Posts

Showing posts with the label Student T

New Main Stand

-
Image
  Now that academy is finished. Parish and co can go “hell for leather” for the new stand. Let's look into what it will mean for the club.  Increase in seats in the main stand of 7,873, reduction in Family stand of 594 and filling in the corner of Arthur Wait to add 683 seats. That would put the ground at 34,259. It would make Selhurst Park the 14th biggest club ground in England. Looking through the plans, It looks like the club will really increase its corporate facilities with two floors of the five-floor stand just being for corporate. It looks good for all budgets of hospitality. Watching padded seat on TikTok, I have noticed very different levels of hospitality. Before that, I used to think it was all very high-end. Actually, there are more affordable packages but still expensive.  New landmark I remember in the early days of cpfc2010 they replaced the gates to the stadium car park. Before that, if there was a news story about Palace. The go-to picture was of the ta...
Post a Comment
Read more

Student T - OpenAI

-
Image
I asked Open AI's new chat bot to create a blog about my favorite distribution. So we go.   Sure, I'd be happy to write a blog about the student's t-distribution! Here is a brief overview of what it is and how it is used: The student's t-distribution, also known simply as the t-distribution, is a probability distribution that is often used to estimate population parameters when the sample size is small and the population variance is unknown. It is a continuous probability distribution that is symmetric around its mean, and it has heavier tails than the normal distribution, which means that it is more prone to producing extreme values. One of the key characteristics of the t-distribution is that it depends on a parameter called the degrees of freedom, which is equal to the sample size minus 1. As the degrees of freedom increase, the t-distribution becomes more and more similar to the normal distribution. This property makes the t-distribution useful for testing hypothese...
Post a Comment
Read more