z = ( x – µ ) / (s÷v?) = 1.732050808
P (z > 1.732050808) = 0.041632294
The answer to this question is slightly tricky because it could be considered unusual because there is only a 4.18% chance of occurrence but it may not be unusual because the sample size is very small. I would say it is unusual because this would be the obvious answer.
Variance is also an important factor in data analysis because it shows how close together are occurrences in data. The variance is the the differences between individuals in a group denoted by a numerical value. This is often reflected in relation to the individual and the group mean. This shows the variance between the population and a sample. Variance is important because it represents large differences within research that could represent issues with either the research methodology, or with the the population being studied.
Bias or interpreting errors seem to be a large area of problem. While the math seems pretty straight forward, the real problem would rest in the collection method. “The reliability of a measure indicates the extent to which it is without bias (error free) and hence ensures consistent measurement across time and across the various items in the instrument. In other words, the reliability of a measure is an indication of the stability and consistency with which the instrument measures the concept and helps to assess the “goodness” of a measure.” (Sekaran, U, 2003 p. 203).
Sekaran, U. (2003). Research methods for business: A skill-building approach (4th ed.). New York, NY: John Wiley & Sons.