Ecolab, a major multinational corporation headquartered here in the Twin Cities,

Question

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

R & D

Production/ Manufacturing

Support

(IT, legal, etc)

Headquarters (MN)

Other North America

Asia / Pacific

Latin America

Africa & Middle East

-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

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

Explanation / Answer

a) Different geaographies could be represented as different clusters for cluster sampling. Thus, the cluster sample would look like different cluster are from different geaographies. eg: Headquarters employees are in Cluster 1, other north america in Cluster 2 etc.

b) Selection bias may occur as the groups that are considered are different as they are from different geaographies and different departments.

Also, measurement bias couls also happen because 47000 is a huge number and all the respondants may not reply thus that would distort the samples demography and hamper the result.

c) Operationalization helps to define all the variables into some measurable factors to develop the output of the survey. Poor operationalization may lead to wrong interpretation of the surveys gathered thus, the results of the survey could be distortes.

Eg: If we want to compare results of protein with milk and water

We can operationlize it with the below hypothesis :

Use of protein with milk results in better result than protein with water

But instead of the above hypothesis, if the hypothesis is dedined as:

Protein results in better muscle

Then we may prove that protein gives better muscle but we will not be able to find that with what protein works better, milk or water.

Such poor operationalization could be improved by first paying attention to what we want to find out and then include all such variables into our hypothesis.

Related Questions

Navigate

• Browse (All)
• Browse E
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.