How Do You Test a Hypothesis Without Sample Variance?

GabrielN00

Homework Statement


Given ##X_1,\dots,X_{100}##, test ##H_0: \lambda=1## against ##H_a: \lambda=4##. The mean ##\bar{X_{100}}=1.5##
(1) Take the decision on 3% level.
(2) Find the p-value

Homework Equations



##t=\frac{\bar{x}-\mu}{s/\sqrt{n}}##

The Attempt at a Solution



The level of significance is ##0.033##. The p-value I need to evaluate ##\frac{\bar{x}-\mu}{s/\sqrt{n}}##, but I am missing ##s##. Is it still possible to have a solution?
 
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Is that the full problem statement?

Is the Poisson distribution mentioned somewhere?
 
GabrielN00 said:

Homework Statement


Given ##X_1,\dots,X_{100}##, test ##H_0: \lambda=1## against ##H_a: \lambda=4##. The mean ##\bar{X_{100}}=1.5##
(1) Take the decision on 3% level.
(2) Find the p-value

Homework Equations



##t=\frac{\bar{x}-\mu}{s/\sqrt{n}}##

The Attempt at a Solution



The level of significance is ##0.033##. The p-value I need to evaluate ##\frac{\bar{x}-\mu}{s/\sqrt{n}}##, but I am missing ##s##. Is it still possible to have a solution?
Do you mean that the upper limit on the type-I error is 3%? How did 3% become 0.033?

Are ##X_1, X_2, \ldots, X_{100}## independent and identically distributed? Are they Poisson random variables? If they are Poisson, you can use the formula for the variance of a Poisson to get the exact standard deviation ##\sigma##, so there is no need to use the unavailable sample variance, ##s##. (However, for a Poisson, variance is a function of the mean, so be careful).
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...

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