when X and Y are independent ,
"P(X\/Y)=P(X)\\\\"
Therefore,
"P(1.202<X\/Y<83180000)=P(1.202<X<83180000)=P\\\\"
consider the log normal distribution,
"P=P(log_{10}{1.202}<log_{10}{X}<log_{10}{83180000})\\\\"
"log_{10}{1.202}=log_{10}{(\\frac{1202}{1000})}=log_{10}{1202}-3=0.08\\\\\nlog_{10}{83180000}=log_{10}{(8318*10000)}=log_{10}{8318}+4=6.92\\\\"
Then,
"P=P(0.8<log_{10}{X}<6.92)\\\\\nnormalize\\ the\\ value,\\\\\nz=\\frac{X-\\bar{X}}{\\sigma}\\\\\nz_1=\\frac{0.8-7}{\\sqrt{3}}=-3.5796\\\\\nz_2=\\frac{6.92-7}{\\sqrt{3}}=-0.0462\\\\\nP=P(-3.5796<z<-0.0462)\\\\\nP=P(-3.5796<z<0)-P(-0.0462<z<0)\\\\\nP=P(0<z<3.5796)-P(0<z<0.0462)\\\\\nusing\\ calculator\\ or\\ table,\\\\\nP=0.4998-0.0184=\\bold{0.4814}\\\\"
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