"Explaining Unbiased Expression with Probability

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In summary, the concept of unbiasedness in statistics is defined as a statistic being equal to the parameter it is estimating. In the given example, the expression \hat p = \frac{X}{n} is considered unbiased for the parameter p because it simplifies to just p, which is the probability being estimated. It is important to note that the expectation of \hat p is equal to p, not just any value. This concept is crucial in accurately estimating parameters in statistics.
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Homework Statement



In an example my book says that the expression bellow is unbiased.
I can't see why this is exactly...

Homework Equations



[tex]
\begin{array}{l}
\hat p = \frac{X}{n} \\\\
E(\hat p) = E\left( {\frac{X}{n}} \right) = \frac{1}{n} \cdot E(X) = \frac{1}{n} \cdot (n \cdot p) = p \\
\end{array}
[/tex]

The Attempt at a Solution



Could the reason be that the expression comes down to just p, which is simply a probability and we have no better suggestion than to believe that it "hits the target"? (If that didn't make any sense, just ignore it)
 
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A statistic [itex]\tau(x_1,x_2,...,x_n)[/itex] is said to be unbiased for a parameter [itex]\theta[/itex] if [itex]E[\tau(x_1,x_2,...,x_n)]=\theta[/itex].

It is just a definition.

It is important to know that to say that [itex]\hat{p}=\frac{x}{n}[/itex] is unbiased is WRONG. It is unbiased for a particular PARAMETER.

The expectation of [itex]\hat{p}[/itex] is precisely p. If it so happened that [itex]E[\hat{p}]=p-2[/itex] then [itex]\hat{p}[/itex] would not be an unbiased estimator for p, it would be an unbiased estimator for p-2.
 
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What is "Explaining Unbiased Expression with Probability"?

"Explaining Unbiased Expression with Probability" is a scientific concept that refers to using mathematical probability to understand and describe unbiased expressions or behaviors in various scientific fields, such as psychology, sociology, and economics.

Why is it important to study unbiased expression with probability?

Studying unbiased expression with probability allows scientists to better understand and predict human behaviors and decision-making processes. It also helps us identify and address potential biases in research studies, data analysis, and decision-making.

How does probability play a role in explaining unbiased expression?

Probability allows us to quantify and measure the likelihood of certain behaviors or expressions occurring in a given situation. By using mathematical models and statistical analysis, we can identify patterns and trends in unbiased expression and make predictions about future behaviors.

What are some common misconceptions about explaining unbiased expression with probability?

One common misconception is that probability can fully explain and predict human behaviors. While probability can provide valuable insights, it is not the only factor at play in our decision-making processes. Additionally, some may mistakenly believe that probability is biased or subjective, when in fact it is a mathematical concept based on objective data.

How can "Explaining Unbiased Expression with Probability" be applied in real-world situations?

Understanding unbiased expression with probability can be useful in various fields, such as market research, public policy, and social sciences. For example, it can help companies make informed decisions about product development and marketing strategies, or aid in the creation of fair and unbiased policies and laws.

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