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Statistics educators have cognitive and noncognitive goals for students. For example, former American Statistical Association (ASA) President Katherine Wallman defined statistical literacy as including the cognitive abilities of understanding and critically evaluating statistical results as well as appreciating the contributions statistical thinking can make.
Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots , histograms , probability plots , spaghetti plots , residual plots, box plots , block plots and biplots .
Box plot : In descriptive statistics, a boxplot, also known as a box-and-whisker diagram or plot, is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation, lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation). A boxplot may also indicate which ...
Many graphs are also referred to as charts. [51] Eppler and Lengler have developed the "Periodic Table of Visualization Methods," an interactive chart displaying various data visualization methods. It includes six types of data visualization methods: data, information, concept, strategy, metaphor and compound. [52]
The NCBI article titled "Teaching Data Science to Medical Students: A Multi-Disciplinary Approach" (NCBI article [3]) covered how Google Charts has helped medical students learn about data science in a hands-on way. Google Charts allows for the visualization of complex data sets, which may improve some students' understanding of the information.
Data and information visualization; Data point; Datasaurus dozen; Defect concentration diagram; Dendrogram; Distribution-free control chart; DOE mean plot; Dot plot (bioinformatics) Dot plot (statistics) Double mass analysis; Dual-flashlight plot
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]
Dr. Wolfgang Greller and Dr. Hendrik Drachsler defined learning analytics holistically as a framework. They proposed that it is a generic design framework that can act as a useful guide for setting up analytics services in support of educational practice and learner guidance, in quality assurance, curriculum development, and in improving teacher effectiveness and efficiency.