The number of calls arriving at a switchboard from noon to 1 PM during the business days Monday through Friday is monitored for six weeks (i. e., 30 days). Let X be defined as the number of calls during that one-hour period. The relative frequency of calls was recorded and reported as Value 5 68 9 10
Relative Frequency 0.067 0.067 0.100 0.133 0.200
Value 11 12 13 14 15
Relative
Frequency 0.133 0.133 0.067 0.033 0.067
(a) Does the assumption of a Poisson distribution seem appropriate as a probability model for this data? Use a = 0.05.
(b) Calculate the P-value for this test.

A) The assumption of a Poisson distribution is appropriate and we will fail to reject the null hypothesis since the critical value is lower than the level of significance

b) p-value = 0.834

Step-by-step explanation:

a) let the number of calls per hour = X

number of sample points = 10

the expected number of calls per hour : E (x)

= ∑ xi * yi  = 10.221

given boundaries are : n - 1 , i = 0

Therefore the mean ( β ) number of calls per hour = 10.221

Note : The interesting event is the number of calls that arrives per hour

applying hypothesis testing :

H0 :   α ≤ β  ( null hypothesis )

Ha :   α ≥ β  ( alternate hypothesis )

we will fail to reject the null hypothesis since the critical value is lower than the level of significance

attached below is the remaining part of the solution

b) P-value = 0.834

1)is not similar since corresponding sides are not in the same ratio

2)are similar since corresponding sides are in the same ratio and corresponding angles are equal

hope it will

#faazmessi

f(x) = y

f(-3) = -5

step-by-step explanation: