Normal distribution assumption

In summary, my teacher wants to know why we can use the normal distribution to model service time in a deterministic process. He was looking for explanations outside of 3sigma, histograms, and other types of measures. He was advised to read about the sum of identically distributed independent random variables and how it is approximately normally distributed.
  • #1
luckyluke
3
0
Hi everybody.
For sake of work I have to make an assumption that service time for patients is normally distributed.
Normally the doctor has to wait one patient every half hour but anyway this time can vary being less or more.
My teacher wants some theory arguments (normal distribution properties)why we can use normal distribution for modeling service time in our case.
This has to be in generally judging about process without looking on 3sigma,histogram etc.
I don't really know what to say
Any advices about readings or links?
THX
 
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  • #2
well the exponential distribution is usually used for waiting time problems, not the normal

unlike the normal, the waiting time cannot be negative
 
  • #3
Thank you.
It is about service time and there are many examples online where service time follow normal distribution...
For example
cob.jmu.edu/wangpx/kj/MS/5Sim/LectureSimHandout.pdf

where ATM service times follow normal distribution.
or
cs.mwsu.edu/~ranette/CMPS4223-Sim/Statistical%20Distr.ppt
where bus interarrival times are normally distributed.

Regards
 
  • #4
service time, waiting time have the same issues. just show that the variation in service time is more or less evenly distributed around the mean, without large outlier and the normal will work. Ideally subtracting 2-3 standard deviations from the mean does not get you a negative number. I.e. if the average service time is 1 minute but the SD is 10 minutes due to some large positive outliers then normal will not work. But if its 10 minutes with a standard deviation of 2 minutes normal is OK
 
  • #5
luckyluke said:
My teacher wants some theory arguments (normal distribution properties)why we can use normal distribution for modeling service time in our case.

A sum of identically distributed independent random variables is approximately normally distributed. I think there are some results relating the sum of independent non-identically distributed random variables to a normal distribution, but I can't quote them. If you think of the service of a patient as involving a sequence of many independent tasks (e.g. weighing the patient involves, walking to the scale, stepping on the scale, reading the scale, recording the weight) you could argue that a normal distribution approximates the sum of the elapsed times of these tasks.
 
  • #6
Thank you for this advice.
I was reasoning on normal distribution used when there is mistake (late or earlier) from scheduled time.In literature I saw that we can use normal distribution rather than Poisson when we have scheduled time (deterministic process) and this time arrival variate.
Anyway still not finding any other explanations except the fact u mentioned about sum of i.i.d variables.
Regards
 

FAQ: Normal distribution assumption

1. What is the normal distribution assumption?

The normal distribution assumption is a statistical concept that states that data follows a specific pattern called a normal distribution. This means that the data is symmetrically distributed around a central point, with most of the data falling within a certain range of values.

2. Why is the normal distribution assumption important in science?

The normal distribution assumption is important in science because it allows researchers to make accurate predictions and draw conclusions from data. Many statistical tests and models rely on the assumption of normality to be valid and reliable.

3. How can I determine if my data follows a normal distribution?

There are several methods for determining if your data follows a normal distribution, such as creating a histogram or a Q-Q plot. You can also use statistical tests, such as the Shapiro-Wilk test, to assess the normality of your data.

4. What happens if my data does not follow a normal distribution?

If your data does not follow a normal distribution, it may be necessary to use alternative statistical methods or models that do not rely on the normal distribution assumption. Additionally, transformations can sometimes be applied to make the data more normally distributed.

5. Is the normal distribution assumption always accurate?

No, the normal distribution assumption is not always accurate. In some cases, data may follow a different distribution, such as a skewed or multi-modal distribution. It is important to assess and determine the appropriate distribution for your data before making conclusions based on the normal distribution assumption.

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