1. What Are Skewness And Kurtosis?

Skewness and kurtosis are statistical measures that describe the shape of a probability distribution. Skewness measures the asymmetry of the distribution, while kurtosis measures the "tailedness" or peakedness of the distribution.

2. SPSS Descriptive Statistics Command

The SPSS command for calculating descriptive statistics including skewness and kurtosis:

Command Components:

• DESCRIPTIVES - Main command for descriptive statistics
• /STATISTICS= - Specifies which statistics to calculate
• MEAN - Arithmetic average of the data
• STDDEV - Standard deviation, measure of dispersion
• SKEWNESS - Measure of distribution asymmetry (dimensionless)
• KURTOSIS - Measure of distribution tailedness (dimensionless)

3. Interpreting Skewness And Kurtosis Values

Skewness Interpretation:

• 0 = Perfectly symmetrical distribution
• Positive value = Right-skewed (tail extends to right)
• Negative value = Left-skewed (tail extends to left)
• Values between -0.5 and 0.5 = Approximately symmetrical

Kurtosis Interpretation:

• 0 = Mesokurtic (normal distribution peakedness)
• Positive value = Leptokurtic (sharper peak, heavier tails)
• Negative value = Platykurtic (flatter peak, lighter tails)

4. Using The SPSS Command Generator

Instructions: Enter your dataset name, list the variables you want to analyze (separated by spaces), and select the statistics you need. The generator will create the appropriate SPSS syntax.

5. Frequently Asked Questions (FAQ)

Q1: What is considered a normal range for skewness and kurtosis?
A: For most statistical analyses, skewness values between -2 and +2 and kurtosis values between -7 and +7 are generally acceptable for assuming normal distribution.

Q2: Can I calculate skewness and kurtosis for categorical variables?
A: No, skewness and kurtosis are only meaningful for continuous, interval, or ratio scale variables.

Q3: What if my data shows significant skewness or kurtosis?
A: Consider data transformations (log, square root) or use non-parametric statistical tests that don't assume normality.

Q4: Are there alternative SPSS procedures for these statistics?
A: Yes, you can also use FREQUENCIES or EXAMINE procedures with appropriate statistics options.

Q5: How do I interpret negative kurtosis values?
A: Negative kurtosis indicates a flatter distribution with lighter tails than a normal distribution, suggesting fewer extreme values.