Function 
Notation 
Result 
Q_type(Q_Sample):
Determines the type of queue using Kendall's notation. 
Type
= 
M/M/3 
Q_L(Q_Sample):
Computes the mean number in the system. 
L= 
6.011236 
Q_W(Q_Sample):
Computes the mean number in the system. 
W
= 
1.2022472 
Q_Lq(Q_Sample):
Computes the mean number in the queue. 
Lq= 
3.511236 
Q_Wq(Q_Sample):
Computes the mean time in the queue. 
Wq
= 
0.7022472 
Q_Ls(Q_Sample):
Computes the mean number in service. 
Ls= 
2.5 
Q_Ws(Q_Sample):
Computes the mean time in service. 
Ws
= 
0.5 
Q_LamB(Q_Sample):
Computes the throughput of the station. 
LamB
= 
5 
Q_Eff(Q_Sample):
Computes the efficiency of the servers. 
Eff
= 
0.8333333 
Q_P0(Q_Sample):
Computes the probability of 0 in the system. 
P0
= 
0.0449438 
Q_PB(Q_Sample):
Computes the probability that all servers are busy. 
PB
= 
0.7022472 
Q_PF(Q_Sample):
Computes the probability that the system is full. 
PF
= 
0 
Q_FNext(k,
Q_Sample):
The FNext function computes the factor to obtain the next
probability in a series of state probabilities. The function
must be multiplied by the previous probability. k is the
index of the state computed.
P(1) = P(0)*FNext(1, Queue) 
P(1)
= 
0.1123596 
Q_Pn(k,
Q_Sample):
Computes the probability of n customers in the system. Illustrated
for 11. 
P(11)
= 
0.02722 
Q_PTq(time, Q_Sample):Computes
the cumulative probability distribution of the waiting
time in the queue. An example of this function is shown
below.

PTq(0.5) = 
0.4259344 