Diagnosis of the reading and interpretation of statistical graphs by undergraduate students from economic-administrative sciences programs at the University of Guadalajara

Salvador Sandoval,Semei Coronado,Robert Delmas,Victor Gualajara,Pedro Celso-Arellano

doi:10.23913/ride.v11i21.786

Abstract

Recently, statistical reasoning has been of vital importance not only in quantitative analysis but also in the interpretation of graphs at all educational levels. There are students that can make calculations almost immediately but are not able to interpret or present their ideas graphically. In this way, the present study seeks to conduct a diagnostic of the problems that economic-administrative students have when reading and interpreting graphs in their statistics courses. For this, a Spanish version of the test Comprehensive Assessment of Outcomes in Statistics (CAOS) was administered. This instrument allows for the determination of reasoning applied to different types of statistical graphs and in some cases to determine what type of calculation is required to do it. The instrument was applied to 138 undergraduate students from the economic-administrative area of the University of Guadalajara during January-June 2018. The results show that a large percentage of students confuse a normal distribution with a uniform one and that they are unable to distinguish that a bias can be determined from the measures of central tendency and dispersion, as well as other statistical reasoning difficulties. This may be as a result of a deficiency that exists in statistical teaching, an insufficient mathematical preparation on the part of the students, among other factors.

Highlights

Graphical representation dates back more than 200 years (Unwin, 2008) For example, (Wainer & Spence, 2005) compiled the work of (Playfair, 1801) who represented data in graphical form
The Comprehensive Assessment of Outcomes in Statistics (CAOS) test was applied to undergraduate students who had taken a descriptive statistics course to assess their statistical thinking
The results show that a high percentage of students had problems recognizing what kind of distribution they were analyzing. They were confused with how to calculate the skew with measures of central tendency or dispersion. There could be another factor that affects their performance in statistical thinking

Summary

Introduction

Graphical representation dates back more than 200 years (Unwin, 2008) For example, (Wainer & Spence, 2005) compiled the work of (Playfair, 1801) who represented data in graphical form. The discipline of statistics uses either real or hypothetical data which can be interpreted graphically (Cleveland, 1985; Tufte, 2001). In any branch of the sciences and, independent of the type of data used to produce it, the ability to read and interpret a graph is indispensable for both students, irrespective of the educational level at which they are studying, and researchers in the making (Glazer, 2011). Interpreting and reading a graph requires knowledge of statistics, mathematics and real life. In this digital age, information is most often presented graphically (Susac, Bubic, Kazotti, Planinic, & Palmovic, 2018). Newspapers, magazines, billboards, television, the internet and new research generally present results in graph form. Students should learn to read and interpret graphs based on real data to ensure that they are able to read and interpret a graph throughout their academic life (Monteiro & Ainley, 2007)

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