Bias+and+Precision

Here's what we know about bias and precision:

**Bias**
Within a statistical sampling or testing error caused by systematically favoring an outcome is referred to as bias. The error is a consistent, repeated deviation of the sample statistic from the population in the same direction. Within the field of statistics there are several different types of bias not limited to; selection bias, response bias, sampling bias, funding bias, spectrum bias, and bias of the estimator. To reduce bias the surveyor __must__ use a random sample. Simple random sampling produces unbiased estimate-neither consistently overestimated or consistently underestimated.

**Precision**
Larger samples will produce a more precise and unbiased data. If a sample is reproducable, or can be repeated, to produce the same results, it is determined to be highly precise. //Source:// [|http://water.epa.go][|v/grants_funding/beachgrants/app4b1.cfm]
 * It is pertinent to strive for a sample survey which is __highly precise__ with __ little-to-no bias .__**
 * ICON || BIAS || PRECISION ||  ||
 * A || High || Low ||  ||
 * B || Low || Low ||  ||
 * C || High || High ||  ||
 * **D** || **Low** || **High** ||