Quantitative Research Methods

Descriptive Statistics

Summarize. Organize. Simplify.

Gain a clear overview of patterns and trends before conducting inferential analysis.

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.

Mode

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

Normal Distribution

SPSS Output Example

Analyze > Descriptive Statistics > Descriptives

Metric Statistic
N120
Minimum18.00
Maximum65.00
Mean34.52
Std. Deviation5.21

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).