Testing/proving X-bar oof an exponential distribution

In summary, the conversation revolves around a list of students with GPAs and the use of probability plots to determine if the distribution is exponential. The speaker also mentions having to prove or test a chi-bar with three different types of tests using miniTab software, but is unsure of how to do so. They ask for help and express confusion about the probability plot, as well as the use of chi-bar or x-bar and what they are supposed to prove.
  • #1
kadaj6
31
0
ok, so I have a list of students with GPA, I checked the probability plot and I think its a Exponential distribution, take a look:

Probability Plot of gpa.jpg



So I am given a χ-bar to prove, and I have to prove or test it with three different types of test, I don't know which ones or how to do them in miniTab software.

please help me.
 
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  • #2
That plot looks odd to me - it certainly does not look like a probability distribution.
i.e. if it were then the probability of getting a 4.0gpa is 0.99... did nearly everyone get a high gpa?

The "percent" on the vertical axis - what is it a percent of?

The curve looks like an inverse cumulative-normal.

Finally - are you asking about chi-bar or x-bar?
You appear to have supplied an incomplete problem statement - what are you supposed to "prove"?
Do you know of any tests that may fit the bill?
 

Related to Testing/proving X-bar oof an exponential distribution

1. What is an exponential distribution?

An exponential distribution is a probability distribution commonly used in statistics to model the time between events occurring at a constant rate. It has a right-skewed shape and is often used to describe the time between failures in a system or the time between customer arrivals in a queue.

2. How is X-bar used in an exponential distribution?

X-bar, or the sample mean, is used to estimate the population mean in an exponential distribution. It is calculated by taking the average of a sample of observations from the exponential distribution.

3. Why is it important to test/prove X-bar of an exponential distribution?

Testing or proving X-bar of an exponential distribution is important because it allows us to determine if our sample accurately represents the population. This is important for making accurate predictions and drawing conclusions about the population.

4. What is the process for testing/proving X-bar of an exponential distribution?

The process for testing/proving X-bar of an exponential distribution involves collecting a random sample from the population, calculating the sample mean, and comparing it to the expected population mean using statistical tests such as the t-test or ANOVA. If the sample mean is not significantly different from the expected population mean, we can conclude that X-bar of the exponential distribution has been proven.

5. What are some real-world applications of testing/proving X-bar of an exponential distribution?

Testing/proving X-bar of an exponential distribution is commonly used in various fields such as engineering, finance, and healthcare. For example, engineers may use it to estimate the mean time between failures of a machine, financial analysts may use it to predict the time between stock price changes, and healthcare professionals may use it to estimate the time between patient arrivals in a hospital emergency room.

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