In a queueing system with customer arrivals every 3 minutes and service times of 2 minutes, the average number of customers in the system is calculated to be approximately 0.667
To calculatethe average number of customers in the system, we can use Little's Law, which states that the average number of customers in a stable queueing system is equal to the average arrival rate multiplied by the average time spent in the system.
First, we need to calculate the average arrival rate. Since customers arrive once every 3 minutes, the arrival rate is 1 customer per 3 minutes or 1/3 customers per second.
The total service time is 2 minutes, and the standard deviation is 6.3. Therefore, the average service time is 2 minutes.
Using Little's Law, we multiply the average arrival rate (1/3 customers per minute) by the average service time (2 minutes) to obtain the average number of customers in the system.
Average number of customers in the queue = (1/3) × 2 = 2/3 ≈ 0.667
For each of these examples, I have attached an image provide showing work to fully understand the problem.
Positive correlation
The number of kids at the playground and the number of swings being used
As the number of kids at the playground increases, the number of swings being used will increase. When both variables increase, they have a positive correlation. Thus, the situation in this problem has a positive correlation.
If we sketch a scatter plot for this situation, notice that the number of kids at the playground would be on the x-axis and the number of swings being used would be on the y-axis.
We can predict that if the number of kids at the playground increases, then the number of swings being used would also increase. Since this is only a sketch, it's not important exactly where our points are. Instead, we simply want to draw the points so our scatter plot has a line of best fit line with an upward of positive slope.
The image for this correlation is the first attachment.
Negative correlation
The amount of time Diaco spends goofing off in class and the grade Dicaco earns in the class
Notice that if the amount of time that Diaco spends goofing off increases, his grade is likely to decrease. When one variable increases and the other decreases, they have a negative correlation. Thus, the situation in this problem has a negative correlation.
If we sketch a scatter plot for this situation, notice that the time goofing off would be on the x-axis and Diaco's grade would be on the y-axis.
We can predict that if Diaco spends little or no time goofing off, his grade will be high and if he spends a lot of time goofing off, his grade will be low. Since this is only a sketch, it's not important exactly where our points are. Instead, we want to simply draw the points so our scatter plot has a line of best fit with a downward or negative slope.
The image for this correlation is the second attachment.
No correlation
The number of pets a family has and the number of kids in the family
Notice that in most cases, the number of pets a family has is not related to the number of kids in the family. Thus, there is no correlation between the number of pets a family has and the number of kids in the family.
If we sketch a scatter plot for this situation, notice that the number of pets a family has would be on the x-axis and the number of kids in the family would be on the y-axis.
Since there is no correlation between the variables, the data points will be spread out and there will be no best fit line.
The image for "no correlation" is the third attachment.