The data that UCPs are designed to provide for is reliable, valid, comparable, and objective.
Reliable data is trusted data that can be used without doubt. Replicable data is data that is allowed to be copied or can be duplicated.
Specific data is always going to be more reliable than general data. The reason for this, is because people can answer more accurately, without giving a broad answer to a question.
Validity refers to the accuracy of a measure in assessing what it intends to measure, while reliability refers to the consistency of the measure. Establishing validity involves multiple factors such as construct validity, content validity, and criterion validity, making it more complex than evaluating reliability. It requires more evidence and validation processes to ensure that the measure is actually measuring what it is supposed to.
Hi, data provides evidence to back up your claim. Without evidence, your claim is not reliable.
yes it can store data without being asking for saving
GIGO stands for "Garbage In, Garbage Out." This concept is important in computing, as it refers to the idea that data that is input into a computer system must be valid and accurate in order to produce accurate results. If bad data is entered, the output will be incorrect. In short, the quality of the output is only as good as the quality of the input. Therefore, it is important to ensure that the data that is being entered into a computer system is valid and accurate in order to produce reliable results.
what are three features of reliable data?
It is data you can trust
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So they can be sure that the data they are releasing to the rest of the scientific community and world is actually correct.
A conclusion or assertion would be considered to be scientifically valid if the data are accurate and the reasoning based on that data is, as far as we can tell, correctly reasoned. Science does not deal in absolute truth, which is why scientists prefer the term valid, which indicates that as far as we presently know, this statement is true, although new data and/or new reasoning may cause us to change our minds in the future.