# SKEW

The SKEW function calculates the skewness of a distribution based on a sample of data. Skewness measures the asymmetry of the distribution in a dataset.

## Syntax ðŸ”—

=SKEW(`number1`, [`number2`, ...])

When you're exploring data sets and seeking insights into the shape and symmetry of distributions, the SKEW function in Excel serves as a valuable tool. Skewness, a crucial statistical metric, allows you to evaluate the asymmetry present in a dataset's distribution. By harnessing the power of the SKEW function, you can assess whether the data is symmetrically distributed or exhibits skew towards one end of the range, aiding in making informed analytical decisions in fields such as finance, economics, and research analysis. The function provides a quantitative measure of skewness, indicating the degree and direction of asymmetry within the data sample, essential for thorough data analysis in Excel.

## Examples ðŸ”—

Suppose you have a dataset of sample returns from an investment portfolio. To calculate the skewness of the returns, you can use the SKEW function. If the returns are stored in cells A1 to A10, the formula would be: =SKEW(A1:A10)

Consider a set of exam scores represented by the values 85, 78, 92, 80, 70, and 95. To determine the skewness of these scores, you can use the SKEW function with the values directly input in the formula: =SKEW(85, 78, 92, 80, 70, 95)

## Notes ðŸ”—

Ensure that the dataset you provide as arguments to the SKEW function represents a valid sample of data for accurate skewness calculation. The SKEW function returns a positive value for a right-skewed distribution (tail to the right), a negative value for a left-skewed distribution (tail to the left), and zero for a perfectly symmetrical distribution.

## Questions ðŸ”—

What does the skewness value calculated by the SKEW function indicate?

The skewness value obtained from the SKEW function denotes the degree and direction of skewness within the dataset. A positive skewness value indicates a right-skewed distribution, a negative value signifies a left-skewed distribution, while a value close to zero suggests a symmetric distribution.

Can I use the SKEW function with a dataset containing text or non-numeric values?

No, the SKEW function requires numerical data inputs to compute skewness accurately. Ensure that the dataset provided to the SKEW function consists of valid numeric values for correct skewness assessment.

How can the skewness calculated by the SKEW function influence data analysis?

Understanding the skewness of a dataset through the SKEW function aids in identifying patterns and deviations from normal distributions. It is instrumental in various analytical contexts such as risk assessment, performance evaluation, and trend analysis, providing valuable insights into the data's distribution shape and symmetry.