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For each of the following situations choose the statistical model that you find to be the most appropriate. Justify your choice.
a) We are interested in assessing the effects of temperature (low, medium, and high) and technical configuration on the amount of waste output for a manufacturing plant. Suppose that we have randomly selected 5 technical configurations out of 100 configurations, and we want our conclusions to apply to all 100 configurations.
b) We are evaluating the association between the presence of a very rare adverse event (yes, no) and the treatment received (placebo, new drug) for a group of 100 patients. We want to be able to control for age (in years).
c) We are evaluating the effectiveness of five different diets with respect to weight loss. Fifty women were randomly assigned to each one of the five different diet regimens, and the weight loss during a one year period was recorded.
d) We are interested in evaluating the relationship between the levels of C-reactive protein and the body mass index for a sample of 1000 middle aged African-American women.
e) We are interested in comparing (on average) the housing prices (in thousands of dollars) for five specific locations within the same city. To allow for fair comparisons we will take into account the size of the house (in square feet) and the age of the house (in years).
Simple Linear Regression While correlation analysis determines the degree to which the variables are related, regression analysis develops the relationship between the var
Objective of index numbers
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You have an assembly line which produces 1L bottles of seltzer with a standard deviation of 0.05L. • Assuming the distribution of volume is normal, what is the chance any single
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Examine properties of good average with reference to AM, GM, HM, MEAN MEDIAN MODE
In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o
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