Validity and Reliability
Reliability and Validity When examining the data they have collected, it is essential for researchers to determine to what degree is their data consistent. There are many methods by which researchers can assess the reliability of their instruments. Through different statistical procedures, researchers will evaluate the reliability coefficient to ascertain to what extent their data is consistent. The reliability coefficient is generally a numerical value between 0.00 and 1.00, where the coefficients of reliability are numerical values close to 1.00. The test-retest approach to reliability is used to assess how consistent a measured group of subjects tested with the same measuring instrument remain over time. Using this method, a researcher administers the same test twice to the same group of people, using the same measuring instrument, with the two test separated by a period of time. The researcher then compares the sets of scores and the resulting correlation coefficient is known as the test-retest reliability coefficient, or coefficient of stability. It is important to note that the amount of time elapsed between the two tests will most probably effect the coefficient of stability. For instance, if a group of students were to take the same mathematics test two weeks apart, it is likely that they will produce similar results. However, should the group of students take the mathematics test once at the beginning of the school year and once at the end of the school year, the scores may vary since the lessons taught in the interim will provide the students with more knowledge that will enable them to perform better on the exam. Another disadvantage regarding the test-retest approach is that the subjects may remember the questions from the first test, which would enable them to produce a better score on the retest. The test-retest reliability method is often used for cognitive test and characteristic skills. Generally, this approach to reliability is
References: [1] Huck, Schuyler. (2008). Reading statistics and research. Allyn & Bacon. [2] Shuttleworth, Martyn (2009). Construct Validity. Retrieved [June 13, 2010] from Experiment Resources: http://www.experiment-resources.com/construct-validity.html Read more: http://www.experiment-resources.com/construct-validity.html#ixzz0qlmk88Rt