Internet Technology Fundamentals To use a passing score at the percentiles listed below: PASS candidates with this score or HIGHER: 2.90 High Scores Medium Scores Low Scores Percentile Rank Proficiency Score 95 th 3.97 90 th 3.84 85 th 3.73 80 th 3.64 75 th 3.55 70 th 3.47 67 th 3.42 65 th 3.40 60 th 3.33 55 th 3.25 50 th (median) 3.18 45 th 3.11 40 th 3.04 35 th 2.97 33 rd 2.95 30 th 2.90 25 th 2.82 20 th 2.73 15 th 2.64 10 th 2.53 5 th 2.39 Mean (Avg) Score 3.184 Standard Deviation 0.483 Number of Cases 1119 * Example: to use a passing score at the 30 th percentile for Proficiency Score, pass candidates who have a Proficiency Score of 2.90 or higher.
Relative Frequency 0 1 2 3 4 5 Proficiency Score
Using the Norms Table Sample Norms Table The table below shows a portion of a typical norms table. To simplify the table, the percentiles in the middle have been left out. The numbers in [brackets] in the table link to the notes in the right-hand column, which explain how to read the table. To use a passing score at the percentiles listed below... PASS candidates with this score or HIGHER [2] PASS candidates with this score or LOWER [2] Percentile Rank Number of Correct Answers Time Taken 95th 105.2 [3] 4:20 90th 103.4 [5] 4:20 80th 97.5 [5] 4:45 [1] 75th 97.1 5:01 25th 43.4 9:09 20th 40.9 9:31 10th 36.7 9:47 5th 31.0 10:22 [4] Mean [Avg] Score 84.6 6:27 Standard Deviation 19.3 3:06 Number of Cases 912 912 [1] The table shows which percentile ranks are associated with which scores. The 80 th percentile for Time Taken is 4 minutes and 45 seconds. [2] Better scores are always associated with higher percentiles. For Time Taken, a shorter time is a better score; therefore, shorter times are associated with higher percentiles, and longer times with lower percentiles. For Number of Correct Answers, a higher number is better, so higher scores are associated with higher percentiles and lower scores with lower percentiles. [3] A candidate who scored 107 correct answers could be described as above the 95 th percentile or in the top 5 percent. [4] A candidate whose time was 10:35 could be described as below the 5 th percentile or in the lowest 5 percent. [5] A Number of Correct Answers of 98 is not listed in the table. A candidate with 98 correct answers is between the 80 th and 90 th percentiles. For decision-making purposes, they would be classified as scoring at the 80 th percentile because they didn t reach the value required for the 90 th percentile.
Reading The Norms Table The norms table enables the reader to determine how the performance of a specific test taker compares to the performance of other test takers. It contains the test scores that correspond to various percentiles in the score distribution. To use the norms table to evaluate the score of an individual compared to all people who have taken the test, find the individual s score in the appropriate column. Follow the row containing the individual s score across to the left-most (Percentile Rank) column to find the percentile rank corresponding to the individual s score. If the individual s exact score is not listed in the table, they should be assigned the highest percentile value for which they qualify. For example, if the test taker s score is between the 55 th and 60 th percentile, they should be classified as scoring at the 55 th percentile. Definitions Percentile Rank... In general, the percentile rank is the percentage of test takers who scored less well than the given score. Thus, for scores for which a higher score is better (for example, percent correct), an individual s percentile rank is the percentage of test takers who had a lower percent correct. For scores for which a lower score is better (for example, number of errors), an individual s percentile rank is the percentage of test takers who had more errors. If the 75 th percentile on a certain test corresponded to a score of 68, this would mean that 75% of test takers scored below 68. A test taker who scored 68 on that test is at the 75 th percentile, or in the top 25%. Also, the percentile rank indicates what percentage of test takers would fail if a certain score is used as a passing score. For example, if the passing score is set at the 30 th percentile, we would expect approximately 30% of test takers to fail the test. Percentile... the test score associated with a given percentile rank. For example, if 75% of test takers scored below 68, then 68 would be the 75 th percentile; we could also say that the percentile rank associated with 68 is 75. In other words, the percentage of test takers below the score is the percentile rank, and the score itself is the percentile. Median... the test score corresponding to the 50 th percentile. By definition, half of the test takers will have scores below the median, and half will have scores equal to or greater than the median. A test taker who scores at or above the median is thus in the top half of the group. The median is one kind of average score. Mean... the traditional average value, calculated by finding the sum of all scores and dividing by the number of scores. The mean score will not necessarily be equal to the median score. Standard Deviation... a statistical term that describes how widely spread the test scores are about the mean. A small standard deviation means most people scored in a narrow range of scores; a large standard deviation means the scores were spread widely. The standard deviation can also be used to interpret an individual s score: if the test taker s score is within one standard deviation above or below the mean, the individual can be considered to be relatively close to average. Using Norms to Make Pass/Fail Decisions When using tests that report more than one score, an organization must decide which score or which set of scores to use in their decision-making process. If they use several scores, they face the additional choice of whether to set a passing requirement for each score separately, or to base the passing requirement on a single number derived from a combination of the scores. SHL Professional Services can provide assistance to organizations in choosing the best way to use test scores in their decision making.
When organizations set passing scores (also called cutoff scores, or cut scores), there are two basic approaches: (1) They can set a passing score designed to eliminate a certain percentage of candidates, or (2) they can set a passing score at the score level that reflects their desired level of test performance. Norms can be useful with either approach. If the intent is to eliminate a certain percentage of candidates, the company can use the fact that the percentile rank indicates what percentage of test takers would fail if a certain score is used as a passing score. For example, if the company wishes to eliminate the lowest 25 percent of candidates from the selection process, they should set their passing score at the 25 th percentile. The employer can use the norms table to learn what test score is the 25 th percentile, and then use that score as the requirement. For employers that take the second approach, the norms can be used to estimate the effects of their decision. For example, if an employer decides to require a typing speed of 30 net words per minute, they can look at the norms table to see what percentile that represents. That percentile will be an estimate of what percentage of candidates will fail to achieve the 30 words per minute requirement. Interpreting The Graphical Display The graphical displays provide a quick way to learn how a specific test taker s score compares to the performance of other test takers. They also illustrate how difficult a test is and how test takers in general perform on the test. The graphs show the distribution of scores for all test takers. The horizontal axis displays the score and the vertical axis displays how many test takers achieved each score. To use the graph, simply locate the individual s score along the horizontal axis. The individual s standing in the group can be determined visually by noting whether the score places them toward the right end of the distribution (among the highest scorers), the left end of the distribution (among the lowest scorers), or more toward the middle. The relative height of the curve indicates how common the score is; if the individual s score is near the high point of the curve, he or she has a very common score; if the individual s score is where the curve is not very high, he or she has a score that is either much higher or much lower than the scores of most test takers. Note that, depending on the nature of the score, a high score is not necessarily a good score. If the score reflects the number of errors, for example, a lower score is more desirable, and the left end of the scale indicates better performance than does the right end. In such a case, a candidate who scores lower than most others would be a better candidate.
Relative Frequency Sample Graph of Test Scores A score of 75 puts an individual in a region where the curve is relatively high above the axis, indicating that it is a common score. The graph shows that scores from about 65 to 85 are very common. A score of 25 is a very low score. Not many people scored lower. A score of 50 is in the middle of the range of possible scores, but the graph shows that most people scored higher than 50. A score of 95 is a very high score. Not many people scored higher. 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Score