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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).
Estimate a linear probability model: Consider the multiple regression model: y = β 0 +β 1 x 1 +.....+β k x k +u Suppose that assumptions MLR.1-MLR4 hold, but not assump
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The first step in this case is to ensure that you are adequately clear on the General Linear Model and its relationship to both ANOVA and regression. The distinction is approxim
advantage and disadvantage
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Find the Relation between two substance: The following table shows the results obtained in experiments aimed to determine how solubility of water in benzene depends on tempera
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