Answer:
True.
In the data set 19, 8, 7, 5, 4, 9, 2, 5, 8, 6, the value 19 is an outlier. An outlier is a data point that is significantly different from the rest of the data points in a set. In this case, the value 19 is much higher than the other values in the set. This could be due to a number of factors, such as a data entry error or a genuine outlier.
There are a number of ways to identify outliers. One common method is to use the interquartile range (IQR). The IQR is the difference between the third and first quartiles of a data set. A data point that is more than 1.5 times the IQR above the third quartile or below the first quartile is considered to be an outlier.
In this case, the value 19 is more than 1.5 times the IQR above the third quartile. Therefore, it is considered to be an outlier.
Outliers can be removed from a data set, or they can be left in. Removing outliers can sometimes improve the accuracy of statistical analysis, but it is important to be careful not to remove too many data points. Leaving outliers in can sometimes make the data set more difficult to analyze, but it can also provide useful information about the data.
Explanation: