Answer:
True, I think.
Step-by-step explanation:
Answer:
a) The approximate probability that more than 25 chips are defective is 0.1075.
b) The approximate probability of having between 20 and 30 defecitve chips is 0.44.
Step-by-step explanation:
Lets call X the total amount of defective chips. X has Binomial distribution with parameters n=1000, p =0.02. Using the Central Limit Theorem, we can compute approximate probabilities for X using a normal variable with equal mean and standard deviation.
The mean of X is np = 1000*0.2 = 20, and the standard deviation is √np(1-p) = √(20*0.98) = 4.427
We will work with a random variable Y with parameters μ=20, σ=4.427. We will take the standarization of Y, W, given by

The values of the cummmulative distribution function of the standard normal random variable W, which we will denote
, can be found in the attached file. Now we can compute both probabilities. In order to avoid trouble with integer values, we will correct Y from continuity.
a)

Hence the approximate probability that more than 25 chips are defective is 0.1075.
b)

As a result, the approximate probability of having between 20 and 30 defecitve chips is 0.44.
THE FACTORS OF 16 ARE 1,2,4,8,16
THE FACTORS OF 96 ARE 1,2,3,4,6,8,12,16,24,32,48,96
THE GREATEST COMMON FACTOR IS 16
THE GREATEST COMMON FACTOR OF 2 OR MORE NUMBERS IS THE LARGEST WHOLE NUMBER THAT DIVIDES EVENLY INTO EACH OF THE NUMBERS
Work out what he saves in 1 month
161
141 +
302 =
302 x 24 (months)
= $7,248
I'm assuming 'for' means 'four/4'
4/5 is 0.8 blocks per hour.
8*.08 is 6.4 hours.