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1. Instructions: Please provide a summary of Chapter 7.

   ( Human Resource Selection, 8th Edition Ebook Author(s): Robert D. Gatewood, Hubert S. Field chapter 7) The term reliability has a host of definitions. In our discussion, we will touch on several of these. But for now, we want to consider a fundamental definition of the concept. In the context of HR selection, reliability simply means the degree of dependability, consistency, or stability of scores on a measure used in selection research (either predictors or criteria). In general, the reliability of a measure is determined by the degree of consistency between two sets of scores on the same measure. In our earlier selection example, we would have expected the programming aptitude test to yield similar results from one testing period to the next if the test produced reliable data. Because the results were not similar, we would probably conclude that the test contained errors of measurement. Thus, attempts to establish the reliability of ascore produced by a measurement procedure involve the careful study of the sources of error during measurement that cause variance in or inconsistency of scores over replications of that assessment. Reliability is trying to account for the expected degree of consistency in scores orerrors of measurement.Errors of Measurement It is important to keep in mind that reliability deals with errors of measurement. In this sense, a measure that is perfectly reliable is free of errors. None of our selection measures, whether predictor or criterion, will be free of measurement errors (although such errors tend to be less frequent with measures of physical attributes relative to measures of unobservable psychological characteristics). Selection measures designed to assess important job-related characteristics (such as knowledge, skills, and personality traits) may be prone to error due to the sample of items used, the test taker, the examiner, and the situation in which testing takes place. In general, the greater the amount of measurement error, the lower the reliability of a selection measure; the less error, the higher the reliability. Thus if errors of measurement can be assessed, a measures reliability can be determined. What, then, areerrors of measurement?When we use selection devices such as tests, we obtain numerical scores on the measures. These scores serve as a basis for selection decision-making. Because we are using scores as a basis for our decisions, we want to know thetrue scores of applicants for each characteristic being measured. For example, if we administer a mathematics ability test, we want to know thetrue math ability of each test taker. But unless our measure is perfectly reliable, we will encounter difficulties in knowing these true scores. In fact, we may get mathematics ability scores that are quite different from the individuals true abilities. Lets see why. The score obtained on a measurethat is, the obtained scoreconsists of two parts: a true component and an error component. The components of any obtained score (X)can be summarized by the following equation: Xobtained XtrueXerror where Xobtained obtained score for a person on a measureXtruetrue score for a person on the measure; that is; the actual amount of the attribute measured that a person really possessesXerrorerror score for a person on the measure; that is; the amount that a persons score was influenced by factors present at the time of measurement that is unrelated to the attribute measured: These errors are assumed to represent random fluctuations or chance factors: This notion of a score being composed of true and error parts is a basic axiom of measurement theory.6True ScoreThe true score is really an ideal conception. It is the score individuals would obtain if external and internal conditions to a measure were perfect. For example, in our mathematics ability test, an ideal or true score would be one for which both of the following conditions existed:1.Individuals answered correctly the same percentage of problems on the test that they would have if all possible problems had been given and the test was a construct valid measure of the underlying phenomenon of interest (see next chapter).2.Individuals answered correctly the problems they actually knew without being affected by external factors such as lighting or temperature of the room in which the testing took place, their emotional state, or their physical health.Another way of thinking about a true score is to imagine that an individual takes a test measuring a specific ability many different times. With each testing, his or her scores will differ somewhat; after a large number of testings, the scores will take the form of a normal distribution. The differences in scores are treated as if they are due to errors of measurement. The average of all test scores best approximates the test takers true ability.Therefore, we might think of a true score as the mean or average score made by an individual on many different administrations of a measure.This idealized situation does not exist. The notion of a true score, however, helps to define the idea that there is a specific score that would be obtained if measurement conditions were perfect. Because a true score can never be measured exactly, the obtained score is used to estimate the true score. Reliability answers this important question: How confident can we be that an individuals obtained score represents his or her true score?Error ScoreA second part of the obtained score is the error score. This score represents errors of measurement. Errors of measurement are those factors that affect obtained scores but are not related to the characteristic, trait, or attribute being measured.7These factors, present at the time of measurement, distort respondent's scores either over or under what they would have been on another measurement occasion. There are many reasons why individuals scores differ from one measurement occasion to the next. Fatigue, anxiety, or noise during testing that distracts some test takers but not others are only a few of the factors that explain differences in individual's scores over different measurement occasions.

2. All summaries of the assigned weekly chapters must be at least 300 words as thought-out responses are required. The assignments should represent the students careful, thoughtful efforts to cover the key elements of the topic thoroughly.

   Homework assignments should contribute substantive value to the understanding of the subject. Content should go beyond mere description or paraphrasing. Students must always submit work that represents their original words or ideas.

   If any words, ideas, or assignments are not your own, you must cite all relevant sources and make clear the extent to which such sources were used.

   Failure to cite your work will result in the student not receiving full credit for the assignment.