Write a response to each discussion
There are several categories of standardized scores. Researchers will commonly use Z, T, Stanine and scaled scores. These scores can be very helpful to researcher in their analysis raw scores. Provided within this paper is an overview and an example of each.
Z-scores help us relate the data to the mean, whether the data is below or above the mean. If a z-score is 0, then the score is identical to the mean score. Furthermore, z-scores can be both positive and negative. Another reason researchers find z-scores so they can compare data sets. One way a z-score can be used is determine a company’s financial stability (Boyte, 2015).
T-scores are commonly used in behavioral, personality and clinical research and test development. T-score is similar to z-scores because of distribution of the score, with t-scores the distribution is 50 and the mean is 0 (Eford, 2015). One way of using t-scores is when representing benchmark scores. In this example, the t-score would eliminate the natural variations between survey questions and provide a way to determine whether scores that are high or low (Unknown, 2017).
Stanine is a system that divides the normal curve into nine equidistant segments, giving it the nickname “standard nine” (Eford, 2015). This score is used to indicate performance on a psychological or educational test. Some may prefer to use stanines scores, as they convert test scores into a single digit. One use of the stanine score is when teachers need to explain test scores to parents: 1-3 is performing below average, a score of 4-6 is average performance and a score of 7-9 is above average performance (Eissenberg & Rudner, 1988).
Scaled scores are commonly used in intelligence, achievement and perceptual reports, scaled score will have a mean of 10 and a SD of 3 (Eford, 2015). The best example to use would be if you are comparing two students who took two completely different test. Let’s say student A took a more challenging test then student B, but got a lower score of 62%. Student B’s test was much easier and he got an 85%. The teacher would then use the scaled score to determine a fair comparison of the two students’ scores.
Standardized scores including z-scores, t-scores, stanine (standard nine), and scaled scores are used in research. However, each standardized score is different from each other. For instance, the mean of a z-score is zero and the standard deviation is one. On the other hand, the mean of a t-score is fifty and the standard deviation is ten. The stanine score or standard nine consists of nine equally distant segments while having a mean of five and the standard deviation of two. The mean of a scaled score is ten and the standard deviation is three. (Erford, B.T., 2015, pp. 264-266). An example as to where you might use each of the four standardized scores is listed below.
· Z-Scores: Kylee is in high school and just received her test results from finals in her History class. Kylee received an 80% on the test and has asked the teacher how well she did when compared to the fifty peers in her class. The teacher would be able to utilize the z-score in determining the percentage that Kylee ranked higher and lower in from the 80% score from the final.
· T-Scores: Jeremy would like to know more about his personality and personality characteristics. By using a t-score, Jeremy can understand the strengths and weaknesses of his personality and personality characteristics compared to others who have taken the personality test.
· Stanine Scores: Maggie’s parents David and Jane are reviewing her test results that were required to every student at the end of the year. Using a stanine score, David and Jane can view the nine segments and see what areas Maggie is excelling in and needs to work on when compared to the other students who had taken the same standardized test.
· Scaled Scores: Bethany is required to take an exam with a passing score of 400. A scaled score is used in this exam, because it provides the ability to be compared to other exams and the scoring of the exam is easier to comprehend.