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Descriptive Statistics
Descriptive statistics (DS) help researchers to comprehend research data in details. By using DS, it is possible to learn about the data value, the character of variables, distribution range, etc. (McHugh, 2003a, p. 35). DS helps researchers to arrange data and summarize it. It may be used as a main instrument in the descriptive studies, or it may also be implemented as a complementary part of the research.
There are many types of DS (measures of shapes, measures of central tendency, measures of dispersion, percentile and quartile measures), and the selection of the right one is essential to the obtaining of accurate information (McHugh, 2003b, p. 111). For the increase in the reliability of statistics, it is important to ensure that the measurement criteria and the estimation of variables are matched.
It is also necessary to make certain that the statistics provide the information that is needed for particular research. In case a researcher knows how to choose the right levels of measurement, DS may help to reveal a significant amount of information about any kind of variable (Ho & Yu, 2015, p. 365). For example, for the typical cases, the mode, the median, and the mean measures are recommended; for exploring the nature of the distribution of the variable, the test of Skewness or Kurtosis is applied; and the measures of dispersion (range, variance, and deviation) are used to discover the mean variability (McHugh, 2003b, p. 115)
The practice of statistics includes the evaluation of the collected data; nevertheless, the DS measurements sometimes maybe “incomplete” (Conor, 1998, p. 268). For example, on the lower scales of measurement (nominal or ordinal scale), a researcher has less ability to rank and label the analyzed data; some measurements involve broader interpretation while others provide a higher level of precision. However, the profound understanding of how the DS measures work is necessary, otherwise, the validity of the results may be significantly reduced.
Statistics Anxiety
Statistics anxiety may be defined as a complex of the negative emotions encountered during learning or practicing statistical analysis (Baloglu, Deniz, & Kesici, 2011, p. 387). The feelings of anxiety or the adverse attitudes towards statistics interfere with the students’ efficacy and negatively affect their academic or professional performance. It is observed that anxiety may arise from the previous experience, negative perception of the mathematics, and the broader factors of personal characteristics such as self-perception or perfectionism (Perepiczka, Chandler, & Becerra, 2011, p. 100).
Statistics anxiety is a common phenomenon among the students, especially those who do not have a lot of experience in mathematics and who do not recognize the significance of analytical methods of research. Nevertheless, the course of statistics is a necessary part of the curriculum as it contributes to further professional development. When feeling statistics anxiety, a person cannot evaluate his/her abilities adequately because of the prejudiced and negative presumptions. In this way, negative sentiments interfere with the learning process.
Since many students may perceive statistics as something daunting and stressful, the positive climate in the class may help them to develop an adequate attitude towards the subject. It is observed, that when students feel support and are encouraged to achieve academic goals, the positive view of statistics starts to form (Perepiczka, Chandler, & Becerra, 2011, p. 105). However, fighting with negative perceptions requires the individual’s work and self-discipline as well. It is important to comprehend the origins and nature of statistics anxiety and make efforts to eradicate them. The statistics anxiety may be reduced in case the value of statistics is recognized by a student. DS is an important element of research, and by obtaining a necessary competence in the subject, a psychology practitioner increases his/her level of professional expertise.
References
Baloglu, M., Deniz, M., & Kesici, S. (2011). A descriptive study of individual and cross-cultural differences in statistics anxiety. Learning and Individual Differences, 21, 387–391. Web.
Conor, G. (1998). Understanding and using descriptive statistics. British Journal of Occupational Therapy, 61(6), 267-272. Web.
Ho, A., & Yu, C. (2015). Descriptive statistics for modern test score distributions: Skewness, Kurtosis, discreteness, and ceiling effects. Educational and Psychological Measurement, 75(3), 365–388. Web.
McHugh, M. L. (2003a). Descriptive statistics, part I: Level of measurement. Journal for Specialists in Pediatric Nursing, 8(1), 35-37. Web.
McHugh, M. L. (2003b). Descriptive statistics, part II: Most commonly used descriptive statistics. Journal for Specialists in Pediatric Nursing, 8(3), 111-6. Web.
Perepiczka, M., Chandler, N., & Becerra, M. (2011). Relationship between graduate students’ statistics self-efficacy, statistics anxiety, attitude toward statistics, and social support. The Professional Counselor, 1(2), 99–108. Web.
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