Finding the bias of a random sample

In summary, the conversation discusses a study to estimate the proportion of residents in a city who support the construction of a new bypass road. A random sample of 2025 residents were polled and the number in the sample who supported the proposal was denoted by X. To estimate the true proportion in support, the formula p = (X + sqrt(2025)/2)/2025 was used. The question then asks for the bias of the estimator p, which can be found by comparing the expected value of p to the mean of the population.
  • #1
hahaha158
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Homework Statement


In a study to estimate the proportion of residents in a city that support the construction of a new bypass road in the vicinity, a random sample of 2025 residents were polled. Let X denote the number in the sample who supported the proposal. To estimate the true proportion in support of the plan, we can compute p =(X+sqrt(2025)/2)/2025. What is the bias of the estimator p?

Homework Equations

The Attempt at a Solution



I am not too sure how to find the bias, can someone tell me what formula I am looking for, or how I should start?

All I could find was on wikipedia that the bias is Expected value(θ' - θ). I am assuming θ' is 2025? How do I continue from here?
Thanks
 
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  • #2
hahaha158 said:
I am not too sure how to find the bias, can someone tell me what formula I am looking for, or how I should start?

The estimator p is a random variable. To see if it is biased, you must find it's expected value and the compare the expected value to the mean of the population. Using "E()" to denote "expected value of", start by writing E(p) = E( ( X + sqrt(2025)/2)/2025 ). You have use facts about the expected values of sums of random variables and the expected value of the product of a constant times a random variables.
 

Related to Finding the bias of a random sample

What is a random sample?

A random sample is a subset of a larger population that is selected in a way that each individual in the population has an equal chance of being chosen. This is important in research as it allows for the generalization of findings to the larger population.

Why is finding the bias of a random sample important?

Finding the bias of a random sample is important because it allows us to understand any potential flaws or limitations in the sample. If a sample is biased, the results may not accurately represent the larger population, and any conclusions drawn from the sample may be inaccurate.

How is the bias of a random sample measured?

The bias of a random sample can be measured by comparing the characteristics of the sample to the characteristics of the larger population. This can be done through statistical tests or by examining the methods used to select the sample.

What are some examples of biased random samples?

Some examples of biased random samples include convenience samples, where individuals are chosen based on their accessibility, and voluntary response samples, where individuals choose to participate in the study. These samples may not accurately represent the larger population and can lead to biased results.

How can we reduce bias in a random sample?

To reduce bias in a random sample, researchers can use random sampling techniques, such as simple random sampling, stratified sampling, or cluster sampling. These methods help to ensure that each individual in the population has an equal chance of being selected for the sample, reducing the potential for bias.

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