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A manufacturing company has two factories F1 and F2 producing a certain commodity that is required at three retail outlets M1, M2 and M3. Once produced, the commodity is stored at one of the ve company warehouses, W1;W2;W3;W4;W5 from where it is distributed to thevarious retail outlets. It is not feasible to move the commodity from a warehouse to a factory, nor is it feasible to move the commodity from a retail outlet to a warehouse. The tables below give the maximum weekly amount of the commodity that can be moved from factory Fi to warehouse Wj and from warehouse Wj to retail outlet Mk. Maximum weekly movement of the commodity between warehouses is indicated in the network shown below. Each factory F1 and F2 has a weekly production capacity of 60 units. Using an appropriate network, determine the maximum amount of the commodity that can be supplied to the markets.
The division of a sample of observations into several classes, together with the number of observations in each of them. It acts as a useful summary of the main features of the da
Lorenz curve : Essentially the graphical representation of cumulative distribution of the variable, most often used for the income. If the risks of disease are not monotonically in
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if |t | > t = 1.96
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
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The risk of being able to recognize the respondent's confidential information in the data set. Number of approaches has been proposed to measure the disclosure risk some of which c
Ask questioThe finance manager of ‘Softy’ baby soap manufacturing company being successful in the first two years of the company’s operations is considering setting up another plan
The Current status data arise in the survival analysis if the observations are limited to the indicators of whether or not the event of interest has happened at the time the sample
Kaiser's rule is the rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati
Complier average causal effect (CACE): The treatment effect amid true compliers in the clinical trial. For the suitable response variable, the CACE is given by the difference in o
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