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total pages=1007 total pages=1007
**Currently reading:** chapter 1, page 80 **Currently reading:** chapter 1, page 88
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"$$p_1 = \\frac{p_2}{1 + p_2}$$" "$$p_1 = \\frac{p_2}{1 + p_2}$$"
] ]
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"### Example 1.24\n",
"\n",
"Let $A$ be the event where my chosen marble is red.\n",
"\n",
"Let $B_1$ be the set of the first bag, $B_2$ the second bag, $B_3$ the third bag.\n",
"\n",
"Notice that $B_1, B_2,$ and $B_3$ are disjoint and therefore form a partition of our sample space.\n",
"\n",
"\n",
"\\begin{align*}\n",
"P(A) &= P(A|B_1)P(B_1) + P(A|B_2)P(B_2) + P(A|B_3)P(B_3) \\\\\n",
"&= \\frac{75}{100} \\cdot \\frac{1}{3} + \\frac{60}{100} \\cdot \\frac{1}{3} + \\frac{45}{100} \\cdot \\frac{1}{3} \\\\\n",
"&= \\frac{180}{300} = \\frac{6}{10} = 0.6\n",
"\\end{align*}\n",
"\n"
]
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"source": [
"### Example 1.25\n",
"\n",
"Let $A$ be the event we chose a red marble and let $B$ be the event we chose from the first bag.\n",
"\n",
"\\begin{align*}\n",
"P(B|A) &= \\frac{P(A|B)P(B)}{P(A)} \\\\\n",
"&= \\frac{\\frac{75}{100} \\cdot \\frac{1}{3}}{\\frac{6}{10}} \\\\\n",
"&= \\frac{75}{300} \\cdot \\frac{10}{6} \\\\\n",
"&= \\frac{750}{1800} = \\frac{75}{180} = \\frac{15}{36} = \\frac{5}{12} \\\\\n",
"\\end{align*}\n"
]
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"source": [
"### Example 1.26\n",
"\n",
"Let $A$ be the event we chose a red marble and let $B$ be the event we chose from the first bag.\n",
"\n",
"\\begin{align*}\n",
"P(B|A) &= \\frac{P(A|B)P(B)}{P(A)} \\\\\n",
"\n",
"\\end{align*}"
]
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@@ -133,13 +133,44 @@
"$$P(A_1 \\cup A_2 \\cup \\dots \\cup A_n) = 1 - (1 - P(A_1))(1 - P(A_2))\\dots(1 - P(A_n))$$" "$$P(A_1 \\cup A_2 \\cup \\dots \\cup A_n) = 1 - (1 - P(A_1))(1 - P(A_2))\\dots(1 - P(A_n))$$"
] ]
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"source": [
"## Law of Total Probability (1.4.2)\n",
"\n",
"$$P(A) = P(A|B)P(B) + P(A|B^c)P(B^c)$$\n",
"\n",
"**Definition.** Law of Total Probability: \\\n",
"If $B_1, B_2, B_3, \\dots $ is a partition of the sample space $S$, then for any event $A$ we have\n",
"\n",
"$$P(A) = \\sum_i P(A \\cap B_i) = \\sum_i P(A|B_i)P(B_i)$$"
]
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"\n" "## Bayes' Rule (1.4.3)\n",
"\n",
"**Definition.** Bayes' Rule\n",
"\n",
"- For any two events $A$ and $B$, where $P(A) \\neq 0$, we have\n",
"\n",
"$$P(B|A) = \\frac{P(A|B)P(B)}{P(A)}$$\n",
"\n",
"- If $B_1, B_2, B_3, \\dots$ form a partition of the sample space $S$, and $A$ is any event with $P(A) \\neq 0$, we have\n",
"\n",
"$$P(B_j|A) = \\frac{P(A|B_j)P(B_j)}{\\sum_i P(A|B_i)P(B_i)}$$"
] ]
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