Search results
Results From The WOW.Com Content Network
Wired, The New York Times, and The Observer reported that the data-set had included information on 50 million Facebook users. [35] [36] While Cambridge Analytica claimed it had only collected 30 million Facebook user profiles, [37] Facebook later confirmed that it actually had data on potentially over 87 million users, [38] with 70.6 million of those people from the United States. [39]
An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...
For example, if one collects some data, applies several different significance tests to it, and publishes only the one that happens to have a p-value less than 0.05, then the total p-value for "at least one significance test reaches p < 0.05" can be much larger than 0.05, because even if the null hypothesis were true, the probability that one ...
Data Quality (DQ) is a niche area required for the integrity of the data management by covering gaps of data issues. This is one of the key functions that aid data governance by monitoring data to find exceptions undiscovered by current data management operations.
A data breach, also known as data leakage, is "the unauthorized exposure, disclosure, or loss of personal information". [ 1 ] Attackers have a variety of motives, from financial gain to political activism , political repression , and espionage .
Data manipulation is a serious issue/consideration in the most honest of statistical analyses. Outliers, missing data and non-normality can all adversely affect the validity of statistical analysis. It is appropriate to study the data and repair real problems before analysis begins.
Dirty data, also known as rogue data, [1] are inaccurate, incomplete or inconsistent data, especially in a computer system or database. [ 2 ] Dirty data can contain such mistakes as spelling or punctuation errors, incorrect data associated with a field, incomplete or outdated data, or even data that has been duplicated in the database.
A Lancet review on Handling of Scientific Misconduct in Scandinavian countries gave examples of policy definitions. In Denmark, scientific misconduct is defined as "intention[al] negligence leading to fabrication of the scientific message or a false credit or emphasis given to a scientist", and in Sweden as "intention[al] distortion of the ...