Defect detection. we would like to determine if a meter is defective. the reading error is a n(0,0) rv if it is not defective. the error would be a n(0.5, 03) rv should it be defective. suppose that the following meter reading error data are collected in a calibration process: 0.16,-0.43, 1.25, -0.61, -2.42, 0.74,-0.72, 2.33,-0.4, 1.3, 0.04, 0.08, 0.88, -0.22, 0.55,-0.51,0.32,-0.54,-0.64, 0.54,-0.98,-0.40,0.66,-0.33,0,0.52, -0.23, 0.33,0.22,0.13,0.34,0.34, 0.66,-0.23,-0.33, 0.23, -0.12,-0.14,0.36 (a) find the sample mean and sample variance. (b) assuming 0 = 0.5 and 02 = 0.6, is it more probable that the meter is defective? (c) assuming 9 and 0, are unknown, is it more probable that the meter is defective?

step-by-step explanation:

there is a formula i can give you:

it is r^2*n*sin(360/n) divided by 2 where r represents the "radius" and n is the number of sides.

plug them in:

(10sqrt(3))^2*6*sin(360/6) divided by 2

100*3*6*sin(60) divided by 2

900*sin(60)

900*sqrt(3)/2

450*sqrt(3)

approx is 779.4 cm^2

according to egenuity the answer is

step-by-step explanation:

d. 344.22

step-by-step explanation:

i found the life tables for the year 2012. 

life table of males at age 30. probability of dying between ages x and x+1

total population:  

29–30 . . . . . . . . . . . . 0.001030

30–31 . . . . . . . . . . . . 0.001061

males:  

29–30 . . . . . . . . . . . . 0.001420

30–31 . . . . . . . . . . . . 0.001448

white population

29–30 . . . . . . . . . . . . 0.001005

30–31 . . . . . . . . . . . . 0.001037

white males

29–30 . . . . . . . . . . . . 0.001372

30–31 . . . . . . . . . . . . 0.001399

non hispanic white population

29–30 . . . . . . . . . . . . 0.001083

30–31 . . . . . . . . . . . . 0.001116

non hispanic white males

29–30 . . . . . . . . . . . . 0.001477

30–31 . . . . . . . . . . . . 0.001503

jacob, non hispanic white male. 30 years old.

probability that jacob lives to be 30 years old. 

since the given probabilities are probabilities of dying, i think we simply subtract it from 1 to get the probability of living. we will use the probability of non hispanic white male.

                                          probability of living to be 30 y.o.

29 - 30 : 1 - 0.001477 = 0.998523

30 - 31 : 1 - 0.001503 = 0.998497