Initial commit

python/Math/Describe linear regression.py

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+#https://gist.github.com/cartr/6513044  
+# Define the data
+
+# A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and a is the intercept (the value of y when x = 0).
+
+
+data = set()  
+count = int(input("Enter the number of data points: "))  
+for i in range(count):  
+    x=float(input("X"+str(i+1)+": "))  
+    y=float(input("Y"+str(i+1)+": "))  
+    data.add((x,y))  
+  
+# Find the average x and y  
+avgx = 0.0  
+avgy = 0.0  
+for i in data:  
+    avgx += i[0]/len(data)  
+    avgy += i[1]/len(data)  
+  
+# Find the sums  
+totalxx = 0  
+totalxy = 0  
+  
+for i in data:  
+    totalxx += (i[0]-avgx)**2  
+    totalxy += (i[0]-avgx)*(i[1]-avgy)  
+  
+# Slope/intercept form  
+m = totalxy/totalxx  
+b = avgy-m*avgx  
+  
+print("Best fit line:")  
+print("y = "+str(m)+"x + "+str(b))  
+  
+x = float(input("Enter a value to calculate: "))  
+print("y = "+str(m*x+b))