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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).
applications of normal probability distribution
Test for Equality of Proportions For example, we may want to test whether the percentage of smokers (p 1 ) among the males equals the percentage of female smokers (p 2 ). W
Accident proneness A personal psychological issue which affects the individual's probability of suffering the accident. The concept has been studied statistically under the num
mle
Solve the following Linear Programming Problem using Simple method. Maximize Z= 3x1 + 2X2 Subject to the constraints: X1+ X2 = 4 X1 - X2 = 2 X1, X2 = 0
(a) At a stream gauging station, the following discharges and stage measurements were taken for the purpose of the rating curve at that section: Stage (m) 1
find the expected value of the mean square error and of the mean square reggression
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
In New Jersey, banks have been charged with withdrawing from counties having a high percentage of minorities. To substantiate this charge, data is presented in the table below conc
What does the confidence level of a confidence interval tell you? Suppose that a population has mean, µ, and standard deviation, σ. What does the central limit theorem tell us
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