##### Asked by: Ghania Albersen

asked in category: General Last Updated: 24th March, 2020# How does outlier affect mean?

**Outlier**An extreme value in a set of data which is much higher or lower than the other numbers.

**Outliers affect**the

**mean**value of the data but have little

**effect**on the

**median**or mode of a given set of data.

In this regard, why does an outlier affect the mean?

An **outlier** can **affect the mean** of a data set by skewing the results so that the **mean** is no longer representative of the data set.

Subsequently, question is, what impact would an outlier have? An **outlier** is a value that is very different from the other data in your data set. This can skew your results. As you can see, having **outliers** often **has** a significant **effect** on your mean and standard deviation. Because of this, we must take steps to remove **outliers** from our data sets.

Similarly, how do outliers affect the mean and standard deviation?

A single **outlier** can raise the **standard deviation** and in turn, distort the picture of spread. For data with approximately the same **mean**, the greater the spread, the greater the **standard deviation**. If all values of a data set are the same, the **standard deviation** is zero (because each value is equal to the **mean**).

Why is the mean more sensitive to outliers?

**Outliers** are extreme, or atypical data value(s) that are notably different from the rest of the data. It is important to detect **outliers** within a distribution, because they can alter the results of the data analysis. The **mean** is **more sensitive** to the existence of **outliers** than the median or mode.