Traverse is a method in the field of surveying to establish control networks. It is also used in geodetic work. Traverse networks involved placing the survey stations along a line or path of travel, and then using the previously surveyed points as a base for observing the next point.

Disadvantages. It is less precise compared to other advanced methods of surveying. It is easily subjected to various errors such as errors adjoining to magnetic meridian, local attraction etc. Imperfect sighting of the ranging rods and inaccurate leveling also causes error.

Traverse networks are free of the strength of figure considerations that happen in triangular systems; Scale error does not add up as the traverse is performed. Azimuth swing errors can also be reduced by increasing the distance between stations.

ERRORS IN TRAVERSE SURVEYING

• Instrumental error.
• Personal error.
• Natural error.

Sources of Errors in TraversingSome sources of error in running a traverse are:1. Poor selection of stations, resulting in bad sighting conditions caused by alternatesun and shadow, visibility of inly the rod’s top, line of sight passing too close to theground, lines that are too short, and sighting into the sun.

Errors are normally classified in three categories: systematic errors, random errors, and blunders. Systematic errors are due to identified causes and can, in principle, be eliminated. Errors of this type result in measured values that are consistently too high or consistently too low.

Generally errors are classified into three types: systematic errors, random errors and blunders.

Abbe’s principle states that “maximum accuracy is obtained when the scale and the measurement axes are common”. If the micrometer must be held by hand during measurement then try to minimize contact time.

Note: Violations are classified as human error only when they fail to achieve the desired outcome. Where a violation does achieve the desired outcome, and does not cause any other undesired outcomes, this is not human error.

5 Ways to Prevent Human Error Disasters

1. Training, Training and More Training.
2. Limit Access to Sensitive Systems.
3. Develop a Strong Disaster Recovery Plan.
4. Test your Disaster Recovery Plan.
5. Hold Semiannual or Annual Refresher Courses.

If you reduce the random error of a data set, you reduce the width (FULL WIDTH AT HALF MAXIMUM) of a distribution, or the counting noise (POISSON NOISE) of a measurement. Usually, you can reduce random error by simply taking more measurements.

Random errors will shift each measurement from its true value by a random amount and in a random direction. These will affect reliability (since they’re random) but may not affect the overall accuracy of a result.

A random error in collected data cannot be corrected. For determining the relative deviation in the analysis of a data set. the standard deviation and the average of the data set must be determined. The relative error is an indication of the precision of the collected data.

Random errors can be evaluated through statistical analysis and can be reduced by averaging over a large number of observations (see standard error). Systematic errors are reproducible inaccuracies that are consistently in the same direction. These errors are difficult to detect and cannot be analyzed statistically.

It means that averaging multiple measurements can reduce the variation associated with an individual measurement. If the measurements are accurate, if there is no systematic error, but just random error, then averaging multiple measurements will improve the closeness of the composite measurement to the true value.

An error (from the Latin error, meaning “wandering”) is an action which is inaccurate or incorrect. In some usages, an error is synonymous with a mistake. In statistics, “error” refers to the difference between the value which has been computed and the correct value.

One of the types of error is systematic error, also called bias, because these errors errors are reproducible and skew the results consistently in the same direction. A common approach to identify systematic error is to use control samples with a method comparison approach.

Systematic errors are errors that affect the accuracy of a measurement. Systematic errors are —one-sided“ errors, because, in the absence of other types of errors, repeated measurements yield results that differ from the true or accepted value by the same amount.