chore: separate variance and deviation, penta stuff

arbiter/src/eve/stats.rs

@@ -116,22 +116,35 @@ impl Model {
     /// sample data.
     fn mean(&self, x: Score) -> f64 {
         match *self {
-            Self::Pentanomial => 0.0,
+            Self::Pentanomial => {
+                0.00 * x.ll + 0.25 * x.ld + 0.50 * (x.dd + x.wl) + 0.75 * x.wd + 1.00 * x.ww
+            }
             Self::Traditional => 1.0 * x.w + 0.5 * x.d + 0.0 * x.l,
         }
     }
 
     /// Calculates the deviation (square root of the variance) of the given
     /// sample data from the given pivot point.
     fn deviation(&self, x: Score, mu: f64) -> f64 {
+        self.variance(x, mu).sqrt()
+    }
+
+    /// Calculates the variance of the given sample data from the given pivot.
+    fn variance(&self, x: Score, mu: f64) -> f64 {
         match *self {
-            Self::Pentanomial => 0.0,
+            Self::Pentanomial => {
+                ((x.dd + x.wl) * f64::powi(0.50 - mu, 2)
+                    + x.ll * f64::powi(0.00 - mu, 2)
+                    + x.ld * f64::powi(0.25 - mu, 2)
+                    + x.wd * f64::powi(0.75 - mu, 2)
+                    + x.ww * f64::powi(1.00 - mu, 2))
+                    / x.n
+            }
             Self::Traditional => {
-                f64::sqrt(
-                    0.0 + x.w * f64::powi(1.0 - mu, 2)
-                        + x.d * f64::powi(0.5 - mu, 2)
-                        + x.l * f64::powi(0.0 - mu, 2),
-                ) / f64::sqrt(x.n * 2.0)
+                (x.w * f64::powi(1.0 - mu, 2)
+                    + x.d * f64::powi(0.5 - mu, 2)
+                    + x.l * f64::powi(0.0 - mu, 2))
+                    / (x.n * 2.0)
             }
         }
     }