Evaluation of the divergence of syllabusand questions using the goodness-of-fit test and the Jeffrey index (Case study: Graduation test statistics course questions 1393-1393)

The purpose of this study is to investigate the divergence of the questions of the master's and doctoral exams of a number of statistical courses during the years 1397-1393 from the topics approved by the Supreme Planning Council. For this purpose, the main topics and sub-topics (with the title of main cluster, sub-cluster and topics) were first identified based on the course titles approved by the Ministry of Science, Research and Technology, on which the master's and doctoral entrance exams are designed. In the next step, the frequency distribution of the mentioned test booklet questions in specific time intervals in each topic was extracted and the distance of this distribution of questions in the clusters with the ideal and expected distribution of specialized experts was calculated and tested. The Chi-square test was used to examine the divergence and the Jeffrey index was used to evaluate the good fit of the two distributions as well as the information distance. The sample studied in this study is a case study consisting of a total of eight courses, two courses "Statistics and Experimental Design" in the master's degree exam in agricultural engineering and also four specialized master's degree courses in statistics (mathematical statistics, regression, sampling and basics of probability) And two specialized doctoral courses in this field (probability and statistical inference). The results show that out of eight non-specialized courses in only one course (experimental design in the field of agricultural engineering) and of course in 2016 the rate of divergence was significant (P-Value = 0.28, Chi-square = 8.88 , Jeffrey). Also, among the specialized courses in the field of statistics, the degree of divergence from the ideal situation for one of the courses (probability course of the doctoral exam in statistics in 1396) is significant (0.46P-Value <0.01, Chi-square = 12.50, Jeffrey =).