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A stem-and-leaf display or stem-and-leaf plot is a device for presenting quantitative data in a graphical format, similar to a histogram, to assist in visualizing the shape of a distribution. They evolved from Arthur Bowley 's work in the early 1900s, and are useful tools in exploratory data analysis. Stemplots became more commonly used in the ...
The first component is called the 'Leaf Area Ratio' (LAR) and indicates how much leaf area there is per unit total plant mass. For young plants, values are often in the range of 1–20 m 2 kg −1, for tree seedlings they are generally less. The second component is the 'Unit Leaf Rate' (ULR), which is also termed 'Net Assimilation Rate' (NAR).
Plot (graphics) A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables. The plot can be drawn by hand or by a computer. In the past, sometimes mechanical or electronic plotters were used.
Rationale. Specific leaf area is a ratio indicating how much leaf area a plant builds with a given amount of leaf biomass: where A is the area of a given leaf or all leaves of a plant, and M L is the dry mass of those leaves. Typical units are m 2 /kg or mm 2 /mg. Leaf mass per area (LMA) is its inverse and can mathematically be decomposed in ...
In statistics, a contingency table (also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the multivariate frequency distribution of the variables. They are heavily used in survey research, business intelligence, engineering, and scientific research. They provide a basic picture of the interrelation ...
The stem can also be called the culm, halm, haulm, stalk, or thyrsus. The stem is normally divided into nodes and internodes: [2] The nodes are the points of attachment for leaves and can hold one or more leaves. There are sometimes axillary buds between the stem and leaf which can grow into branches (with leaves, conifer cones, or flowers). [2]
The exploration of the content of a data set. The use to find structure in data. Checking assumptions in statistical models. Communicate the results of an analysis. If one is not using statistical graphics, then one is forfeiting insight into one or more aspects of the underlying structure of the data.
In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts ...