You are manager of a specialty coffee shop and collect data throughout a full day regarding waiting time for customers from the time they enter the shop until the time they pick up their order. (a) What type of distribution do you think would be most desirable for the waiting times: skewed right, skewed left, mound-shaped symmetric? Explain. A skewed left distribution would be the most desirable because this would mean there are a lot of short waiting times and only a few long waiting times. A skewed right distribution would be the most desirable because this would mean there are never any long waiting times. A skewed right distribution would be the most desirable because this would mean there are a lot of short waiting times and only a few long waiting times. A skewed left distribution would be the most desirable because this would mean there are never any long waiting times. A mound shaped symmetric distribution would be the most desirable distribution because this would mean
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
You are manager of a specialty coffee shop and collect data throughout a full day regarding waiting time for customers from the time they enter the shop until the time they pick up their order.
(a) What type of distribution do you think would be most desirable for the waiting times: skewed right, skewed left, mound-shaped symmetric? Explain.
A skewed left distribution would be the most desirable because this would
A skewed right distribution would be the most desirable because this would mean there are never any long waiting times.
A skewed right distribution would be the most desirable because this would mean there are a lot of short waiting times and only a few long waiting times.
A skewed left distribution would be the most desirable because this would mean there are never any long waiting times.
A mound shaped symmetric distribution would be the most desirable distribution because this would mean are a lot of short waiting times and only a few long waiting times.
(b) What if the distribution for waiting times were bimodal? What might be some explanations?
A bimodal distribution for waiting times might exist if orders are filled at different rates during busy and slow periods.
A bimodal distribution for waiting times might exist if almost all orders take a long time to fill and only a couple orders are filled very quickly.
A bimodal distribution for waiting times might exist if almost all orders are filled very quickly and only a couple orders get lost throughout the day.
A bimodal distribution for waiting times might exist if almost all orders are filled in approximately the same amount of time.
(a) Option (iii) is the correct option here.
(iii) A skewed right distribution would be the most desirable because this would mean there are a lot of short waiting times and only a few long waiting times.
This is the correct option because here likely to see most of the customer's waiting fewer times for their orders, while only few may have to wait for more time, which will lead to tail in the right side of data.
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