Outliers or extreme values can sometimes indicate invalid data. These values that lie far outside the normal range could signal a technical issue, or a problem with the collection or extraction of the data.
D. Invalid data type is the BEST description for the issue in which character values are mixed with integer values in a data set column. In this case, the data set column has a mix of two different data types - character values (e.g. text or string) and integer values (whole numbers). This is considered invalid as a data set column should have a consistent data type for all values in the column.
When character values are mixed with integer values, it can cause problems during data analysis and processing, as the software may not know how to handle these mixed values. For example, if the analyst tries to perform mathematical operations on the column, the software may produce an error or incorrect results, as it does not know how to handle the character values.
Therefore, it is important to ensure that all data types in a data set column are consistent, in order to avoid problems during data analysis and processing. The issue of invalid data types can often be resolved by converting the values to a consistent data type, such as converting character values to integer values, or vice versa.
D. Invalid data type
If a data set column contains character values mixed with integer values, it would be considered to have an invalid data type. A data type refers to the type of information that a column can contain, such as numbers, text, or dates. Mixing character values with integer values in the same column would be considered invalid because it violates the expected data type for the column. The other options (duplicate data, missing data, and data outliers) are not related to the data type of the values in the column.
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