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COMP 480/580 Probabilistic Algorithms and Data Structures Luay Nakhleh Tail Bounds Computer Science Rice University What Is This About? How large can a random variable get? In other words, how far can a value that the random variable


  1. COMP 480/580 Probabilistic Algorithms and Data Structures Luay Nakhleh Tail Bounds Computer Science Rice University

  2. What Is This About? ❖ How large can a random variable get? ❖ In other words, how far can a value that the random variable takes be from its mean?

  3. mean

  4. mean tails

  5. mean how large? tails

  6. <latexit sha1_base64="kTVjQRU6iUov3VUghL8k1P3M2A8=">AB9XicbVDLSgMxFL1TX7W+qi7dBItQN2VGBF0WRXBZwT6gHUsmzbShmWRIMkoZ+h9uXCji1n9x59+YaWehrQcCh3Pu5Z6cIOZMG9f9dgorq2vrG8XN0tb2zu5ef+gpWiCG0SyaXqBFhTzgRtGmY47cSK4ijgtB2MrzO/UiVZlLcm0lM/QgPBQsZwcZKD2kvwmYUBOhmWu2c9sVt+bOgJaJl5MK5Gj0y1+9gSRJRIUhHGvd9dzY+ClWhFOp6VeomMyRgPadSgSOq/XSWeopOrDJAoVT2CYNm6u+NFEdaT6LATmYh9aKXif953cSEl37KRJwYKsj8UJhwZCTKkADpigxfGIJorZrIiMsMLE2KJKtgRv8cvLpHVW89yad3deqV/ldRThCI6hCh5cQB1uoQFNIKDgGV7hzXlyXpx352M+WnDynUP4A+fzB395kdY=</latexit> <latexit sha1_base64="kTVjQRU6iUov3VUghL8k1P3M2A8=">AB9XicbVDLSgMxFL1TX7W+qi7dBItQN2VGBF0WRXBZwT6gHUsmzbShmWRIMkoZ+h9uXCji1n9x59+YaWehrQcCh3Pu5Z6cIOZMG9f9dgorq2vrG8XN0tb2zu5ef+gpWiCG0SyaXqBFhTzgRtGmY47cSK4ijgtB2MrzO/UiVZlLcm0lM/QgPBQsZwcZKD2kvwmYUBOhmWu2c9sVt+bOgJaJl5MK5Gj0y1+9gSRJRIUhHGvd9dzY+ClWhFOp6VeomMyRgPadSgSOq/XSWeopOrDJAoVT2CYNm6u+NFEdaT6LATmYh9aKXif953cSEl37KRJwYKsj8UJhwZCTKkADpigxfGIJorZrIiMsMLE2KJKtgRv8cvLpHVW89yad3deqV/ldRThCI6hCh5cQB1uoQFNIKDgGV7hzXlyXpx352M+WnDynUP4A+fzB395kdY=</latexit> <latexit sha1_base64="kTVjQRU6iUov3VUghL8k1P3M2A8=">AB9XicbVDLSgMxFL1TX7W+qi7dBItQN2VGBF0WRXBZwT6gHUsmzbShmWRIMkoZ+h9uXCji1n9x59+YaWehrQcCh3Pu5Z6cIOZMG9f9dgorq2vrG8XN0tb2zu5ef+gpWiCG0SyaXqBFhTzgRtGmY47cSK4ijgtB2MrzO/UiVZlLcm0lM/QgPBQsZwcZKD2kvwmYUBOhmWu2c9sVt+bOgJaJl5MK5Gj0y1+9gSRJRIUhHGvd9dzY+ClWhFOp6VeomMyRgPadSgSOq/XSWeopOrDJAoVT2CYNm6u+NFEdaT6LATmYh9aKXif953cSEl37KRJwYKsj8UJhwZCTKkADpigxfGIJorZrIiMsMLE2KJKtgRv8cvLpHVW89yad3deqV/ldRThCI6hCh5cQB1uoQFNIKDgGV7hzXlyXpx352M+WnDynUP4A+fzB395kdY=</latexit> <latexit sha1_base64="kTVjQRU6iUov3VUghL8k1P3M2A8=">AB9XicbVDLSgMxFL1TX7W+qi7dBItQN2VGBF0WRXBZwT6gHUsmzbShmWRIMkoZ+h9uXCji1n9x59+YaWehrQcCh3Pu5Z6cIOZMG9f9dgorq2vrG8XN0tb2zu5ef+gpWiCG0SyaXqBFhTzgRtGmY47cSK4ijgtB2MrzO/UiVZlLcm0lM/QgPBQsZwcZKD2kvwmYUBOhmWu2c9sVt+bOgJaJl5MK5Gj0y1+9gSRJRIUhHGvd9dzY+ClWhFOp6VeomMyRgPadSgSOq/XSWeopOrDJAoVT2CYNm6u+NFEdaT6LATmYh9aKXif953cSEl37KRJwYKsj8UJhwZCTKkADpigxfGIJorZrIiMsMLE2KJKtgRv8cvLpHVW89yad3deqV/ldRThCI6hCh5cQB1uoQFNIKDgGV7hzXlyXpx352M+WnDynUP4A+fzB395kdY=</latexit> <latexit sha1_base64="hf6hOeTjseL13iz+i/MO/ptaY5E=">AB6HicbVBNS8NAEJ3Ur1q/qh69LBbBU0lEqMeiF48t2A9oQ9lsJ+3azSbsboQS+gu8eFDEqz/Jm/GbZuDtj4YeLw3w8y8IBFcG9f9dgobm1vbO8Xd0t7+weFR+fikreNUMWyxWMSqG1CNgktsGW4EdhOFNAoEdoLJ3dzvPKHSPJYPZpqgH9GR5CFn1Fip2R2UK27VXYCsEy8nFcjRGJS/+sOYpRFKwTVue5ifEzqgxnAmelfqoxoWxCR9izVNItZ8tDp2RC6sMSRgrW9KQhfp7IqOR1tMosJ0RNWO96s3F/7xeasIbP+MySQ1KtlwUpoKYmMy/JkOukBkxtYQyxe2thI2poszYbEo2BG/15XSvqp6btVrXlfqt3kcRTiDc7gED2pQh3toQAsYIDzDK7w5j86L8+58LFsLTj5zCn/gfP4AtbmM3A=</latexit> <latexit sha1_base64="hf6hOeTjseL13iz+i/MO/ptaY5E=">AB6HicbVBNS8NAEJ3Ur1q/qh69LBbBU0lEqMeiF48t2A9oQ9lsJ+3azSbsboQS+gu8eFDEqz/Jm/GbZuDtj4YeLw3w8y8IBFcG9f9dgobm1vbO8Xd0t7+weFR+fikreNUMWyxWMSqG1CNgktsGW4EdhOFNAoEdoLJ3dzvPKHSPJYPZpqgH9GR5CFn1Fip2R2UK27VXYCsEy8nFcjRGJS/+sOYpRFKwTVue5ifEzqgxnAmelfqoxoWxCR9izVNItZ8tDp2RC6sMSRgrW9KQhfp7IqOR1tMosJ0RNWO96s3F/7xeasIbP+MySQ1KtlwUpoKYmMy/JkOukBkxtYQyxe2thI2poszYbEo2BG/15XSvqp6btVrXlfqt3kcRTiDc7gED2pQh3toQAsYIDzDK7w5j86L8+58LFsLTj5zCn/gfP4AtbmM3A=</latexit> <latexit sha1_base64="hf6hOeTjseL13iz+i/MO/ptaY5E=">AB6HicbVBNS8NAEJ3Ur1q/qh69LBbBU0lEqMeiF48t2A9oQ9lsJ+3azSbsboQS+gu8eFDEqz/Jm/GbZuDtj4YeLw3w8y8IBFcG9f9dgobm1vbO8Xd0t7+weFR+fikreNUMWyxWMSqG1CNgktsGW4EdhOFNAoEdoLJ3dzvPKHSPJYPZpqgH9GR5CFn1Fip2R2UK27VXYCsEy8nFcjRGJS/+sOYpRFKwTVue5ifEzqgxnAmelfqoxoWxCR9izVNItZ8tDp2RC6sMSRgrW9KQhfp7IqOR1tMosJ0RNWO96s3F/7xeasIbP+MySQ1KtlwUpoKYmMy/JkOukBkxtYQyxe2thI2poszYbEo2BG/15XSvqp6btVrXlfqt3kcRTiDc7gED2pQh3toQAsYIDzDK7w5j86L8+58LFsLTj5zCn/gfP4AtbmM3A=</latexit> <latexit sha1_base64="hf6hOeTjseL13iz+i/MO/ptaY5E=">AB6HicbVBNS8NAEJ3Ur1q/qh69LBbBU0lEqMeiF48t2A9oQ9lsJ+3azSbsboQS+gu8eFDEqz/Jm/GbZuDtj4YeLw3w8y8IBFcG9f9dgobm1vbO8Xd0t7+weFR+fikreNUMWyxWMSqG1CNgktsGW4EdhOFNAoEdoLJ3dzvPKHSPJYPZpqgH9GR5CFn1Fip2R2UK27VXYCsEy8nFcjRGJS/+sOYpRFKwTVue5ifEzqgxnAmelfqoxoWxCR9izVNItZ8tDp2RC6sMSRgrW9KQhfp7IqOR1tMosJ0RNWO96s3F/7xeasIbP+MySQ1KtlwUpoKYmMy/JkOukBkxtYQyxe2thI2poszYbEo2BG/15XSvqp6btVrXlfqt3kcRTiDc7gED2pQh3toQAsYIDzDK7w5j86L8+58LFsLTj5zCn/gfP4AtbmM3A=</latexit> Why Do We Care? ❖ Example: ❖ is the number of steps an algorithm takes. X ❖ is the average-case running-time of the algorithm. E ( X ) ❖ Can the algorithm, on average, take 2n steps, but on some inputs take, say, 500n 2 steps?

  7. Recall ❖ A random variable is a function from the sample space of an experiment/process to the set of real numbers. ❖ A coin is tossed twice. Let X(t) be the random variable that equals the number of heads that appear when t is the outcome. Then X(t) takes on the following values: ❖ X(HH)=2 ❖ X(HT)=X(TH)=1 ❖ X(TT)=0

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