8. 0, 12,-45,-156.
9.
A. -27
B. -27,-19,-13,-5,4,0
C. 0
The confidence interval formula is extremely complicated to derive, which is one of the justifications for using the bootstrap approach. this statement is true.
<h2>What purposes serve the bootstrap method?</h2>
A resampling technology named the bootstrap can be used to sample a dataset using replacement to calculate statistics on a group. Estimating summary statistics like the mean or standard deviation may be done using it.
<h3>The advantages of the bootstrap method</h3>
The benefits of bootstrapping include its simplicity in estimating standard errors and confidence intervals as well as its cost-effectiveness in avoiding the need to conduct the operation to get additional groups of sampled data.
Therefore it can be concluded that the said query statement is true.
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The thing you have to figure out about this is the distance for each person and the time it takes for the biker to meet the runner. The rates we are told. The formula is distance = rate times time. Let's do that for the runner first. His rate is 6 so the formula so far is d = 6t. Now let's work on the time. If the biker left an hour later than the runner, then the runner has been running an hour more than the biker. Therefore, the runner's time is t + 1. Hold off on the distance part til we do for the biker what we just did for the runner. The biker's rate is 14, and we already decided that his time is t. His equation is d = 14t. Now at the exact moment the biker meets the runner their distances are the same. So if the equation for the runner is d = 6t + 6 and the equation for the biker is d = 14t and their distances are the same, by the transitive property, their rates and times are the same as well, meaning we set them equal to each other and solve for t. 6t + 6 = 14t. 6 = 8t and t = 3/4. This means that it took 45 minutes for the biker to meet the runner.