"a_0=20, \\overline{x}=25, s=10, n=15, \\alpha=0.05\\\\\nH_0: \\mu=a_0=20, H_1: \\mu>a_0=20\\text{ (right-tailed)}"
We assume that bet has normal distribution.
We will use the following random variable as a criterion:
"U=\\frac{(\\overline{X}-a_0)\\sqrt{n}}{s}"
This random variable has t-distribution with "k=n-1" degrees of freedom.
Observed value:
"u_{obs}=\\frac{(25-20)\\sqrt{15}}{10}\\approx 1.94"
Critical value (one-sided):
"t_{cr}=t_{cr}(\\alpha;k)=t_{cr}(0.05;14)\\approx 1.76"
"(1.76;\\infty)\\text{ --- critical region}"
"u_{obs}" falls into the critical region. So we reject "H_0".
We can accuse him of being overly risky (if clients bet only $20 per game).
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