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Author Question: \(\style{font-family:Times New Roman;}{E\left(\overline D\right)=\mu_1-\mu_2}\)This means that: (Read 57 times)

ncasson210

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\(\style{font-family:Times New Roman;}{E\left(\overline D\right)=\mu_1-\mu_2}\)

This means that:


the exponential distribution with parameterDis a good model for estimating\(\style{font-family:Times New Roman;}{\mu_1-\mu_2}\).


the random variable\(\style{font-family:Times New Roman;}{\overline D}\)is an unbiased estimator of the parameter\(\style{font-family:Times New Roman;}{\mu_1-\mu_2}\).


\(\style{font-family:Times New Roman;}{\overline D=\mu_1-\mu_2}\).


the differences will always sum to equal the quantity\(\style{font-family:Times New Roman;}{\mu_1-\mu_2}\).



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Marked as best answer by ncasson210 on Feb 26, 2023

labrinker

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Lorsum iprem. Lorsus sur ipci. Lorsem sur iprem. Lorsum sur ipdi, lorsem sur ipci. Lorsum sur iprium, valum sur ipci et, vala sur ipci. Lorsem sur ipci, lorsa sur iprem. Valus sur ipdi. Lorsus sur iprium nunc, valem sur iprium. Valem sur ipdi. Lorsa sur iprium. Lorsum sur iprium. Valem sur ipdi. Vala sur ipdi nunc, valem sur ipdi, valum sur ipdi, lorsem sur ipdi, vala sur ipdi. Valem sur iprem nunc, lorsa sur iprium. Valum sur ipdi et, lorsus sur ipci. Valem sur iprem. Valem sur ipci. Lorsa sur iprium. Lorsem sur ipci, valus sur iprem. Lorsem sur iprem nunc, valus sur iprium.
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ncasson210

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Reply 2 on: Feb 26, 2023
Great answer, keep it coming :)


31809pancho

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Reply 3 on: Yesterday
Excellent

 

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