diff --git a/src/data/roadmaps/data-analyst/content/108-descriptive-analysis/101-dispersion/index.md b/src/data/roadmaps/data-analyst/content/108-descriptive-analysis/101-dispersion/index.md
index 654473af3..866cdcc59 100644
--- a/src/data/roadmaps/data-analyst/content/108-descriptive-analysis/101-dispersion/index.md
+++ b/src/data/roadmaps/data-analyst/content/108-descriptive-analysis/101-dispersion/index.md
@@ -1,3 +1,7 @@
 # Dispersion 
 
-Dispersion in descriptive analysis, specifically for a data analyst, offers a crucial way to understand the variability or spread in a set of data. Descriptive analysis focus on describing and summarizing data to find patterns, relationships, or trends. Distinct measures of dispersion such as range, variance, standard deviation, and interquartile range gives data analysts insight into how spread out data points are, and how reliable any patterns detected may be. This understanding of dispersion helps data analysts in identifying outliers, drawing meaningful conclusions, and making informed predictions.
\ No newline at end of file
+Dispersion in descriptive analysis, specifically for a data analyst, offers a crucial way to understand the variability or spread in a set of data. Descriptive analysis focus on describing and summarizing data to find patterns, relationships, or trends. Distinct measures of dispersion such as range, variance, standard deviation, and interquartile range gives data analysts insight into how spread out data points are, and how reliable any patterns detected may be. This understanding of dispersion helps data analysts in identifying outliers, drawing meaningful conclusions, and making informed predictions.
+
+Visit the following resources to learn more:
+
+- [@article@Standard Deviation and Variance](https://www.mathsisfun.com/data/standard-deviation.html)