Modeling Public Bus Headways with Gaussian Processes

In summary, a Gaussian distribution, also known as a normal distribution, is a statistical distribution that is symmetric and bell-shaped. It is commonly used to model continuous random variables in various fields such as natural sciences, social sciences, and engineering. It is characterized by its mean and standard deviation, with the mean representing the center of the distribution and the standard deviation representing the spread or variability of the data. The Gaussian distribution is significant because it is a fundamental distribution in statistics and is used in many methods and models, as well as arising naturally in many real-world phenomena. However, not all data can be accurately modeled by a Gaussian distribution, as there are cases where different distributions may be more appropriate. In hypothesis testing, the Gaussian distribution is used to
  • #1
Mark J.
81
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Please help me find some references where public bus headways are described(modeled) as gaussian processes.
Best Regards
 
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  • #2
Google "bus headway distribution". You will get lots of references.
 

FAQ: Modeling Public Bus Headways with Gaussian Processes

What is a Gaussian distribution?

A Gaussian distribution, also known as a normal distribution, is a statistical distribution that is symmetric and bell-shaped. It is commonly used to model continuous random variables in various fields such as natural sciences, social sciences, and engineering.

How is a Gaussian distribution characterized?

A Gaussian distribution is characterized by its mean and standard deviation. The mean represents the center of the distribution, while the standard deviation represents the spread or variability of the data.

What is the significance of a Gaussian distribution?

The Gaussian distribution is significant because it is a fundamental distribution in statistics and plays a crucial role in many statistical methods and models. It also arises naturally in many real-world phenomena, making it a useful tool for analyzing and understanding data.

Can all data be modeled by a Gaussian distribution?

No, not all data can be accurately modeled by a Gaussian distribution. While many natural phenomena follow a Gaussian distribution, there are also many cases where the data may follow a different distribution, such as a skewed distribution or a bimodal distribution.

How is a Gaussian distribution used in hypothesis testing?

In hypothesis testing, the Gaussian distribution is used to calculate the probability of obtaining a certain result if the null hypothesis is true. This allows researchers to determine the significance of their findings and make conclusions about the population based on a sample of data.

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