Introduction
The use of scatter plot is one of the strategies that studies employ to visualize and present information to readers. Data visualization has numerous advantages, including enhancing the understanding of a phenomenon, highlighting trends and patterns, and summarizing complex information (Li, 2018). Scatterplot aids in data visualization by depicting the nature of the relationship between two variables measured on a continuous or numerical scale. Visualizations of two variables in a scatterplot can have a positive, negative, or spurious relationship, depending on trends and patterns that they exhibit (Li, 2018). To illustrate the use of scatter plot, this assignment selected a study by Miralpeix and Muñoz (2018), which depicts the relationship between the receptive vocabulary size and proficiency in English as a Foreign Language.
Variables in the Study
Receptive vocabulary size (RVS) and proficiency in English as a Foreign Language (PEFL) are two variables examined in the selected study. RVS is an independent variable that measures the number of words a participant understands. It is a computerized test where participants indicate whether they understand a series of words presented to them. PEFL is the dependent variable in the study that measures the levels of language skills among learners. It evaluates reading, writing, listening, speaking, vocabulary, and grammar skills measured on a Likert scale from 1 to 5 to indicate the degree of proficiency. Since these two variables exist on a numeric scale, it is possible to examine their relationship and depict using the scatterplot.
Association between Variables
The study used a scatterplot in the visualization of the relationship between RVS and PEFL. The examination of the scatterplot indicates that RVS and PEFL have a positive correlation. Although the scatterplot shows the existence of outliers in data points, it shows a pattern and trend of a positive association between RVS and PEFL. The dispersion of values shows that RVS ranged from 2500 to 7200 scores, while PEFL ranged from 3.31 to 8.72. As the range in RVS is less than that of PEFL, it implies that these variables have a moderate relationship between them. Since these variables have a causal relationship, the scatterplot reveals that learners with high scores in RVS tend to have high levels of PEFL, and vice versa.
Pearson Correlation
Pearson correlation coefficient ought to be an additional analysis to the scatterplot to quantify the degree of relationship between RVS and PEFL. According to Field (2017), the Pearson correlation coefficient shows both the direction and the magnitude of the relationship between two variables. In this case, the scatterplot shows the direction of the relationship but does not depict the strength of association. Hence, the Pearson correlation coefficient is necessary to quantify the degree of relationship between RVS and PEFL among learners. The coefficient ranges from -1 to +1 to indicate both the direction and magnitude of a relationship (Field, 2017). As the scatterplot indicates a positive relationship, the coefficient would indicate if the relationship is strong (r ≥ 0.7), moderate (r = 0.4-0.6), or weak (r ≤ 0.4) (Field, 2017). Therefore, the addition of the Pearson correlation in the analysis would provide supplementary information to the scatterplot.
Conclusion
Data visualization using scatterplot enhances the presentation, highlights trends, and summarizes relationships between variables. The study sought to establish the nature of the relationship between RVS and PEFL as variables of interest. By using the scatterplot, the selected study demonstrated that RVS and PEFL have a positive relationship. The analysis of the strength of the relationship using the Pearson correlation coefficient would provide additional information. The nature of the relationship shows that learners with high RVS have a high level of PEFL skills. In essence, the scatterplot and correlation indicate that PEFL skills among learners increase as the level of RVS rises.
References
Field, A. P. (2017). Discovering statistics using IBM SPSS statistics. Thousand Oaks.
Li, Q. (2018). Using R for data analysis in social sciences: A research project-oriented approach. Oxford University Press.
Miralpeix, I., & Muñoz, C. (2018). Receptive vocabulary size and its relationship to EFL language skills. International Review of Applied Linguistics in Language Teaching, 56(1), 1-24. Web.