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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).
Problem : A company supplying electrical products, places a rush order for electric wires. Consignments of wires are to be sent immediately when they are available. Previous
A sample of 43 houses that were purchased in the Southern California town Monrovia within a month was collected. We are interested in the study of the relationships between Price a
Type of Correlation 1. Positive and Negative Correlation: 2. Simple Partial and Multiple Correlations. 3. Linear and Non linear or Correlations
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Statistics Can Lead to Errors The use of statistics can often lead to wrong conclusions or wrong estimates. For example, we may want to find out the average savings by i
Ask question #Minimum The data in the accompanying table give the weights? (in g) of randomly selected quarters that were minted after 1964. The quarters are supposed to have a med
Regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Mathematical Properties The sum of deviations of the items from the arithmetic mean (taking signs into account) is always zero, i.e. = 0. The sum of
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Types of business forecasting are generally as follows: 1. Sales and Demand forecasts 2. Porduction forecasts. 3. Cost Forecasts 4. Financi
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