Water Transfer Utility

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July 28th, 2010 admin Leave a comment Go to comments

Water Transfer Utility

statistical hypothesis testing, a problem of tail?

Brigsby Financial Consulting, said the bill quarterly average Water U.S. $ 47.50. Some are publicly managed and some are private. An economist said that the privatization of competition is not equal and that monopoly power to provide public services are transferred to private companies. The problem is that consumers end up paying more than the average water supplied by private companies. A sample of 64 consumers in Atlanta was a water bill quarterly average $ 51 with a standard deviation $ 12. A (symbol) = 0.05, "Atlanta sample supports the conclusion that rates are higher than average This private water system? What is your conclusion?

Since we want to test if the true average water bill, μ, is greater the average publication: μ ₀ = 47.50, we will let our alternative hypothesis is: H_a: μ> μ ₀ so that the null hypothesis is H = ≤ ₀ μ μ ₀. We envision that the sample mean x-bar = 51 and the number of samples is n = 64. Since we we are only given the sample standard deviation, s = 12, we will be using the t test to determine whether the data support the alternative hypothesis. If you use a calculator with a built-in t-test, is the point where you simply plug the observed data Select the correct alternative hypothesis and get some results. If this is the case, you can skip the rest of the answer. However, if this is not the case, we need to calculate the T statistic: T = (x-bar - μ ₀) / (s / √ n) t = ((51) - (47.5)) / (12 / √ 64) = 3.5 / (12 / = (7 / 2) (2 / 3) = 7 / 3 = 2.333 ... We will use a t-table to determine the critical value for our confidence level α = 0.05. Since we have n = 64, our degree of freedom df = n-1 = 63. Most T-tables do not have a line for df = 63, it is to use the line Next in small-df = 60. We waited until the value α = 0.05 critical to ensure that the critical value is 1.671. So from our t-statistic = 2.333 ... exceeds the critical value (ie, our data has enabled more than half the chance), we affirm that the information collected is sufficient to reject the null hypothesis and say that the water bills are higher than average. Done and done.

City-County Council approves the transfer utility and County Council approved the transfer of water and city water services treatment for the citizens of Energy Monday Group.