Definition Of Bias In Statistics
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Let us consider an example in case you have the rule to evaluate the mean of the population.
Definition of bias in statistics. It is the tendency of statistics that is used to overestimate or underestimate the parameter in statistics. A bias is the intentional or unintentional favoring of one group or outcome over other potential groups or outcomes in the population. Bias can seep into your results for a slew of reasons including sampling or measurement errors or unrepresentative samples. The bias of an estimator of a parameter should not be confused with its degree of precision as the degree of precision is a measure of the sampling error.
In statistics bias is a term which defines the tendency of the measurement process. Bias in statistics is a term that is used to refer to any type of error that we may find when we use the statistical analyses. These biases can come in the form of two main categories. We can say that it is an estimator of a parameter that may not be confusing with its degree of precision.
To understand the difference between a statistic and a parameter see this article. It means that it evaluates the over or underestimation of the value of the population parameter. Bias is important not just in statistics and machine learning but in other areas like philosophy psychology and business too.
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