How to Determine the Constant c for a t-Student Distribution in Statistics?

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SUMMARY

The discussion focuses on determining the constant c for a t-Student distribution when using n+1 independent random variables from a normal distribution N(μ, σ²). The statistic t is defined as t = c(ȳ - xₙ₊₁) / s, where ȳ is the sample mean and s is the sample standard deviation. It is established that for the statistic to follow a t-Student distribution, the degrees of freedom will be n, as the sample standard deviation s has n degrees of freedom. The key difference between the two formulas discussed is that the first compares the sample mean to a new observation, while the second compares it to the population mean.

PREREQUISITES
  • Understanding of t-Student distribution and its properties
  • Knowledge of sample mean (ȳ) and sample standard deviation (s)
  • Familiarity with normal distribution N(μ, σ²)
  • Basic statistics concepts, including degrees of freedom
NEXT STEPS
  • Study the derivation of the t-Student distribution and its applications
  • Learn about the implications of degrees of freedom in statistical testing
  • Explore the differences between sample statistics and population parameters
  • Investigate the use of R or Python for calculating t-Student statistics
USEFUL FOR

Statisticians, data analysts, and students studying inferential statistics who need to understand the application of the t-Student distribution in hypothesis testing and confidence intervals.

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Question:
Consider n+1 mutually independent random variables [itex]x+i[/itex] from a normal distribution [itex]N(\mu ,\sigma ^{2})[/itex]. Define:

[tex]\bar{x} = \frac{1}{n} \sum_{i=1}^{n}{x_{i}}[/tex] and [tex]s^{2}=\frac{1}{n}\sum_{i=1}^{n}{\left(x_{i} - \bar{x}\right)^{2}}[/tex]

Find the constant c so that the statistic

[tex]t= c\frac{\bar{x} - x_{n+1}}{s}[/tex]

follows a t-student law. Find the degrees of freedom. Justify.

What I have so far:
Not much, but for a statistic to follow Student T distribution with n-1:

[tex]t=\frac{\bar{x}-\mu}{s / \sqrt{n}}[/tex]

Because we have n+1 random variables, and s has n degrees of freedome, the resulting student t distribution will have n degree of freedoms (if s is sample standard deviation, it should have n-1 degrees of freedom). I also just expanded the above equation:

[tex]t=c \frac {\frac{1}{n}\sum_{i=1}^{n}{x_{i}}-x_{n+1}}{\left(\frac{1}{n}\sum_{i=1}^{n}\left(x_{i} - \bar{x}\right)^{2}\right)^{\frac{1}{2}}}[/tex]

But what next? Can someone help? thanks!
 
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What are the two differences between the formula

[tex]t= \frac{\bar{x} - x_{n+1}}{s}[/tex]

and

[tex]t=\frac{\bar{x}-\mu}{s / \sqrt{n}}[/tex]
?
 

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