IMPROVING THE TEACHING OF STATISTICS IN BUSINESS EDUCATION: LESSONS AND REFLECTIONS

摘要: Undergraduate business students in the United States and U.S. - modeled educational institutions, often take a course research methodology or seminar during their final year which requires basic statistics courses as prerequisites. This paper speaks about improving teaching of schools to serve course. It identifies need for change so enable better identify appropriate statistical procedures synthesize results real world project. Revisions syllabi philosophy are suggested. BACKGROUND AND INTRODUCTION The author is at present professor University Puerto Rico has been teaching, both graduate undergraduate levels Rican universities last twenty-five years. Caribbean island territory States; primarily Spanish-speaking but bilingual. Although setting this distinctive, its curriculum similar those methods taught BBA (Bachelor Business Administration) programs throughout States. describes prerequisites many context curriculum. student difficulties using statistics, analyzes her understanding preparation. proposes changes way should be service faculties. where solve life problem. intended an integrating course, expected bring bear knowledge learned field specialty well methodological techniques they have acquired, particularly use spreadsheets software. textbook followed Zikmund’s Research Methods, along with others, one standard texts field. Topics include: process, proposal, secondary primary data, survey design, measurement, scales, questionnaire writing communication results. About third text deals sampling, univariate multivariate statistics. However, these sections not reviewed only want time because two semesters prerequisite first semester includes descriptive probability concepts, distributions, sampling Central Limit Theorem. second begins estimation, hypothesis testing, analysis variance, nonparametric regression correlation analysis. portions applicable include interpretation data graphics. Application relevant hypotheses model building In following important: For design component must draw upon identifying target population, sample frame, size determination design. As analyze survey, able variable type each question, scale calculate example, mean no meaning categorical measured on nominal scale. They state propositions formulate that will later test. also testing. arriving valid write conclusions