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• W2766709867 abstract "Data from published studies is used to recover information about the sample mean self-reported number of times cheated by college students. The sample means were estimated by fitting distributions to the reported data. The few estimated sample means thus recovered were roughly 2 or less. Keywords: cheating, self-reports The mean is perhaps the most important statistic to be calculated from a sample. Nevertheless, Liebler (2016) discovered in a literature search that among the hundreds of surveys found on student cheating, none stated the sample mean self-reported number of times cheated, and (2) none collected and reported [frequencies] for each [self-reported number of times cheated]. Thus, the sample mean cannot simply be read in these papers or calculated from data reported in these papers; instead it must be estimated. The goal in the present paper is to use data reported in published studies to recover information about the sample means. An example Let q be the self-reported number of times cheated by a student. As a first attempt at estimating the sample mean, [??], consider the method of weighting the midpoint of each class of q by the fraction of students reporting a q in this class. For example, applying the midpoint method to the data set shown in Table 1 for McCabe (1992) yields the midpoint estimate of the sample mean, m. [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] In this equation, L is the largest q . Although L is not reported, it is possible to get a rough idea of the potential range of L. Suppose that the typical course has 4 assessment instruments (e.g., 2 exams, 1 set of quizzes, and 1 paper) and the typical student takes 5 courses per semester. In this case, the typical student experiences 20 assessment instruments per semester. McCabe (1992) reports that his sample consists of 88% seniors, 9% juniors, and 3% unclassified. Therefore, suppose that the typical student in his sample had completed 6 semesters at the time of the survey. Because McCabe (1992) asks students to self-report the number of times cheated while in college, the typical student had experienced 120 assessment instruments at the time of the survey. Thus, L potentially ranges from 5 to 120. To see the effect of L on [??], substitute various L into the equation for [??]. For example, for L = (6, 30, 60, 120), this yields [??] = (2.1, 4.4, 7.3, 13.0). In this example, [??] depends crucially on L, and the range of [??] is large. In my opinion, without a plausible way to estimate L, the midpoint method is not satisfactory. Method The criteria for papers to be included in the analysis are the same as in Liebler (2016): (1) the paper reported numerical data on self-reports of the number of times undergraduates in the United States cheated during some period in college; (2) the paper reported self-reports of the number of times cheated by using either (a) categories containing one number, or (b) at least three categories if some categories contain more than one number; and (3) the paper was published by 2013. Nine papers satisfy the criteria. One paper was excluded because students were asked to report the average number of times cheated instead of the number of times cheated. One paper was excluded because of inconsistencies in the reported data. Thus, of the 222 papers containing surveys on student cheating, this leaves only 7. Data from these 7 papers (hereafter, Papers) is shown in Table 1; two papers appear twice. Each data set will be referred to by first author only, except that two data sets from the same paper will be differentiated by clarifying words. The data is the same as in Liebler (2016) except that for Premeaux, data from tier 2 schools is also included. Several well-known distributions were examined as possible fits to the data. Table 2 shows the probability density functions, pdf's, of the distributions that produced a satisfactory fit. …" @default.
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• W2766709867 date "2017-09-22" @default.
• W2766709867 modified "2023-09-24" @default.
• W2766709867 title "Estimates of the Average Number of Times Students Say They Cheated." @default.
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