Ecolab, a major multinational corporation headquartered here in the Twin Cities, is hoping to conduct an employee satisfaction survey. It wants to recruit a representative sample of 2,500 employees for this survey. Assume the following table represents the sampling frame of Ecolab’s entire 47,000-employee global workforce. Each cell tells us how many employees work in a particular division in a particular region. (Note: this is fake data) Regon Employee Division Management Sales R & D Production/ Manufacturing Support (IT, legal, etc) Headquarters (MN) 3000 2000 5000 1000 500 Other North America 5000 8000 1000 3000 500 Europe 1500 1500 1200 1000 250 Asia / Pacific 1500 2000 1800 3000 400 Latin America 1000 1500 600 1500 150 Africa & Middle East 1000 1000 600 1500 100 -what would a cluster sample look like in this scenario? Explain in a sentence or two, perhaps by giving an example. -Name and briefly describe any two biases that might skew the results of this survey IF the researchers decided to directly email all 47,000 employees instead of using random sampling. In other words, why might the results of a survey sent out to all 47,000 employee’s emails be biased? -POOR OPERATIONALIZATION: Somewhere in the real world, find an example of a poor operationalization of a variable. Please state where you found this example and explain why it is a poor operationalization. Then, either find an example of how it could be improved or recommend a way in which the operationalization could be improved

The cluster would be based geographically and would look like a survey carried out considering samples from three offices from one being headquarters based in US and offices being based out in Europe and Latin America. HQ is being chosen as one sample being representing almost a (true)complete sample as it would represent employees from all others office. Further second stage cluster may be selection of cluster by further selecting the employees (10% each from each region among each division)
Considering just one sampling based on only one region for example only headquarter or be it one continent wouldn’t give true sample as the satisfaction at head office would be very much different from an sub office.
Alternatively, if sampling based only on one or two employee division would also not give true sample.
An email sent to all 47000, would represent a complete sample as the response may be received from all in time. Also the unequal division of employees in all regions would not generate true survey result.
Internal Revenue Service (IRS) selected a random sample (IRS selected sample of 345 returns of the 24,399 identified) .Of the 345 which the IRS reviewed, 313 resulted in needing additional tax assessment. This action led the IRS to draw inferences about the population that were not likely conclusions on their part. Information sought from a paper published on a true case “Random sampling issues in a federal court case, a case study by Kristin Kennedy Bryant University, USA James Bishop Bryant University, USA”
 
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