So first off, the answer to this is 24 now think of x as the real or original sum or amount, also y as the new sum or amount.
y * 1.5 is x, and y+12 is x. Now flip that to figure out what is y, also which is what we need, and you have x/1.5 = y as well as x-12 = y. Use the equal values method and make an equation x/1.5=x-12. solve this equation to get x, which is 36. to figure out the new amount, y, you need to minus 12, which can help you get the answer which is 24.
There is 3.6 5/6s in 3
There is 0.4 5/6s in 1/3
Answer:
z = 5
x = 0
x = 1
Step-by-step explanation:
(z - 5)x^2 - (z - 5)x = 0 Take out z - 5 as a common factor
(z - 5)(x^2 - x) Take out x as a common factor
(z - 5)(x)(x - 1) Any one of these could equal 0. There are 3 solutons.
z - 5 = 0 Add 5 to both sides
z - 5 + 5 = 0 + 5
z = 5
===============
x = 0
===============
x - 1 = 0
x - 1 + 1 = 0 + 1
x = 1
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Answer:
The approximate probability of getting 100000 views or more in January if we assume view counts from day-to-day are independent = 0.22254
Step-by-step explanation:
January has 31 days.
The average number of views per day = 3022 views per day.
In terms of hourly basis, the average number of views = 3022/24 ≈ 126 views per hour
Then we need to find the probability that the number of views in January is equal to or exceeds 100000.
100000 views in January = 100000/31 = 3225.81 ≈ 3226 views per day
On an hourly basis, 3226 views per day ≈ 135 views per hour.
So, mean = λ = 126 views per hour
x = 135 views per hour.
Using Poisson's distribution function
P(X = x) = (e^-λ)(λˣ)/x!
P(X ≥ x) = Σ (e^-λ)(λˣ)/x! (Summation From x to the end of the distribution)
But it's easier to obtain
P(X < x) = Σ (e^-λ)(λˣ)/x! (Summation From 0 to x)
P(X ≥ x) = 1 - P (X < x)
Putting λ = 126 views/hour and x = 135 views/hour in the Poisson distribution formula calculator
P(X ≥ 135) = 0.22254
