A sample data is used to make decisions through different analysis. The confidence interval explains the level of uncertainty that is in a particular statistic. The value of confidence intervals explains how much one can be confident that the results of a data analysis reflect the expectations. The intervals are determined using the confidence levels and 95% level shows that the data is valid.
From a sample of 368 pallets of Boston shingles, the confidence interval is from 3120.668 to 3127.761. With the 330 pallets of Vermont shingles the confidence interval is from 3698.998971 to 3709.085877. Based on both estimates, the assumptions required to construct the confidence interval are valid. My conclusion is that it is easier to predict the weight and values of a given data in cases where the confidence interval does not deviate far away from the mean. Thus, it is easier to make a prediction in Boston since the confidence interval is closer at 7.09 as compared to that of Vermont at 10.
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For the insurance claims, the confidence interval of all injury files with exaggerated loss amounts is from.4637 to 0.6696. The confidence interval of the dollar excess payment amount is from 138.769 to 499.727. It is difficult to predict the excess payment amount since the variable from the mean is 360 but can be easier to estimate the files used to make excess payments.
