Question

why does simple random sampling require a field (a list of all individuals in the population) and why does the requirement of a field make collecting a simple random sample difficult?

Answer 1

Typically, research starts with a simple random sample. This gives them the ability to statistically assess a group or population sample taken from a larger one in order to imitate the response of the entire group.

Why does simple random sampling require a field (a list of every person in the population)?

A smaller subset of a larger population is referred to as a simple random sample. Everyone in this area has an equal chance of being chosen. Because of this, a simple random sample is meant to represent the larger group objectively. An plus or minus variant is used to indicate the approach's typical error margin. This is an illustration of a sampling inaccuracy.

Why is it difficult to gather a simple random sample because of a field's requirements:-

- A simple random sample cannot produce an appropriate statistical measure of a large population unless the entire population to be studied is accessible. Think of a list of college students or a team of employees at a specific company.

The problem is the accessibility of these lists. It may be challenging to access the complete list as a result. Some schools and universities might not wish to provide a complete list of their faculty or students to researchers. Similar to this, due to privacy policies, some businesses might not be able or willing to provide information about specific employee groups.

Answer 2

Commonly, research begins with a straightforward random sample. This enables them to statistically analyze a sample of people drawn from a bigger population or group in order to simulate the response of the complete group.

Why does a field (a list of every person in the population) need to be included in simple random sampling?) :-

   - Simple random sample is the term used to describe a smaller portion    of a bigger population. Each person in this area has an equal probability of being selected. For this reason, a straightforward random sample is intended to be impartial in its portrayal of the wider group. This approach typically has an error margin, which is denoted by a plus or minus variant. An example of a sampling error is this.

why does the requirement of a field make collecting a simple random sample difficult :-

    - Only when a complete list of the entire population to be researched is available can a simple random sampling yield an accurate statistical measure of a big population. Consider a list of university students or a group of workers at a particular business.

The availability of these lists is the issue. Accessing the entire list can therefore be difficult. It's possible that some colleges or universities won't want to give researchers an exhaustive list of their faculty or students. Similar to this, some businesses might not be able or willing to provide information about particular employee groups due to privacy policies.

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