From 83b8445087829c0276ca9d149ac37ca924b53957 Mon Sep 17 00:00:00 2001 From: Ernesto Moreno <88721535+ernestom1412@users.noreply.github.com> Date: Tue, 5 Oct 2021 19:30:32 -0400 Subject: [PATCH] Add files via upload --- your-code/main.ipynb | 252 +++++++++++++++++++++++++++++++++++++------ 1 file changed, 217 insertions(+), 35 deletions(-) diff --git a/your-code/main.ipynb b/your-code/main.ipynb index 95bfcb9..2af91f2 100644 --- a/your-code/main.ipynb +++ b/your-code/main.ipynb @@ -11,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -31,10 +31,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "0.6" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p_vanilla=(3/4)*(1/2)+(1/2)*(1/2)\n", + "p_vanilla_bw1=((3/4)*(1/2))/p_vanilla\n", + "p_vanilla_bw1" + ] }, { "cell_type": "markdown", @@ -45,10 +60,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "0.4" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p_vanilla_bw2=((1/2)*(1/2))/p_vanilla\n", + "p_vanilla_bw2" + ] }, { "cell_type": "markdown", @@ -59,10 +88,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Probability the cookie came from Bowl1: 0.3333333333333333\n", + "Probability the cookie came from Bowl2: 0.6666666666666666\n" + ] + } + ], + "source": [ + "p_chocolate=(1/4)*(1/2)+(1/2)*(1/2)\n", + "p_chocolate_bw1=((1/4)*(1/2))/p_chocolate\n", + "p_chocolate_bw2=((1/2)*(1/2))/p_chocolate\n", + "print('Probability the cookie came from Bowl1:',p_chocolate_bw1)\n", + "print('Probability the cookie came from Bowl2:',p_chocolate_bw2)" + ] }, { "cell_type": "markdown", @@ -95,10 +139,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "0.39215686274509803" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p_yellow=(1/5)*(1/2)+(7/50)*(1/2)\n", + "p_yellow_b1=((1/5)*(1/2))/p_yellow\n", + "p_green=(1/10)*(1/2)+(1/5)*(1/2)\n", + "p_geen_b2=((1/5)*(1/2))/p_green\n", + "p_yellow1_green2=p_yellow_b1*p_geen_b2\n", + "p_yellow1_green2" + ] }, { "cell_type": "markdown", @@ -109,10 +171,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "0.13725490196078433" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p_yellow_b2=((7/50)*(1/2))/p_yellow\n", + "p_geen_b1=((1/10)*(1/2))/p_green\n", + "p_yellow2_green1=p_yellow_b2*p_geen_b1\n", + "p_yellow2_green1" + ] }, { "cell_type": "markdown", @@ -123,10 +201,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Probabilities that the green one came from Bag 1 is 0.13725490196078433\n", + "Probabilities that the green one came from Bag 2 is 0.39215686274509803\n" + ] + } + ], + "source": [ + "print('Probabilities that the green one came from Bag 1 is',p_yellow2_green1)\n", + "print('Probabilities that the green one came from Bag 2 is',p_yellow1_green2)" + ] }, { "cell_type": "markdown", @@ -141,10 +231,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "probability of winning the car sticking with Door A 0.3333333333333333\n", + "probability of winning the car switching to Door C 0.6666666666666666\n" + ] + } + ], + "source": [ + "DoorA=((1/3)*(1/3))/(1/3*1/3+1/3*1/3+1/3*1/3)\n", + "DoorC=((1/3)*(2/3))/(1/3*1/3+1/3*1/3+1/3*1/3)\n", + "print('probability of winning the car sticking with Door A',DoorA)\n", + "print('probability of winning the car switching to Door C',DoorC)" + ] }, { "cell_type": "markdown", @@ -157,10 +261,44 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "n_draws = 100_000\n", + "prior = pd.Series(np.random.uniform(0,1,size=n_draws))\n", + "def generative_model(proba_compra):\n", + " compraron = np.random.binomial(100, proba_compra)\n", + " return compraron\n", + "compraron = list()\n", + "for equipo in prior:\n", + " compraron.append(generative_model(equipo))\n", + "posteriori = prior[list(map(lambda x:x ==14, compraron))]\n", + "posteriori.hist()" + ] }, { "cell_type": "markdown", @@ -171,10 +309,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "count 1004.000000\n", + "mean 0.147412\n", + "std 0.034774\n", + "min 0.051833\n", + "25% 0.123244\n", + "50% 0.145268\n", + "75% 0.168321\n", + "max 0.271232\n", + "dtype: float64" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "posteriori.describe()" + ] }, { "cell_type": "markdown", @@ -185,10 +344,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0.09734429823795133,0.21125552606791898)\n" + ] + } + ], + "source": [ + "print(f'({posteriori.quantile(0.05)},{posteriori.quantile(0.95)})')" + ] }, { "cell_type": "markdown", @@ -199,10 +368,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "0.1474116609430692" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "posteriori.mean()" + ] } ], "metadata": { @@ -221,7 +403,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.8.8" } }, "nbformat": 4,