.
Unreliable means not guaranteed. In term of data communication unreliable stands when the delivery of data is unacknowledged.
Scientific data that has not been experimentally tested is unreliable.
cell phone data lagging
It is better than keeping unreliable data!
tcp/ip
The source is the main thing that makes data unreliable. For example: I asked Dave and Jack to get me the population of a town; Dave gets 300,000 and Jack gets 251,000. They both went to different sources and got different results.
Then the component will not work or will be unreliable.
100m or 328ft.
There is no reason for volume to be any less reliable than any other measurement.
Of course not. Errors do happen. Sometimes errors are unintended and could be related to equipment that is faulty or incorrectly calibrated. Sometimes data are intentionally tampered with. There are lots of other reasons why data may be considered unreliable. Honesty, well thought out controls and adequate oversight are ways to minimize problems with unreliable data.
why the magnet change the data from diskette?state the reason.
Cash flow forecasts may be unreliable due to factors such as inaccurate assumptions about future sales, expenses, and economic conditions. Unexpected events, such as changes in consumer demand, supply chain disruptions, or economic downturns, can significantly impact actual cash flows. Additionally, reliance on historical data without considering current market trends can lead to outdated projections. Finally, human error in data entry or analysis can further compromise the accuracy of forecasts.