Molto lavoro per negare il modello, ora si inizia con LaTeX perché altrimenti non finiamo

molla/compatibilita/comp2.ipynb

@@ -2,29 +2,25 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "ba4e56bc",
+   "id": "3b66972b",
    "metadata": {},
    "source": [
-    "## Valori dinamici\n",
-    "N = 10\n",
+    "# Molla statica 1 Calibro\n",
+    "Ac  = 3.20021 ± 0.00923\n",
     "\n",
-    "A      = 3.21951 +- 0.00470 "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "aaf30c1f",
-   "metadata": {},
-   "source": [
-    "## Valori statici\n",
-    "N = 6\n",
+    "# Molla statica 1 Sonar\n",
+    "Ac  = 3.21962 ± 0.00633\n",
     "\n",
-    "A      = 3.2002 +- 0.0092\n"
+    "# Molla dinamica 1 Sonar\n",
+    "KdC      = 3.2792872 ± 0.00924\n",
+    "\n",
+    "# Molla dinamica 1 Cronometro\n",
+    "KdtC     = 3.66092 ± 0.10078\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "id": "b349ba73",
    "metadata": {},
    "outputs": [],
@@ -35,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 3,
    "id": "a68eb302",
    "metadata": {},
    "outputs": [
@@ -43,21 +39,103 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "t = 5.774\n",
-      "p-value (two-tailed) = 0.0048 %\n"
+      "t = 3.807\n",
+      "p-value (two-tailed) = 0.1924 %\n"
      ]
     }
    ],
    "source": [
-    "# Valori dimanici (sonar)\n",
+    "# Valori statici (sonar)\n",
     "Nd = 10\n",
-    "Ad = 3.220\n",
-    "uAd = 0.005\n",
+    "Ad =  3.220\n",
+    "uAd = 0.006\n",
     "\n",
     "#Valori statici (calibro)\n",
     "Ns = 6\n",
     "As = 3.200\n",
-    "uAs = 0.009\n",
+    "uAs = 0.015\n",
+    "\n",
+    "#Nomi coerenti con Cannelli\n",
+    "GdL = Nd + Ns - 2\n",
+    "\n",
+    "s2 = ( (Nd - 1) * uAd**2  +  (Ns - 1) * uAs**2 ) / GdL\n",
+    "\n",
+    "sigma2 = ( s2 / Nd )  + ( s2 / Ns )\n",
+    "\n",
+    "t = ( Ad - As ) / np.sqrt( sigma2 )\n",
+    "\n",
+    "\n",
+    "p_value = 2 * (1 - student_t.cdf(abs(t), df=GdL))\n",
+    "print(f\"t = {t:.3f}\")\n",
+    "print(f\"p-value (two-tailed) = {p_value * 100:.4f} %\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "459b7f56",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t = -5.278\n",
+      "p-value (two-tailed) = 0.0117 %\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Valori statici (sonar)\n",
+    "Nd = 10\n",
+    "Ad =  3.220\n",
+    "uAd = 0.006 * 3\n",
+    "\n",
+    "#Valori dinamici (sonar)\n",
+    "Ns = 6\n",
+    "As =  3.279\n",
+    "uAs = 0.009 * 3\n",
+    "\n",
+    "#Nomi coerenti con Cannelli\n",
+    "GdL = Nd + Ns - 2\n",
+    "\n",
+    "s2 = ( (Nd - 1) * uAd**2  +  (Ns - 1) * uAs**2 ) / GdL\n",
+    "\n",
+    "sigma2 = ( s2 / Nd )  + ( s2 / Ns )\n",
+    "\n",
+    "t = ( Ad - As ) / np.sqrt( sigma2 )\n",
+    "\n",
+    "\n",
+    "p_value = 2 * (1 - student_t.cdf(abs(t), df=GdL))\n",
+    "print(f\"t = {t:.3f}\")\n",
+    "print(f\"p-value (two-tailed) = {p_value * 100:.4f} %\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "5d82905f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t = 0.701\n",
+      "p-value (two-tailed) = 49.4616 %\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Valori dinamici (sonar)\n",
+    "Nd = 10\n",
+    "Ad =  3.279\n",
+    "uAd = 0.09 *3\n",
+    "\n",
+    "#Valori statici (calibro)\n",
+    "Ns = 6\n",
+    "As = 3.200\n",
+    "uAs = 0.015 * 3\n",
     "\n",
     "#Nomi coerenti con Cannelli\n",
     "GdL = Nd + Ns - 2\n",