Updated the formulas and readme text.

Formulas.txt

@@ -1,25 +1,32 @@
-Use Average Weighted Grade to calculate Recovery and Processing cost then use these two to calculate cut off grade using the formula cof(g) = processing cost / ((net price) * recovery). Use inputs from a table. Make graphs in Python for the Cutoff Grade, Recovery, Processing Cost.
+# Description
+
+The process began with utilizing average weighted grade data from a table to determine the recovery rate and processing costs.  These values were then applied in the cut-off grade calculation: Cut-Off Grade = Processing Cost / ((Net Price) * Recovery). The average weighted grade and net price were sourced directly from the table. Finally, Python was employed to create graphs illustrating the cut-off grade, recovery rate, and processing cost trends.
+
+Cut-Off Grade = Processing Cost / ((Net Price) * Recovery)
 
 
-cof(g) = processing cost / ((net price) * recovery)
+Recovery = Rmax​ * (1 − e^(−k*G))
+
+Processing Cost = a + b*G
 
 
-recovery = Rmax​ x (1−e^(−k⋅G))
-
-processing cost = C0​ + C1/G​​
+# Processing Cost Formulas
 
 1. Fixed + Grade-Dependent Cost Model  
 processing cost = C0​ + C1/G​​
 
-2. Tabulated Cost Based on Grade
-
-Table equivalent for the given grade
-
-3. Regression from Real Cost Data (Realist)
+2. Regression from Real Cost Data (Realist)
 
 Linear: C = a + bG
 
-Inverse or logarithmic: C = a + b/G or C = alog⁡(G) + b
+Inverse or Logarithmic: C = a + b/G or C = a*log⁡(G) + b
+
+3. Tabulated Cost Based on Grade
+
+Table equivalent for the given grade
+
+
+# Recovery Formulas
 
 1. Empirical Linear Model