Browsing by Subject "dot plot"

Now showing 1 - 3 of 3
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    Have You Seen the Standard Deviation?
    (NepJOL, 2019) Sarkar, Jyotirmoy; Rashid, Mamunur; Mathematical Sciences, School of Science
    Background: Sarkar and Rashid (2016a) introduced a geometric way to visualize the mean based on either the empirical cumulative distribution function of raw data, or the cumulative histogram of tabular data. Objective: Here, we extend the geometric method to visualize measures of spread such as the mean deviation, the root mean squared deviation and the standard deviation of similar data. Materials and Methods: We utilized elementary high school geometric method and the graph of a quadratic transformation. Results: We obtain concrete depictions of various measures of spread. Conclusion: We anticipate such visualizations will help readers understand, distinguish and remember these concepts.
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    Visualizing Bivariate Statistics Using Ellipses Over a Scatter Plot
    (Susan Rivers' Cultural Institute, 2022-10-03) Rashid, Mamunur; Sarkar, Jyotirmoy; Phuyal, Siddhanta; Mathematical Sciences, School of Science
    A scatter plot shows the relationship between two quantitative variables x and y. Sometimes, we can predict one variable as a linear function of the other using the least-squares regression lines of y on x or x on y. These two regression lines together suffice to identify the mean vector, the coefficient of determination, the correlation coefficient, and the ratio of the standard deviations (SD). So, do our proposed summary ellipses. Additionally, the inner ellipse reveals the SDs and the outer ellipse flags potential outliers.
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    Visualizing the mean and the standard deviation using R/RStudio Shiny package
    (2020) Hufnagel, Rachel; Chen, Ziyi; Rashid, Mamunur; Sarkar, Jyotirmoy; Mathematical Sciences, School of Science
    Many of us have experienced an unpleasant situation in which only the mean and the standard deviation of a data set are reported, but we are expected to know everything about the dataset as if those two values were all we needed to know. We would learn so much more if there were easy ways to create and share graphical representations and interpretations of the entire raw data. In this paper, we not only explain what the mean and the standard deviation tell us about a data set, but also describe how to include additional information on the data. We utilize the work of Sarkar and Rashid (2016) that introduced a geometric visualization of the sample mean based on the empirical cumulative distribution function of the raw data. They also extended the idea to visualize measures of spread such as the mean deviation, the root mean square deviation and the standard deviation. Our research involves creating interactive applications of these methods using R/RStudio Shiny, an open source package that provides an elegant and powerful web framework for building web applications. We hope, upon publication of these tools, users all over the world will use such interactive visualization methods for learning, teaching, and building more advanced tools.