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
D = t*s
distance = time * speed
d = t*30
Total number of balls = 100
Number of balls with odd numbers = 50
Number of balls with number greater than 80 = 20
Number of balls greater than 80 and is odd = 10
⇒ Number of favourable outcomes = 50 + 20 - 10 = 60
P(odd or greater than 80) = 60/100 = 3/5
Answer: 3/5
Answer:
B. Classical
Step-by-step explanation:
By definition, classic decision model is where the problems are clearly defined, all possible actions and alternatives are known, and the consequences of the alternatives are clear.
Answer:
25%
Step-by-step explanation:
4 days of 16 days is 25% or 1/4
Hope this helps! ;-)
