if the oulier is REALLY high, the mean gets higher if the outlier is REALLY low, the mean gets lower
cause is how it happened an effect is the result
It literally means The distancing effect
Do you mean Impinging - if so it means to encroach or infringe or to make an impression or an effect
(The verb effect is only used to mean "make a change." Otherwise use "affect".)"The treatment may effect a modification in his behavior.""The law is designed to effect a major change in land use."
It means that the effect is a particular case. This answer has been confirmed.
Outliers pull the mean in the direction of the outlier.
the mean is affected by outliers
Mean.
just cuz
Yes.
Yes, the mean is generally a better measure of central tendency when there are no outliers, as it takes into account all values in the dataset and provides a mathematically precise average. In the absence of outliers, the mean reflects the true center of the data distribution effectively. However, in the presence of outliers, the median might be preferred since it is less affected by extreme values.
The mean is better than the median when there are outliers.
mean
there are no limits to outliers there are no limits to outliers
Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)
They are observations with a low likelihood of occurrence. They may be called outliers but there is no agreed definition for outliers.
The mean is the least resistant to outliers because it is influenced by every value in the dataset, including extreme values. In contrast, the median, which represents the middle value, is less affected by outliers, as it depends only on the order of the data. The mode, being the most frequently occurring value, is also generally unaffected by outliers. Thus, in terms of sensitivity to extreme values, the mean is the most vulnerable.