diff --git a/MLPP/Stat/Stat.cpp b/MLPP/Stat/Stat.cpp
index 5120e59..211e2b1 100644
--- a/MLPP/Stat/Stat.cpp
+++ b/MLPP/Stat/Stat.cpp
@@ -6,6 +6,9 @@
 
 #include "Stat.hpp"
 #include "Activation/Activation.hpp"
+#include "Data/Data.hpp"
+#include <algorithm>
+#include <map>
 #include <cmath>
 
 namespace MLPP{
@@ -25,6 +28,44 @@ namespace MLPP{
         return sum / x.size();
     }
 
+    double Stat::median(std::vector<double> x){
+        double center = double(x.size())/double(2); 
+        std::vector<double> original_vec = x;
+        sort(x.begin(), x.end());
+        if(x.size() % 2 == 0){
+            return mean({x[center - 1], x[center]});
+        }
+        else{
+            return x[center - 1 + 0.5];
+        }
+        x = original_vec;
+    }
+
+    std::vector<double> Stat::mode(std::vector<double> x){
+        Data data;
+        std::vector<double> x_set = data.vecToSet(x);
+        std::map<double, int> element_num;
+        for(int i = 0; i < x_set.size(); i++){
+            element_num[x[i]] = 0;
+        }
+        for(int i = 0; i < x.size(); i++){
+            element_num[x[i]]++;
+        }
+        std::vector<double> modes;
+        double max_num = element_num[x_set[0]];
+        for(int i = 0; i < x_set.size(); i++){
+            if(element_num[x_set[i]] > max_num){
+                max_num = element_num[x_set[i]];
+                modes.clear();
+                modes.push_back(x_set[i]);
+            }
+            else if(element_num[x_set[i]] == max_num){
+                modes.push_back(x_set[i]);
+            }
+        }
+        return modes;
+    }
+
     double Stat::variance(std::vector<double> x){
         double sum = 0;
         for(int i = 0; i < x.size(); i++){
diff --git a/MLPP/Stat/Stat.hpp b/MLPP/Stat/Stat.hpp
index 5997480..b1c01f8 100644
--- a/MLPP/Stat/Stat.hpp
+++ b/MLPP/Stat/Stat.hpp
@@ -18,6 +18,8 @@ namespace MLPP{
         
             // Statistical Functions
             double mean(std::vector <double> x);
+            double median(std::vector<double> x);
+            std::vector<double> mode(std::vector<double> x);
             double variance(std::vector <double> x);
             double covariance(std::vector <double> x, std::vector <double> y);
             double correlation(std::vector <double> x, std::vector<double> y);
diff --git a/main.cpp b/main.cpp
index 2b8c238..e8b0417 100644
--- a/main.cpp
+++ b/main.cpp
@@ -76,11 +76,13 @@ int main() {
     // std::vector<double> outputSet = {0,1,1,0};
 
     // // STATISTICS
-    // std::vector<double> x = {1,2,3,4,5,6,7,8,9,10};
+    // std::vector<double> x = {1,2,3,4,5,6,7,8,9,1};
     // std::vector<double> y = {10,9,8,7,6,5,4,3,2,1};
     // std::vector<double> w = {0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1};
 
     // std::cout << "Arithmetic Mean: " << stat.mean(x) << std::endl;
+    // std::cout << "Median: " << stat.median(x) << std::endl;
+    // alg.printVector(stat.mode(x));
     // std::cout << "Variance: " << stat.variance(x) << std::endl;
     // std::cout << "Covariance: " << stat.covariance(x, y) << std::endl;
     // std::cout << "Correlation: " << stat.correlation(x, y) << std::endl;