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formula sheet of prob, Lecture notes of Statistics

Formula sheet of probability and variables

Typology: Lecture notes

2021/2022

Uploaded on 10/02/2023

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Download formula sheet of prob and more Lecture notes Statistics in PDF only on Docsity! Page ___ of___ IE6200 Engineering Probability and Statistics 2015 Examination 1 2-HOUR TIMED EXAM Authorized Aid: Closed Book and Computer Standard Scientific Calculator (but no cell phone, tablet, etc.) 4 Pages of student selected notes and material (one side only; 8.5x11 paper) Scan all notes and supplemental pages of calculations to the exam booklet. Provided Tables: Montgomery & Runger Appendix A: Table I Summary of Common Probability Distributions Table KP6-1 IE6200 SN Common Probability Distributions Relevant portions of NCEES FE Exam Probability and Statistics Reference Section Sheets for additional work have been provided. Scoring Rubric: ___ ITEMS with a total of ___ parts; each part has a value of 10 points Score Performance 9 to 10 Only the most minor of errors; no conceptual errors 8 to 9 Two to three minor errors or one conceptual error 7 to 8 Combination of minor and conceptual errors 6 to 7 Many errors 0 to 5 Non-attempt or otherwise little substantive correct work Grading Rubric: Score Letter Grade > 90% A 80 % to 90% B 70 % to 80% C 60 % to 70% D < 60% F Note: Clarity and precision of your work is of the utmost importance. Full credit will not be awarded without appropriate supporting evidence. Clearly state any assumptions particularly if you are stuck and need to move on with the work or have a question about something that is not clear to you from the item statement. “I attest that I have abided by the Northeastern University Guidelines for Academic Integrity as stated in the Graduate Student Handbook.” NAME (Print) NAME (Sig.) TableI Summary of Common Probability Distributions Name Probability Distribution Mean Variance Section in Book Discrete Uniform Lass @+2) (sewiy ea 35 2 12 Binomial es 1- 36 ino (pto-p" * np pC - p) xr=O0,1..4,0<Sp<1 Geometric aapytp Up (1- pip? a7 x=1,2,..,0¢p<1 Negative binomial = y -p) fp? a7 8 ( i)e py pt tp nlp) r-1 xarnrelr+2,..,0Sp<l Hypergeometric KVIN-K np, where p — © a8 = Ww op(l-P) WF N n x=max(0,2-N+K), 1, min(K, 2), K < Bn <N Poisson eae ben A A 39 xl a Continuous Uniform (+a) @-af aaah 2 1 Normal m 2 46 Exponential WA ape 48 Erlang TK rire 49.1 Gamma TK re 49.2 Weibull a \ 3) 5 ( 3) 410 ye ses] L mal O42 af 2 411 ognor. e gitar ( 1} Beta Ti 3 a ag 412 (a+ 3) x ag a+ af Tay (3) 0<x<1, 0<a,0<9 (e+ BF (a4 840) Page of__ Page ___ of___ Cumulative Standard Normal Table for Positive z values z 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.0 0.5000 0.5040 0.5080 0.5120 0.5160 0.5199 0.5239 0.5279 0.5319 0.5359 0.1 0.5398 0.5438 0.5478 0.5517 0.5557 0.5596 0.5636 0.5675 0.5714 0.5753 0.2 0.5793 0.5832 0.5871 0.5910 0.5948 0.5987 0.6026 0.6064 0.6103 0.6141 0.3 0.6179 0.6217 0.6255 0.6293 0.6331 0.6368 0.6406 0.6443 0.6480 0.6517 0.4 0.6554 0.6591 0.6628 0.6664 0.6700 0.6736 0.6772 0.6808 0.6844 0.6879 0.5 0.6915 0.6950 0.6985 0.7019 0.7054 0.7088 0.7123 0.7157 0.7190 0.7224 0.6 0.7257 0.7291 0.7324 0.7357 0.7389 0.7422 0.7454 0.7486 0.7517 0.7549 0.7 0.7580 0.7611 0.7642 0.7673 0.7704 0.7734 0.7764 0.7794 0.7823 0.7852 0.8 0.7881 0.7910 0.7939 0.7967 0.7995 0.8023 0.8051 0.8078 0.8106 0.8133 0.9 0.8159 0.8186 0.8212 0.8238 0.8264 0.8289 0.8315 0.8340 0.8365 0.8389 1.0 0.8413 0.8438 0.8461 0.8485 0.8508 0.8531 0.8554 0.8577 0.8599 0.8621 1.1 0.8643 0.8665 0.8686 0.8708 0.8729 0.8749 0.8770 0.8790 0.8810 0.8830 1.2 0.8849 0.8869 0.8888 0.8907 0.8925 0.8944 0.8962 0.8980 0.8997 0.9015 1.3 0.9032 0.9049 0.9066 0.9082 0.9099 0.9115 0.9131 0.9147 0.9162 0.9177 1.4 0.9192 0.9207 0.9222 0.9236 0.9251 0.9265 0.9279 0.9292 0.9306 0.9319 1.5 0.9332 0.9345 0.9357 0.9370 0.9382 0.9394 0.9406 0.9418 0.9429 0.9441 1.6 0.9452 0.9463 0.9474 0.9484 0.9495 0.9505 0.9515 0.9525 0.9535 0.9545 1.7 0.9554 0.9564 0.9573 0.9582 0.9591 0.9599 0.9608 0.9616 0.9625 0.9633 1.8 0.9641 0.9649 0.9656 0.9664 0.9671 0.9678 0.9686 0.9693 0.9699 0.9706 1.9 0.9713 0.9719 0.9726 0.9732 0.9738 0.9744 0.9750 0.9756 0.9761 0.9767 2.0 0.9772 0.9778 0.9783 0.9788 0.9793 0.9798 0.9803 0.9808 0.9812 0.9817 2.1 0.9821 0.9826 0.9830 0.9834 0.9838 0.9842 0.9846 0.9850 0.9854 0.9857 2.2 0.9861 0.9864 0.9868 0.9871 0.9875 0.9878 0.9881 0.9884 0.9887 0.9890 2.3 0.9893 0.9896 0.9898 0.9901 0.9904 0.9906 0.9909 0.9911 0.9913 0.9916 2.4 0.9918 0.9920 0.9922 0.9925 0.9927 0.9929 0.9931 0.9932 0.9934 0.9936 2.5 0.9938 0.9940 0.9941 0.9943 0.9945 0.9946 0.9948 0.9949 0.9951 0.9952 2.6 0.9953 0.9955 0.9956 0.9957 0.9959 0.9960 0.9961 0.9962 0.9963 0.9964 2.7 0.9965 0.9966 0.9967 0.9968 0.9969 0.9970 0.9971 0.9972 0.9973 0.9974 2.8 0.9974 0.9975 0.9976 0.9977 0.9977 0.9978 0.9979 0.9979 0.9980 0.9981 2.9 0.9981 0.9982 0.9982 0.9983 0.9984 0.9984 0.9985 0.9985 0.9986 0.9986 3.0 0.9987 0.9987 0.9987 0.9988 0.9988 0.9989 0.9989 0.9989 0.9990 0.9990 3.1 0.9990 0.9991 0.9991 0.9991 0.9992 0.9992 0.9992 0.9992 0.9993 0.9993 3.2 0.9993 0.9993 0.9994 0.9994 0.9994 0.9994 0.9994 0.9995 0.9995 0.9995 3.3 0.9995 0.9995 0.9995 0.9996 0.9996 0.9996 0.9996 0.9996 0.9996 0.9997 3.4 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9998 33 ENGINEERING PROBABILITY AND STATISTICS DISPERSION, MEAN, MEDIAN, AND MODE VALUES If X1, X2, … , Xn represent the values of a random sample of n items or observations, the arithmetic mean of these items or observations, denoted X , is defined as . X n X X X n X X n 1 1 for sufficiently large values of n i i n 1 2 1 " f= + + + = n = _ _ _i i i ! The weighted arithmetic mean is ,X w w X wherew i i i= ! ! Xi = the value of the ith observation, and wi = the weight applied to Xi. The variance of the population is the arithmetic mean of the squared deviations from the population mean. If µ is the arithmetic mean of a discrete population of size N, the population variance is defined by / / N X X X N X 1 1 N i i N 2 1 2 2 2 2 2 1 f= - + - + + - = - v n n n n = ^ ^ ^ _ ^ _ h h h i h i 9 C ! Standard deviation formulas are / ... n n A B N X1population sum n series mean product b a i 2 1 2 2 2 2 2 2 2 2 v n v v v v v v v v v v v = - = + + + = = = + ^ _h i/ The sample variance is /s n X X1 1 i i n2 2 1 = - - = ^ `h j7 A ! The sample standard deviation is /s n X X1 1 i i n 2 1 = - - = ^ `h j7 A ! The sample coefficient of variation = /CV s X= The sample geometric mean = X X X Xnn 1 2 3f The sample root-mean-square value = /n X1 i 2^ h! When the discrete data are rearranged in increasing order and n is odd, the median is the value of the n 2 1 th +b l item When n is even, the median is the average of the and .n n 2 2 1 items th th +b bl l The mode of a set of data is the value that occurs with greatest frequency. The sample range R is the largest sample value minus the smallest sample value. PERMUTATIONS AND COMBINATIONS A permutation is a particular sequence of a given set of objects. A combination is the set itself without reference to order. 1. The number of different permutations of n distinct objects taken r at a time is , ! !P n r n r n= - ^ ^h h nPr is an alternative notation for P(n,r) 2. The number of different combinations of n distinct objects taken r at a time is , ! , ! ! !C n r r P n r r n r n= = - ^ ^ ^h h h7 A nCr and n re o are alternative notations for C(n,r) 3. The number of different permutations of n objects taken n at a time, given that ni are of type i, where i = 1, 2, …, k and ∑ni = n, is ; , , , ! ! ! !P n n n n n n n n k k 1 2 1 2 f f=_ i SETS De Morgan's Law A B A B A B A B , + + , = = Associative Law A B C A B C A B C A B C , , , , + + + + = = ^ ] ^ ] h g h g Distributive Law A B C A B A C A B C A B A C , + , + , + , + , + = = ^ ] ^ ^ ] ^ h g h h g h LAWS OF PROBABILITY Property 1. General Character of Probability The probability P(E) of an event E is a real number in the range of 0 to 1. The probability of an impossible event is 0 and that of an event certain to occur is 1. Property 2. Law of Total Probability P(A + B) = P(A) + P(B) – P(A, B), where P(A + B) = the probability that either A or B occur alone or that both occur together P(A) = the probability that A occurs P(B) = the probability that B occurs P(A, B) = the probability that both A and B occur simultaneously ENGINEERING PROBABILITY AND STATISTICS 34 ENGINEERING PROBABILITY AND STATISTICS Property 3. Law of Compound or Joint Probability If neither P(A) nor P(B) is zero, P(A, B) = P(A)P(B | A) = P(B)P(A | B), where P(B | A) = the probability that B occurs given the fact that A has occurred P(A | B) = the probability that A occurs given the fact that B has occurred If either P(A) or P(B) is zero, then P(A, B) = 0. Bayes' Theorem A P B A P A B P B P B P A B P A A P B B B where is the probability of event within the population of is the probability of event within the population of j j i i i n j j j j j 1 = = _ _ _ _ _ _ _ i i i i i i i ! PROBABILITY FUNCTIONS, DISTRIBUTIONS, AND EXPECTED VALUES A random variable X has a probability associated with each of its possible values. The probability is termed a discrete probability if X can assume only discrete values, or X = x1, x2, x3, …, xn The discrete probability of any single event, X = xi, occurring is defined as P(xi) while the probability mass function of the random variable X is defined by f (xk) = P(X = xk), k = 1, 2, ..., n Probability Density Function If X is continuous, the probability density function, f, is defined such that P a X b f x dx a b # # =^ ^h h# Cumulative Distribution Functions The cumulative distribution function, F, of a discrete random variable X that has a probability distribution described by P(xi) is defined as , , , ,F x P x P X x m n1 2m k k m m 1 f#= = = = _ _ _i i i! If X is continuous, the cumulative distribution function, F, is defined by F x f t dt x = 3- ^ ^h h# which implies that F(a) is the probability that X ≤ a. Expected Values Let X be a discrete random variable having a probability mass function f (xk), k = 1, 2,..., n The expected value of X is defined as E X x f xk k n k 1 = =n = _ i6 @ ! The variance of X is defined as V X x f xk k n k 2 2 1 = = -v n = _ _i i6 @ ! Let X be a continuous random variable having a density function f(X) and let Y = g(X) be some general function. The expected value of Y is: E Y E g X g x f x dx= = 3 3 - ] ^ ^g h h6 7@ A # The mean or expected value of the random variable X is now defined as E X xf x dx= =n 3 3 - ^ h6 @ # while the variance is given by V X E X x f x dx2 2 2 = = - = -v n n 3 3 - ^ ^ ^h h h6 9@ C # The standard deviation is given by V X=v 6 @ The coefficient of variation is defined as σ/μ. Combinations of Random Variables Y = a1 X1 + a2 X2 + …+ an Xn The expected value of Y is: E Y a E X a E X a E Xy n n1 1 2 2 f= = + + +n ] ^ ^ _g h h i If the random variables are statistically independent, then the variance of Y is: V Y a V X a V X a V X a a a y n n n n 2 1 2 1 2 2 2 2 1 2 1 2 2 2 2 2 2 2 f f = = + + + = + + + v v v v ] ^ ^ _g h h i Also, the standard deviation of Y is: y y 2=v v When Y = f(X1, X2,.., Xn) and Xi are independent, the standard deviation of Y is expressed as: y = ...X f X f X f 1 2 2 2 2 X X n X1 2 n2 2 2 2 2 2 v v v+ + +v d d dn n n 46 ENGINEERING PROBABILITY AND STATISTICS Cumulative Binomial Probabilities P(X ≤ x) n 1 2 3 4 5 6 7 8 9 x 0 0 1 0 1 2 0 1 2 3 0 1 2 3 4 0 1 2 3 4 5 0 1 2 3 4 5 6 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 8 0.1 0.9000 0.8100 0.9900 0.7290 0.9720 0.9990 0.6561 0.9477 0.9963 0.9999 0.5905 0.9185 0.9914 0.9995 1.0000 0.5314 0.8857 0.9842 0.9987 0.9999 1.0000 0.4783 0.8503 0.9743 0.9973 0.9998 1.0000 1.0000 0.4305 0.8131 0.9619 0.9950 0.9996 1.0000 1.0000 1.0000 0.3874 0.7748 0.9470 0.9917 0.9991 0.9999 1.0000 1.0000 1.0000 0.2 0.8000 0.6400 0.9600 0.5120 0.8960 0.9920 0.4096 0.8192 0.9728 0.9984 0.3277 0.7373 0.9421 0.9933 0.9997 0.2621 0.6554 0.9011 0.9830 0.9984 0.9999 0.2097 0.5767 0.8520 0.9667 0.9953 0.9996 1.0000 0.1678 0.5033 0.7969 0.9437 0.9896 0.9988 0.9999 1.0000 0.1342 0.4362 0.7382 0.9144 0.9804 0.9969 0.9997 1.0000 1.0000 0.3 0.7000 0.4900 0.9100 0.3430 0.7840 0.9730 0.2401 0.6517 0.9163 0.9919 0.1681 0.5282 0.8369 0.9692 0.9976 0.1176 0.4202 0.7443 0.9295 0.9891 0.9993 0.0824 0.3294 0.6471 0.8740 0.9712 0.9962 0.9998 0.0576 0.2553 0.5518 0.8059 0.9420 0.9887 0.9987 0.9999 0.0404 0.1960 0.4628 0.7297 0.9012 0.9747 0.9957 0.9996 1.0000 0.4 0.6000 0.3600 0.8400 0.2160 0.6480 0.9360 0.1296 0.4752 0.8208 0.9744 0.0778 0.3370 0.6826 0.9130 0.9898 0.0467 0.2333 0.5443 0.8208 0.9590 0.9959 0.0280 0.1586 0.4199 0.7102 0.9037 0.9812 0.9984 0.0168 0.1064 0.3154 0.5941 0.8263 0.9502 0.9915 0.9993 0.0101 0.0705 0.2318 0.4826 0.7334 0.9006 0.9750 0.9962 0.9997 0.5 0.5000 0.2500 0.7500 0.1250 0.5000 0.8750 0.0625 0.3125 0.6875 0.9375 0.0313 0.1875 0.5000 0.8125 0.6988 0.0156 0.1094 0.3438 0.6563 0.9806 0.9844 0.0078 0.0625 0.2266 0.5000 0.7734 0.9375 0.9922 0.0039 0.0352 0.1445 0.3633 0.6367 0.8555 0.9648 0.9961 0.0020 0.0195 0.0889 0.2539 0.5000 0.7461 0.9102 0.9805 0.9980 0.6 0.4000 0.1600 0.6400 0.0640 0.3520 0.7840 0.0256 0.1792 0.5248 0.8704 0.0102 0.0870 0.3174 0.6630 0.9222 0.0041 0.0410 0.1792 0.4557 0.7667 0.9533 0.0106 0.0188 0.0963 0.2898 0.5801 0.8414 0.9720 0.0007 0.0085 0.0498 0.1737 0.4059 0.6846 0.8936 0.9832 0.0003 0.0038 0.0250 0.0994 0.2666 0.5174 0.7682 0.9295 0.9899 0.7 0.3000 0.0900 0.5100 0.0270 0.2160 0.6570 0.0081 0.0837 0.3483 0.7599 0.0024 0.0308 0.1631 0.4718 0.8319 0.0007 0.0109 0.0705 0.2557 0.5798 0.8824 0.0002 0.0038 0.0288 0.1260 0.3529 0.6706 0.9176 0.0001 0.0013 0.0113 0.0580 0.1941 0.4482 0.7447 0.9424 0.0000 0.0004 0.0043 0.0253 0.0988 0.2703 0.5372 0.8040 0.9596 0.8 0.2000 0.0400 0.3600 0.0080 0.1040 0.4880 0.0016 0.0272 0.1808 0.5904 0.0003 0.0067 0.0579 0.2627 0.6723 0.0001 0.0016 0.0170 0.0989 0.3446 0.7379 0.0000 0.0004 0.0047 0.0333 0.1480 0.4233 0.7903 0.0000 0.0001 0.0012 0.0104 0.0563 0.2031 0.4967 0.8322 0.0000 0.0000 0.0003 0.0031 0.0196 0.0856 0.2618 0.5638 0.8658 0.9 0.1000 0.0100 0.1900 0.0010 0.0280 0.2710 0.0001 0.0037 0.0523 0.3439 0.0000 0.0005 0.0086 0.0815 0.4095 0.0000 0.0001 0.0013 0.0159 0.1143 0.4686 0.0000 0.0000 0.0002 0.0027 0.0257 0.1497 0.5217 0.0000 0.0000 0.0000 0.0004 0.0050 0.0381 0.1869 0.5695 0.0000 0.0000 0.0000 0.0001 0.0009 0.0083 0.0530 0.2252 0.6126 0.95 0.0500 0.0025 0.0975 0.0001 0.0073 0.1426 0.0000 0.0005 0.0140 0.1855 0.0000 0.0000 0.0012 0.0226 0.2262 0.0000 0.0000 0.0001 0.0022 0.0328 0.2649 0.0000 0.0000 0.0000 0.0002 0.0038 0.0444 0.3017 0.0000 0.0000 0.0000 0.0000 0.0004 0.0058 0.0572 0.3366 0.0000 0.0000 0.0000 0.0000 0.0000 0.0006 0.0084 0.0712 0.3698 0.99 0.0100 0.0001 0.0199 0.0000 0.0003 0.0297 0.0000 0.0000 0.0006 0.0394 0.0000 0.0000 0.0000 0.0010 0.0490 0.0000 0.0000 0.0000 0.0000 0.0015 0.0585 0.0000 0.0000 0.0000 0.0000 0.0000 0.0020 0.0679 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0027 0.0773 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0034 0.0865 P Montgomery, Douglas C., and George C. Runger, Applied Statistics and Probability for Engineers, 4th ed. Reproduced by permission of John Wiley & Sons, 2007. 47 ENGINEERING PROBABILITY AND STATISTICS Cumulative Binomial Probabilities P(X ≤ x) (continued) n 10 15 20 x 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 0.1 0.3487 0.7361 0.9298 0.9872 0.9984 0.9999 1.0000 1.0000 1.0000 1.0000 0.2059 0.4590 0.8159 0.9444 0.9873 0.9978 0.9997 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.1216 0.3917 0.6769 0.8670 0.9568 0.9887 0.9976 0.9996 0.9999 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.2 0.1074 0.3758 0.6778 0.8791 0.9672 0.9936 0.9991 0.9999 1.0000 1.0000 0.0352 0.1671 0.3980 0.6482 0.8358 0.9389 0.9819 0.9958 0.9992 0.9999 1.0000 1.0000 1.0000 1.0000 1.0000 0.0115 0.0692 0.2061 0.4114 0.6296 0.8042 0.9133 0.9679 0.9900 0.9974 0.9994 0.9999 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.3 0.0282 0.1493 0.3828 0.6496 0.8497 0.9527 0.9894 0.9984 0.9999 1.0000 0.0047 0.0353 0.1268 0.2969 0.5155 0.7216 0.8689 0.9500 0.9848 0.9963 0.9993 0.9999 1.0000 1.0000 1.0000 0.0008 0.0076 0.0355 0.1071 0.2375 0.4164 0.6080 0.7723 0.8867 0.9520 0.9829 0.9949 0.9987 0.9997 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.4 0.0060 0.0464 0.1673 0.3823 0.6331 0.8338 0.9452 0.9877 0.9983 0.9999 0.0005 0.0052 0.0271 0.0905 0.2173 0.4032 0.6098 0.7869 0.9050 0.9662 0.9907 0.9981 0.9997 1.0000 1.0000 0.0000 0.0005 0.0036 0.0160 0.0510 0.1256 0.2500 0.4159 0.5956 0.7553 0.8725 0.9435 0.9790 0.9935 0.9984 0.9997 1.0000 1.0000 1.0000 1.0000 0.5 0.0010 0.0107 0.0547 0.1719 0.3770 0.6230 0.8281 0.9453 0.9893 0.9990 0.0000 0.0005 0.0037 0.0176 0.0592 0.1509 0.3036 0.5000 0.6964 0.8491 0.9408 0.9824 0.9963 0.9995 1.0000 0.0000 0.0000 0.0002 0.0013 0.0059 0.0207 0.0577 0.1316 0.2517 0.4119 0.5881 0.7483 0.8684 0.9423 0.9793 0.9941 0.9987 0.9998 1.0000 1.0000 0.6 0.0001 0.0017 0.0123 0.0548 0.1662 0.3669 0.6177 0.8327 0.9536 0.9940 0.0000 0.0000 0.0003 0.0019 0.0093 0.0338 0.0950 0.2131 0.3902 0.5968 0.7827 0.9095 0.9729 0.9948 0.9995 0.0000 0.0000 0.0000 0.0000 0.0003 0.0016 0.0065 0.0210 0.0565 0.1275 0.2447 0.4044 0.5841 0.7500 0.8744 0.9490 0.9840 0.9964 0.9995 1.0000 0.7 0.0000 0.0001 0.0016 0.0106 0.0473 0.1503 0.3504 0.6172 0.8507 0.9718 0.0000 0.0000 0.0000 0.0001 0.0007 0.0037 0.0152 0.0500 0.1311 0.2784 0.4845 0.7031 0.8732 0.9647 0.9953 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0003 0.0013 0.0051 0.0171 0.0480 0.1133 0.2277 0.3920 0.5836 0.7625 0.8929 0.9645 0.9924 0.9992 0.8 0.0000 0.0000 0.0001 0.0009 0.0064 0.0328 0.1209 0.3222 0.6242 0.8926 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0008 0.0042 0.0181 0.0611 0.1642 0.3518 0.6020 0.8329 0.9648 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0006 0.0026 0.0100 0.0321 0.0867 0.1958 0.3704 0.5886 0.7939 0.9308 0.9885 0.9 0.0000 0.0000 0.0000 0.0000 0.0001 0.0016 0.0128 0.0702 0.2639 0.6513 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0003 0.0022 0.0127 0.0556 0.1841 0.4510 0.7941 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0004 0.0024 0.0113 0.0432 0.1330 0.3231 0.6083 0.8784 0.95 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0010 0.0115 0.0861 0.4013 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0006 0.0055 0.0362 0.1710 0.5367 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0003 0.0026 0.0159 0.0755 0.2642 0.6415 0.99 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0043 0.0956 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0004 0.0096 0.1399 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0010 0.0169 0.1821 P Montgomery, Douglas C., and George C. Runger, Applied Statistics and Probability for Engineers, 4th ed. Reproduced by permission of John Wiley & Sons, 2007.
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