Many reasons. See Wikipedia under outliers: Outliers can have many anomalous causes. A physical apparatus for taking measurements may have suffered a transient malfunction. There may have been an error in data transmission or transcription. A sample may have been contaminated with elements from outside the population being examined. Alternatively, an outlier could be the result of a flaw in the assumed theory, calling for further investigation by the researcher. According to Wikipedia, an outlier in statistics is a number that is numerically distant to other numbers. Thus, it is not necessarily an incorrect data point, but one that requires extra scrutiny. A value that is observed and noted manually, can often be incorrectly recorded. As stated above, a transcription error creates an outlier.
An outlier is an outlying observation that appears to deviate markedly from the other members of a given sample. Outliers can occur by chance.
Outlier: an observation that is very different from the rest of the data.How does this affect the data: outliers affect data because it means that your calculations might be off which makes it a possibility that more than the outlier is off.
Depends on whether the outlier was too small or too large. If the outlier was too small, the mean without the outlier would be larger. Conversely, if the outlier was too large, the mean without the outlier would be smaller.
Calculate the mean, median, and range with the outlier, and then again without the outlier. Then find the difference. Mode will be unaffected by an outlier.
1,2,3,4,20 20 is the outlier range
An outlier is an outlying observation that appears to deviate markedly from the other members of a given sample. Outliers can occur by chance.
Outlier: an observation that is very different from the rest of the data.How does this affect the data: outliers affect data because it means that your calculations might be off which makes it a possibility that more than the outlier is off.
No, median is not an outlier.
0s are not the outlier values
Depends on whether the outlier was too small or too large. If the outlier was too small, the mean without the outlier would be larger. Conversely, if the outlier was too large, the mean without the outlier would be smaller.
No. A single observation can never be an outlier.
The answer depends on the nature of the outlier. Removing a very small outlier will increase the mean while removing a large outlier will reduce the mean.
Calculate the mean, median, and range with the outlier, and then again without the outlier. Then find the difference. Mode will be unaffected by an outlier.
The outlier is 558286.
1,2,3,4,20 20 is the outlier range
there is no outlier because there isn't a data set to go along with it. so theres no outlier
Yes, it will. An outlier is a data point that lies outside the normal range of data. This means that if it is factored in the mean will move in the direction the outlier is, really high if the outlier was high, and really low if the outlier was low.