Investigating research students' perceptions about statistics and its impact on their choice of research approach

In the information society, there is a vast amount of data that needs to be analyzed quantitatively. The ability to perform quantitative analysis based on statistical thinking and data mining, is becoming extremely important. It is important that research students develop positive attitude towards both qualitative and quantitative research approaches. But many research students try to avoid applying quantitative methods in their research and prefer to rely on qualitative research approach due to lack of interest and confidence in statistical skills. This research aims to explore if research students' choice of research approach is affected by their attitude towards Statistics. 81 research students from three different universities participated in a survey in which there was one open ended question. Quantitative data from the survey was analyzed by using cluster analysis and independent sample t-test was applied to examine differences in the attitudes of masters and doctoral research students. Other data analysis methods, such as cross-tabular analysis, chi-square and ANOVA tests were also applied. Responses to open ended question were analyzed qualitatively by detecting the themes, such as, focus on technique, data or meaning. This study found that students pursuing postgraduate degrees in social science streams are not very keen on using a quantitative research approach. Masters students' attitudes towards statistics are different than the doctoral students. Findings of our research indicate that the majority of students who think that statistics is only about numeric methods, prefer to go away from it and choose a qualitative approach. Based on the findings, recommendations for changes in curriculum are presented.