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A real estate agent in the coastal area of Georgia wants to compare the variation in the selling price of homes on the oceanfront with those one to three blocks from the ocean. A sample of 21 oceanfront homes sold within the last year revealed the standard deviation of the selling prices was $45,600. A sample of 18 homes, also sold within the last year, that were one to three blocks from the ocean revealed that the standard deviation was $21,330. At the .01 significance level, can we conclude that there is more variation in the selling prices of the oceanfront homes?
Explain briefly and in nontechnical language what "a significant difference (P
State the formula for the test statistic and show your decision rule using the 1 percent level of significance. (c) Carry out the test. Show your work. (d) What assumptions are required?
Prove that there is a sequence of polynomials p_n on [0,1] such that p_n ----> 0 pointwise on [0,1] but the integral from 0 to 1 of p_n dx
How many data points can she use in a regression analysis using the data provided.
The sample mean is 50, the t-critical value is 1.96, and the standard error of the sample mean is 2.
Write a paragraph or two summarizing what you can conclude from the summaries you generated. You should address the central tendency, variability, and shape of the data.
What different types of variables are used in quantitative studies? Describe each type of variable and how they differ.
One use of the Chi-square goodness of fit test is to determine if specified multinominal probabilities in the null hypothesis is correct.
A textile manufacturer estimates that it produces bolts of cloth with flaws following a Poisson distribution that has an average of one flaw per 200 feet of cloth.
An appliance manufacturer claims to have developed a new toaster oven that consumes an average of no more than 250 W. From previous studies, it is believed that power consumption for toaster ovens is normally distributed with a variance of 324 W.
Where should the warranty limits be set so that only 10% of the TVs need repairs at the manufacturer's expense?
Let ≥ represent the true average area (in square feet) of these apartments. What are the appropriate null and alternative hypotheses?
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