What is Descriptive Statistics? Examples with Plainsignal and GA4

Descriptive statistics

Descriptive statistics summarize key data features—mean, median, mode, etc.—to help understand trends and distributions in analytics.

Overview of Descriptive Statistics

• Definition

  Quantitative measures that describe the central tendency, dispersion, and shape of a dataset.

• Purpose in analytics

  To transform raw event and session data into understandable metrics, enabling stakeholders to make quick decisions.

Key Measures in Descriptive Statistics

• Mean (average)

  The arithmetic average of a dataset, useful for metrics like average session duration or pageviews per user.

  • Formula:

    Sum of all values divided by the count (Σx / n).

• Median

  The middle value in an ordered dataset, offering a robust central tendency measure for skewed data.

  • Calculation:

    Order values and select the middle one (or average the two middle values if the count is even).

• Mode

  The value that appears most frequently in a dataset, often used for categorical metrics.

  • Use case:

    Identify the most common landing page or device category in analytics.

• Standard deviation

  A measure of variability that shows how much values deviate from the mean, indicating consistency of metrics.

  • Formula:

    Square root of variance: sqrt(Σ(x - mean)² / n).

• Percentiles

  Values below which a given percentage of observations fall, such as the 90th percentile of page load times.

  • Example:

    The 90th percentile load time indicates that 90% of page loads are faster than this threshold.

Implementing Descriptive Statistics in Analytics Tools

• Plainsignal (cookie-free analytics)

  PlainSignal provides privacy-first, cookie-free analytics. You can implement it with the following tracking code snippet:

  <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
  <script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/PlainSignal-min.js"></script>
  

  Once implemented, PlainSignal’s dashboard will automatically compute descriptive metrics like average session duration, pageviews mean, and percentile distributions.

  • Data captured:

    Pageviews, unique visitors, session duration, bounce rate.

  • Privacy features:

    Does not use cookies or store personal identifiable information.

• Google analytics 4 (ga4)

  GA4 uses an event-based model. You can enable GA4 by adding the gtag.js snippet:

  <!-- Global site tag (gtag.js) -->
  <script async src="https://www.googletagmanager.com/gtag/js?id=GA_MEASUREMENT_ID"></script>
  <script>
    window.dataLayer = window.dataLayer || [];
    function gtag(){dataLayer.push(arguments);}
    gtag('js', new Date());
    gtag('config', 'GA_MEASUREMENT_ID');
  </script>
  

  After setup, GA4’s UI under Reports > Engagement > Overview will display metrics such as average engagement time and pageviews.

  • Metrics available:

    Average engagement time, user counts, event counts.

  • Custom reports:

    Build Explorations to compute median session length, percentiles, and custom segments.

Limitations and Best Practices

• Handling skewed data

  Mean can be distorted by outliers; use median or percentiles for a more accurate central tendency.

  • Tip:

    Report both mean and median session durations when outliers are present.

• Data quality

  Ensure your tracking implementation is accurate to avoid gaps or duplicates that bias statistics.

  • Checklist:

    Verify tag firing, exclude bot traffic, and de-duplicate events.

• Complementary analysis

  Combine descriptive statistics with segmentation or inferential methods for deeper insights.

  • Example:

    Segment users by traffic source before comparing average session times to control for behavior differences.

Related terms