STANDARD ERROR Meaning and
Definition
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Standard error is a statistical term that measures the average amount of deviation or variation between the sample mean and the true population mean of a set of data. It is essentially a measure of the precision or reliability of the sample mean as an estimate of the population mean.
The standard error is derived from the standard deviation, which quantifies the dispersion of the data points within a sample. However, unlike the standard deviation, which characterizes the spread of individual data points, the standard error focuses on the spread of the sample means.
By calculating the standard error, researchers can estimate the uncertainty associated with their sample mean and properly interpret the significance of their findings. It provides a measure of how representative the sample mean is likely to be when compared to the population mean.
Typically, as the sample size increases, the standard error decreases, indicating increased precision. This reflects the fact that larger sample sizes tend to yield more reliable estimates of the population mean.
The standard error is widely used in hypothesis testing, as it helps in determining the statistical significance of the results. It is also employed in constructing confidence intervals, which provide a range of values within which the population mean is likely to fall.
Common Misspellings for STANDARD ERROR
- atandard error
- ztandard error
- xtandard error
- dtandard error
- etandard error
- wtandard error
- srandard error
- sfandard error
- sgandard error
- syandard error
- s6andard error
- s5andard error
- stzndard error
- stsndard error
- stwndard error
- stqndard error
- stabdard error
- stamdard error
- stajdard error
- stahdard error
Etymology of STANDARD ERROR
The word "standard error" has its origins in statistics, where it refers to the standard deviation of a sample statistic. The term "standard" indicates that it is a measure that is commonly used and accepted, while "error" suggests the deviation or variability from the true population value. The concept of standard error allows statisticians to estimate the accuracy of a sample statistic in relation to the population parameter it represents. This term has been in use since at least the early 20th century in the field of statistics.
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