diff --git a/Document/content/tests/AITG-DAT-03_Testing_for_Dataset_Diversity_and_Coverage.md b/Document/content/tests/AITG-DAT-03_Testing_for_Dataset_Diversity_and_Coverage.md
index badfad0..55bcb3a 100644
--- a/Document/content/tests/AITG-DAT-03_Testing_for_Dataset_Diversity_and_Coverage.md
+++ b/Document/content/tests/AITG-DAT-03_Testing_for_Dataset_Diversity_and_Coverage.md
@@ -15,18 +15,18 @@ Dataset Diversity & Coverage testing ensures that AI training and evaluation dat
 
 **1. Demographic and Population Representation Analysis**
 
-Test: Conduct statistical analyses to compare dataset demographic distribution with real-world demographics.
-Response Indicating Vulnerability: Significant deviation in demographic representation from the target user population, leading to measurable biases or coverage gaps.
+- Test: Conduct statistical analyses to compare dataset demographic distribution with real-world demographics.
+- Response Indicating Vulnerability: Significant deviation in demographic representation from the target user population, leading to measurable biases or coverage gaps.
 
 **2. Scenario and Contextual Coverage Test**
 
-Test: Evaluate the dataset for completeness and variety of real-world scenarios relevant to the model’s intended usage.
-Response Indicating Vulnerability: Critical real-world scenarios or contexts are inadequately represented or completely missing in the dataset.
+- Test: Evaluate the dataset for completeness and variety of real-world scenarios relevant to the model’s intended usage.
+- Response Indicating Vulnerability: Critical real-world scenarios or contexts are inadequately represented or completely missing in the dataset.
 
 **3. Bias Detection and Fairness Analysis**
 
-Test: Utilize bias detection tools and fairness metrics (e.g., demographic parity, equal opportunity) on datasets.
-Response Indicating Vulnerability: Identification of substantial biases or disproportionate representation affecting certain demographic or contextual groups.
+- Test: Utilize bias detection tools and fairness metrics (e.g., demographic parity, equal opportunity) on datasets.
+- Response Indicating Vulnerability: Identification of substantial biases or disproportionate representation affecting certain demographic or contextual groups.
 
 ### Expected Output