Advantages/Strengths• Quick and easy method to theorem the data so the the circulation of the data deserve to be conveniently seen (i.e., clusters of data, gaps in data, or bellshaped distribution) • Every item of data is clearly shows • Mean, median, mode, and selection or spread out of data easily established • A functioning draft that have the right to be easily used to produce a pictograph, bar graph, or other representation • can be created while tallying the data if the selection is recognized Limitationsmitations* • Not useful for very big data sets • Not practical for data through a huge number the data values

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Advantages/Strengths • similar to heat plot but much more practical for big data set with few data worths • exact data can be rebuilded if data have not been grouped right into categories • distribution of data have the right to be quickly seen (i.e.,clusters the data, gaps in data, or bell-shaped distribution) • variety or spread of data is easily identified • Mode(s) deserve to be conveniently seen • Mean and also median have the right to be figured out with some effort • deserve to be provided to represent numerical or categorical data Limitations • Not handy for data v a large number the data worths • Two collaborates must be check out to totally understand the graph • Data have to be tallied front tocreating graph • Scaling, labeling, and also readability must be thought about when developing this graph
Advantages/Strengths • precise data have the right to be reconstructed • simpler to watch the shape of the data as soon as the variety of data values and also size of data set are about the very same • groups data values making use of their digits • circulation of data can easily be checked out (i.e., clusters of data, gaps in data, or bell- shame distribution) • selection or spread of data is easily established • Mean, median, and mode can be calculate • Back-to-back graphs that this kind can compare two different sets of data Limitations *Limitations* • Not practical for very large data sets due to the fact that sorting andreorganizing data can be time-consuming • much more restrictive 보다 histograms are because the size of theirclasses (groups) is based on their critical digits. Histograms room not limited to any class length.
• practically for representing big quantities the data • General distribution of data have the right to be easily seen • similar to stem-and-leaf plots however without the specific data worths • size of classes is not limited Limitationstations* • certain data values are lost—data can not be rebuilded • figure of the data"s distribution can be manipulated depending upon numbering scale offered • precise mean, median, mode, and range cannot it is in determined
Advantages/Strengths • shows the part-to-whole relationship in between data • swarm numerical data into groups • much easier to check out the portion of the data satisfying details conditions Limitationstions* • particular data values space lost—data cannot be rebuilded • exact mean, median, mode, and variety of initial numerical data cannot be determined
Advantages/Strengths • effective representation for huge quantities the data • selection can be identified • Outliers have the right to be revealed • Median and interquartile arrays are easily established • Plots using different sets of data can be easily compared when graphed ~ above the same scale Limitationsmitations* • specific data values are lost—data can not be rebuilded • Mean and mode cannot be determined
Advantages/Strengths • shows relationship in between two different variables • If a sample or tendency exists in ~ the relationship, generalizations and/or predictions have the right to be made Limitationsons* • precise data cannot always be determined—only approximate worths will be feasible at time • given there space two values represented at any type of given point, actions of center are no informative
Advantages/Strengths • mirrors the change between two various variables (where regularly one variable may be time) Limitationss* • have the right to be misleading as result of scale sensitivity • Only appropriate for displaying two variables v one an live independence variable gift observed exactly once at continual intervals


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