Purpose
Summarize Trends
Capture the central trends and general essence of the dataset effectively.
Describe Variability
Understand the distribution and how spread out or clustered the data points are.
Identify Issues
Spot outliers or data entry errors before moving to complex analysis.
Key Descriptive Measures
Switch tabs to explore different types of measures
The "Average"
Measures of central tendency indicate the most common or typical value in your dataset.
Mean (μ)
The mathematical average of all scores.
Median
The middle value when data is ordered.
Mode
The most frequently occurring value.
Tip: Use these to find the typical value.
Distribution Shape
Skewness
Indicates if data leans left (negative) or right (positive).
Kurtosis
Measures how peaked (Leptokurtic) or flat (Platykurtic) the distribution is.
Controls
SPSS Output Example
Analyze > Descriptive Statistics > Descriptives
Best Practices
- Check for Outliers: Always do this before interpreting results as they can skew the mean.
- Visualize: Use Histograms and Boxplots. Numbers alone can be misleading.
- Compare Groups: Look at group means if analyzing differences (e.g., Control vs. Experimental).