Microsoft Word research method fm doc

 
a) Sampling error (i.e., random error) 
Random error, the opposite of reliability (i.e., Precision or repeatability), consists of random 
deviations from the true value, which can occur in any direction.
Sampling error (random error) can be minimized by increasing the size of the sample. 
 
Reliability
(or precision): This refers to the repeatability of a measure, i.e., the degree of 
closeness between repeated measurement of the same value. Reliability addresses the 
question, if the same thing is measured several times, how close are the measurements to 
each other? 

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Research methodology 
45
The sources of variation resulting in poor reliability include:
a) Variation in the characteristic of the subject being measured. Example: blood pressure 
b) The measuring instruments, e.g. questionnaires 
c) The persons collecting the information (observer variation)
Inter-observer variation:
differences between observers in measuring 
the same 
observation
Intra-observer variation:
differences in measuring the same observation by the same 
observer on different occasions. 
 
b) Non Sampling error
(i.e., bias) 
Bias, the opposite of validity, consists of systematic deviations from the true value, always in 
the same direction.
It is possible to eliminate or reduce the non-sampling error (bias) by careful design of the 
sampling procedure. 
Validity:
This refers to the degree of closeness between a measurement and the true value 
of what is being measured. Validity addresses the question, how close is the measured 
value
to the true value? 
 
To be accurate, a measuring device must be both valid and reliable. However, if one cannot 
have both, validity is more important in situations when we are interested in the absolute 
value of what is being measured. Reliability on the other hand is more important when it is 
not essential to know the absolute value, but rather we are interested in finding out if there is 
a trend, or to rank values.