# How do you find the standard error of a point estimate?

**How do you find the standard error of a point estimate?**In

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**To calculate the standard error, follow these steps:**

- Record the number of measurements (n) and
**calculate**the sample mean (μ). **Calculate**how much each measurement deviates from the mean (subtract the sample mean from the measurement).- Square all the deviations calculated in step 2 and add these together:

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.

In this way, what does standard error of estimate mean?

**Standard Error of Estimate**. **Definition**: The **Standard Error of Estimate** is the measure of variation of an observation made around the computed regression line. The smaller the value of a **standard error of estimate** the closer are the dots to the regression line and better is the **estimate** based on the equation of the line

Similarly, what is the error of estimation? Definition of **error of estimate**. : an **error** made by using the equation of a regression line to **estimate** the values of the dependent variable from those of the independent variable.

Just so, how do you find the standard deviation from a point estimate?

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**Example Problem**

- Calculate the mean of the data.
- Subtract the mean from each data point (or the other way around, if you prefer
- Calculate the mean of the squared differences.(4+25+4+9+25+0+1+16+4+16+0+9+25+4+9+9+4+1+4+9) / 20 = 178/20 = 8.9.
- The population standard deviation is the square root of the variance.

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Why is standard error of estimate important?

Although not always reported, the **standard error** is an **important** statistic because it provides information on the accuracy of the statistic (4). And that means that the statistic has little accuracy because it is not a good **estimate** of the population parameter.

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