QlikView Skewness: Analyzing Data Symmetry for Accurate Insights

Skewness: A measure of the symmetry of a distribution. It is a statistic that describes the degree to which a distribution is asymmetrical, or “skewed,” relative to a normal distribution. Positive skewness indicates that the distribution has a long tail on the right side, and negative skewness indicates that it has a long tail on the left side.

In QlikView, you can calculate skewness using the Skewness() function. This function takes a field or expression as an argument and returns the skewness of the distribution of values in that field or expression.

For example, to calculate the skewness of the “Sales” field in a data set, you could use the following expression:

Skewness(Sales)

You can also use the Skewness() function in combination with other functions or expressions, such as to calculate the skewness of a subset of data or to compare the skewness of different fields.

The function will return a value that represents the skewness of the data set. A value of 0 indicates that the data is symmetric and has no skewness. A value greater than 0 indicates that the data is positively skewed, meaning, the tail on right side of distribution is longer or fatter than the tail on the left side. A value less than 0 indicates that the data is negatively skewed, meaning that the tail on left side of distribution is either longer or fatter than the tail on the right side.

Skewness can be visualized by different charts such as boxplot, histogram, density plot, etc.

It’s important to note that skewness is sensitive to outliers, so it’s essential to check for outliers in your data set before calculating the skewness.

Overall, skewness is a statistical measure that allows you to understand the symmetry or asymmetry of a data set in QlikView, providing insights into the distribution of the data and helping you make better data-driven decisions.