Final answer:
The model for the place of birth of a sample of Arab students cannot be definitively determined without additional information on the distribution pattern of the data. Typically, places of birth might follow a normal distribution, but this is not always the case and the provided options require further context to accurately select the model.
Step-by-step explanation:
The place of birth of a sample of Arab students is represented by a specific type of distribution. Based on the options provided, such as Gaussian (normal), uniform, and exponential distributions, the correct model for the place of birth would depend on how the data is spread across different locations. Since no specific distribution shape is indicated, it isn't possible to definitively determine the model without additional information on the pattern of the data. However, often places of birth can sometimes align with a normal distribution if there's a tendency to cluster around certain populous areas, whereas a uniform distribution would suggest that every place of birth is equally likely, which is less common in real-world scenarios.
If the place of birth data resembles the scenarios outlined in other exercises, such as the example where many people can run a short distance and fewer as the distance increases, then an exponential distribution might be the correct model. This is because an exponential distribution typically models the time between events in a Poisson process, and might represent situations where the likelihood of an event decreases exponentially with distance or time.