The equation for standard error is derived assuming that all samples are independent . This is a very strong assumption which is unrealistic in many situations. Samples separated by small distance are often positively correlated. Before using standard statistics it is important to test if samples are correlated. Spatial correlations are examined using geostatistics.
Correlation decreases with distance between samples as shown below.
Standard statistics can be applied only if inter-sample distance exceeds the range of the correlogram. However, this rule is not universal The only thing that matters in statistics is testing hypotheses. If null-hypothesis is rejected then it does not matter whether A was above or below 0.05. However, in each specific research area, it is useful to find a precision level which is usually sufficient for rejecting null-hypotheses. If EIL is within the c.i. for M , then the null-hypothesis cannot be rejected and no decision can be made.