1. What is Pearson's Method of Skewness?

Pearson's method of skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. It indicates whether the data is skewed to the left or right.

2. How Does the Calculator Work?

The calculator uses Pearson's first skewness coefficient formula:

Where:

• Mean — The average of the data set
• Mode — The most frequently occurring value
• Standard Deviation — Measure of data dispersion

Explanation: The formula compares the mean and mode relative to the spread of the data (standard deviation).

3. Interpretation of Skewness Values

Details:

• Skewness = 0: Symmetrical distribution
• Skewness > 0: Right-skewed (positive skew)
• Skewness < 0: Left-skewed (negative skew)

4. Using the Calculator

Tips: Enter the mean, mode, and standard deviation values. Standard deviation must be greater than zero.

5. Frequently Asked Questions (FAQ)

Q1: When should I use Pearson's skewness measure?
A: Use it when you have unimodal distributions and want a simple measure of skewness based on central tendency.

Q2: What are the limitations of this method?
A: It requires knowing the mode, which may not be clearly defined for some distributions. Not as robust as moment-based skewness for multimodal distributions.

Q3: What's considered a "significant" skewness value?
A: Generally, values beyond ±0.5 indicate moderate skewness, and beyond ±1.0 indicate strong skewness.

Q4: How does this compare to other skewness measures?
A: Pearson's first coefficient is simpler but less commonly used than the third-moment skewness coefficient in modern statistics.

Q5: Can skewness be calculated for any data set?
A: The data should be continuous and reasonably large (n > 30) for reliable skewness measurement.