WHAT PROPERTY DESCRIBES THE NUMBER SENTENCE 6+0=6

1 answer:

4 0

The property here is called additive identiy. These are the set of numbers when added to any number , say "a", then they will yield the same number "a". So, in the given eqaution, 6 +0 = 6.Here 0 is the additive identity.

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A commuter railway has 800 passengers a day and charges each one 2 dollars. ?

Fiesta28 [93]

Answer:

I= -20p^2 + 840p

Step-by-step explanation:

When the ticket price is $2 there are 800 passengers daily, but every $0.1 increase in ticket price the number of passengers will be decreased by 2.

You can put information into these equations of:

passenger- = (800-2x)

ticket price= p = $2 + 0.1x

Income is calculated by multiplying the number of the passenger with the ticket price. The answer will be expressed in terms of the ticket price, so we need to remove x from the passenger equation.

p= $2 +0.1x

p-$2 = 0.1x

x= 10p- $20

If p= ticket price, the function for the number of passengers it will be:

passenger = (800-2x)

passenger = 800- 2(10p- $20)

passenger =800- 20p+40

passenger =840- 20p

The function of I will be:

I= passenger x ticket price

I= 840- 20p * p

I= -20p^2 + 840p

4 0

2 years ago

General Hospital has noted that they admit an average of 9 patients per hour.

serious [3.7K]

Answer:

(a) The probability that during the next hour less than 3 patients will be admitted is 0.00623.

(b) The probability that during the next two hours exactly 8 patients will be admitted is 0.00416.

Step-by-step explanation:

The complete question is: General Hospital has noted that they admit an average of 8 patients per hour.

(a) What is the probability that during the next hour less than 3 patients will be admitted?

(b) What is the probability that during the next two hours exactly 8 patients will be admitted?

The above situation can be represented through Poisson distribution as it includes the arrival rate of the pattern. So, the probability distribution of the Poisson distribution is given by;

$P(X = x) = \frac{e^{-\lambda} \times \lambda^{x} }{x!} ; x = 0,1,2,......$

Here X = Number of patients admitted in the hospital

$\lambda$ = arrival rate of patients per hour = 9 patients

So, X ~ Poisson( $\lambda$ = 9)

(a) The probability that during the next hour less than 3 patients will be admitted is given by = P(X < 3)

P(X < 3) = P(X = 0) + P(X = 1) + P(X = 2)

= $\frac{e^{-9} \times 9^{0} }{0!} + \frac{e^{-9} \times 9^{1} }{1!} + \frac{e^{-9} \times 9^{2} }{2!}$

= $e^{-9} +(e^{-9} \times 9)+ \frac{e^{-9} \times 81}{2}$

= 0.00623

(b) Here, $\lambda = 9 \times 2$ = 18 because we have to find the probability for the next two hours and we are given in the question of per hour.