[b]Datos del enunciado:[/b][br]Ciudad A: Proporción poblacional [i]p[/i][i]A[/i]=0.25[br]Ciudad B: Proporción poblacional [i]p[/i][i]B[/i]=0.20[br]Tamaño de las muestras: [i]n[/i][i]A[/i]=[i]n[/i][i]B[/i]=100[br]Incógnitas:[br]a) La probabilidad de que la proporción muestral en B sea [b]mayor que la de A [/b][b]en 3% o más[/b], es decir: [br] [img]data:image/png;base64,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[/img][br]b) La probabilidad de que sea [b]menor que la de A en 3% o más[/b], es decir:[br][img]data:image/png;base64,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[/img][br][b][br]1. Distribución de las proporciones muestrales.-[/b]Cada proporción muestral se distribuye aproximadamente normal, y la diferencia de ellas también:[br][img]data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAGkAAAAfCAYAAADk+ePmAAAEDElEQVRoge2ZP0jzahTGjzcODTEudShK0KEGQh1EhCLFoQQcgnTy3yJdXOrSoXRxanHoUqcuKlSHblYo3QrFoYgF7WBBqyIO1cFMjmZ9vkGSa26jXvO19uZ++cE75JD39On7vO85STsAAOTyn+avfgtw+RrXJAfgmuQAXJMcgGuSA/jfmHRwcEADAwO0ubnZbykGXdMEmwiCACIyBsMwEEUR5XLZbkrbtNtt8DyPcrkMnudRrVZ/XEMvNdk2qVargYiQSqUAAE9PT1AUxRT7KRYXF1Gv1wEA9XodoVDoRz/fim5qsm1StVoFEaHRaJjikiSB4zjbglw6sd2Tzs7OiOM4mp2dNcUXFhbo9fWVms3mbxThr9nZ2SGWZWlycpKIiPb394llWWJZlorFonGf3hf0wbIsra2t9URTpVKhoaEhGh4eJlVVqVKp0MjICA0ODlI6nbacs7u7SxMTE58ntutuOBxGOBzuiMfjcRARLi4uPpwry7Kpn300ZFm2nH98fIxYLGac5mQyicPDQ2iahpmZGfj9ftP9giAYPUEv093m6uoKiqKg3W6DiBCPx7G1tQVN07CysgKGYTrmaJqG+fn5LyuPbbUcx1n2nqWlpZ4sghWFQgFEhFwuZ8T0TfKe8fFxAG+Lsr29jenp6Z5pury8BBFhY2PDiOXzecuN+36jfYat1azX6yAiyycWn8+HQCBgJ+23icVi8Pl8ppiiKBAEwbjWF0Ef6+vr0DTNMp9u8FdDN92Kvb09MAyD5+dnI5ZIJEBEps9ttVpQFAUAemNSKpWyPL76jnm/s6343XKnEwwGEYvFTDGfz4dIJGLSmkgkAAAPDw/geR6tVuvfftVvE41GO9pAKBSCJEmmmCzLhg6v1/tpe7BlkizLCAaDppj+XvDPftBLOI5DPp83ro+OjjpOeDgcNl0LgoBCodAzTYFAAPF43LhutVogImSzWSNWKpU6NmTXTeI4zhCiqipyuRw8Hg9EUUS73baT8tvoJTeZTAIATk5OwPO86RQBAM/z0DQNmqYhmUx2lKJuomkaiMgoY3d3dxgdHYUoiqZ7/H6/8Q4FvG2cUqn0Yd5vm6Q/GLwfgiAgk8l8WOt7QTabhSRJmJubAxGZNo5OJpMx6RRFEbVarWeaqtUqOI7D6uoqGIaBx+NBJBIxrUs0GoXX68XNzQ2Av/tgNBr9MO8A4Mx/ZpeXl4mITO9E/SadTlOxWKTr6+uu5nXsD6yNRoOmpqb6LcPE6ekpSZLU9byONElVVXp8fCRBEPotxUSz2aSxsbGu53WkSefn50RElMvlSFXVPqt54/7+nl5eXqhYLNLt7W1Xczu2J/1JOPIk/Wm4JjkA1yQH4JrkAFyTHIBrkgNwTXIArkkO4BcfArVYs0vrywAAAABJRU5ErkJggg==[/img][br][br]Con:[i]E[/i][[i]D[/i]]=[i]p[/i][i]B[/i]−[i]p[/i][i]A[/i]=0.20−0.25=−0.05[img]data:image/png;base64,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[/img][br][br]Y la varianza de la diferencia:[br]Var([i]D[/i])=0.001875+0.0016=0.003475[br][br]Su desviación estándar:[br][i]σ[/i][i]D[/i]=0.003475=0.0589[br][br][b]2. Calcular las probabilidades.-[/b][b]a) Probabilidad de que [/b][img]data:image/png;base64,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[/img][br][br]Transformamos a Z:[br][img]data:image/png;base64,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[/img][br][i][br]P[/i]([i]D[/i]≥0.03)=[i]P[/i]([i]Z[/i]≥1.36)=1−0.9131=0.0869[br][b][br][br]b)Probabilidad de que [/b][b] [/b][img]data:image/png;base64,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[/img][br][br]Transformamos a Z:[br][img]data:image/png;base64,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[/img][br][i][br]P[/i]([i]D[/i]≤−0.03)=[i]P[/i]([i]Z[/i]≤0.34)=0.6331[br][br][b]Respuesta.-[br][/b]a) [i] p[/i]^[i]B[/i]−[i]p[/i]^[i]A[/i]≥0.03 aproximadamente [b]8.69%[br][/b]b) [i] p[/i]^[i]B[/i]−[i]p[/i]^[i]A[/i]≤−0.03 aproximadamente [b]63.31%[/b][br][br]