Question

The CEO of a local tech company wants to estimate the proportion of employees that are pleased with the cleanliness of the breakrooms. She considers two methods of obtaining a sample of 600 employees from the 4,700 employees at the company. Part A: To make the process easier, the CEO considers surveying the first 600 employees who enter a company annual conference center. Identify the type of sampling method proposed and discuss why this sampling method might be biased. (5 points) Part B: The second method the CEO is contemplating involves a stratified random sample of 600 employees. The company has two campuses with male and female employees at each campus. What circumstances would stratification by campus give a more precise approximation of the proportion of employees who are satisfied with the cleanliness of the breakrooms than stratification by gender? (5 points)(10 points)

Answer 1

Answer:

Methods of obtaining a sample of 600 employees from the 4,700 workforce:

Part A:  The type of sampling method proposed by the CEO is Convenience Sampling.

Part B: When there are equal number of participants in both campuses, stratification by campus would give a more precise approximation of the proportion of employees who are satisfied with the cleanliness of the breakrooms than stratification by gender.  Another method to ensure that stratification by campus gives a more precise approximation of the proportion of employees who are satisfied with the cleanliness of the breakrooms than stratification by gender is to ensure that the sample is proportional to the proportion of each campus to the whole population or workforce.

Step-by-step explanation:

A Convenience Sampling technique is a non-probability (non-random) sampling method and the participants are selected based on availability (early attendees).  The early attendees might be different from the late attendees in characteristics such as age, sex, etc.  Therefore, sampling biases are present.  All non-probability sampling methods are prone to volunteer bias.

Stratified sampling  is more accurate and representative of the population.  It reduces sampling bias.  The difficulty arises in choosing the characteristic to stratify by.