Ok
the sets are
natural numbers (or counting numbers), this is like 1,2,3,4,5 etc
whole numbers, this is including 0, so 0,1,2,3,4,5,6 etc
integers, this includes the previoius set and negatives, so -3,-2,-1,0,1,2,3,4,5 etc
rational numbers, this is the set of numbers that can be written in form a/b where b≠0, so all integers can be written like this, like example -3=-3/1, so -7/9 belongs here
-7/9 goes in the rational set
Answer:
to estimate the sum you round to the closest number like 38 is closest to 40 so you just say you total is $40.00
difference is when say you have 30 dollars and you spend 10 the difference is 10 dollars
prime (not composite) as it can only be divided by 1 and itself
The cost of the ride varies by however many miles is driven, however the charging rate stays the same no matter how long the ride is. In the expression 0.20m + 2.00 , 2.00 is the constant as it stays the same, and 0.20 is the coefficient as is varies with however many miles are driven.
Answer:
Probability that the sample mean carapace length is more than 4.25 inches = 0.9993
Step-by-step explanation:
Given - There are many regulations for catching lobsters off the coast
of New England including required permits, allowable gear, and
size prohibitions. The Massachusetts Division of Marine Fisheries
requires a minimum carapace length measured from a rear eye
socket to the center line of the body shell. For a particular local
municipality, any lobster measuring less than 3.37 inches must
be returned to the ocean. The mean carapace length of the
lobsters is 4.01 inches with a standard deviation of 2.13 inches.
A random sample of 60 lobsters is obtained.
To find - What is the probability that the sample mean carapace length
is more than 4.25 inches?
Proof -
Given that, μ = 4.01, σ = 2.13 , n = 60
Now,
μₓ⁻ = σ / √n
= 
=
= 0.275
⇒μₓ⁻ = 0.275
Now,
P(X⁻ > 3.37) = 1 - P( X⁻ < 3.37)
= 1 - P(z <
)
= 1 - P( z < -3.2 )
= 1 - 0.0007
= 0.9993
⇒P(X⁻ > 3.37) = 0.9993
∴ we get
Probability that the sample mean carapace length is more than 4.25 inches = 0.9993