Search results
Results From The WOW.Com Content Network
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 research process by fabrication of data, text, hypothesis, or methods from another researcher's manuscript form or ...
Publication of studies on p-hacking and questionable research practices: Since the late 2000s, a number of studies in metascience showed how commonly adopted practices in many scientific fields, such as exploiting the flexibility of the process of data collection and reporting, could greatly increase the probability of false positive results.
Data editing is defined as the process involving the review and adjustment of collected survey data. [1] Data editing helps define guidelines that will reduce potential bias and ensure consistent estimates leading to a clear analysis of the data set by correct inconsistent data using the methods later in this article. [2]
Consilience does not forbid deviations: in fact, since not all experiments are perfect, some deviations from established knowledge are expected. However, when the convergence is strong enough, then new evidence inconsistent with the previous conclusion is not usually enough to outweigh that convergence.
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
Random errors are errors in measurement that lead to measurable values being inconsistent when repeated measurements of a constant attribute or quantity are taken. Random errors create measurement uncertainty. Systematic errors are errors that are not determined by chance but are introduced by repeatable processes inherent to the system. [3]
In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. [1]
The importance of point-in-time consistency can be illustrated with what would happen if a backup were made without it. Assume Wikipedia's database is a huge file, which has an important index located 20% of the way through, and saves article data at the 75% mark. Consider a scenario where an editor comes and creates a new article at the same time a backup is being performed, which is being ...