Bernoulli distribution.
Exactly 2 times:
"P(2)=C_8^2\\cdot(\\frac{1}{4})^2\\cdot(1-\\frac{1}{4})^{8-2} \\approx 0.311"
3 times or more:
"P(0)=C_8^0\\cdot(\\frac{1}{4})^0\\cdot(1-\\frac{1}{4})^{8-0} \\approx 0.1 \\\\[0.2cm]"
"P(1)=C_8^1\\cdot(\\frac{1}{4})^1\\cdot(1-\\frac{1}{4})^{8-1} \\approx 0.267 \\\\[0.2cm]"
"P(\\geq3)=1-P(0)-P(1)-P(2) \\approx 1 -0.1 -0.267 -0.311 = 0.322"
Ali shots and Baba shots are independent events. Still Bernoulli distribution.
"P_{Ali}(0)=C_3^0\\cdot(\\frac{1}{4})^0\\cdot(1-\\frac{1}{4})^{3-0} \\approx 0.422 \\\\[0.2cm]\nP_{Ali}(1)=C_3^1\\cdot(\\frac{1}{4})^1\\cdot(1-\\frac{1}{4})^{3-1} \\approx 0.422 \\\\[0.2cm]\nP_{Ali}(2)=C_3^2\\cdot(\\frac{1}{4})^2\\cdot(1-\\frac{1}{4})^{3-2} \\approx 0.141 \\\\[0.2cm]\nP_{Ali}(3)=C_3^3\\cdot(\\frac{1}{4})^3\\cdot(1-\\frac{1}{4})^{3-3} \\approx 0.016 \\\\[0.2cm]"
"P_{Baba}(0)=C_3^0\\cdot(\\frac{1}{3})^0\\cdot(1-\\frac{1}{3})^{3-0} \\approx 0.296 \\\\[0.2cm]\nP_{Baba}(1)=C_3^1\\cdot(\\frac{1}{3})^1\\cdot(1-\\frac{1}{3})^{3-1} \\approx 0.444 \\\\[0.2cm]\nP_{Baba}(2)=C_3^2\\cdot(\\frac{1}{3})^2\\cdot(1-\\frac{1}{3})^{3-2} \\approx 0.222 \\\\[0.2cm]\nP_{Baba}(3)=C_3^3\\cdot(\\frac{1}{3})^3\\cdot(1-\\frac{1}{3})^{3-3} \\approx 0.037 \\\\[0.2cm]"
"P=P_{Ali}(0)\\cdot P_{Baba}(0) + P_{Ali}(1)\\cdot P_{Baba}(1) + P_{Ali}(2)\\cdot P_{Baba}(2) + P_{Ali}(3)\\cdot P_{Baba}(3) \\approx \\\\[0.1cm]\n\\approx 0.422\\cdot0.296+0.422\\cdot0.444+0.141\\cdot0.222+0.016\\cdot0.037 \\approx \\\\[0.1cm]\n\\approx 0.344"
Ali takes 5 shots. So he misses 4 times and then hits the traget.
"P=(1-\\frac{1}{4})\\cdot(1-\\frac{1}{4})\\cdot(1-\\frac{1}{4})\\cdot(1-\\frac{1}{4})\\cdot\\frac{1}{4}\\approx 0.079"
Baba takes 4 shots. So when he shoots 4th time he hits the target 2nd time. First 3 shots can create any sequence of 1 hit and 2 missings. Bernoulli distribution again.
"P=\\left(C_3^1\\cdot(\\frac{1}{3})^1\\cdot(1-\\frac{1}{3})^2\\right)\\cdot\\frac{1}{3}\\approx0.148"
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