What is following type of data description called?
Correct Answer: Stem and leaf diagram
Description: Ans. a. Stem and leaf diagram (Ref: https://en.wikipeiUa.org/wiki/Stem-ami-leaf_dispIay) The type of data description given is Stem and Leaf PlotStem and Leaf PlotStem and Leaf Plot is a special table where each data value is split into a stem' (the first digit or digits) and a 'leaf(usually the last digit).A stem-and-leaf display is a device for presenting quantitative data in a graphical format, similar to a histogram to assist in visualizing the shape of a distribution.A basic stem-and-leaf display contains two columns separated by a vertical line.The left column contains the stems and the right column contains the leaves.AdvantagesDisadvantages* Stem-and-leaf displays are useful for displaying the relative density and shape of the data, giving the reader a quick overview of distribution.* They retain (most of) the raw numerical data, often with perfect integrity.* They are also useful for highlighting outliers and finding the mode.* Only useful for moderately sized data sets (around15-150 data points).* With very small data sets a stem- and-leaf displays can be of little use. A dot plot may be better suited for such data.* With very large data sets, a stem-and-leaf display will become very cluttered. A box plot or histogram may become more appropriate as the data size increases. Box PlotA box plot is a convenient way of graphically depicting groups of numerical data through their quartiles.Box plots may also have lines extending vertically from the boxes (whiskers) indicating variability outside the upper and lower quartiles. hence the terms box-and-whisker plot and box-and-whisker diagram. Outliers may be plotted as individual points.Box plots are non-para metric: they display variation in samples of a statistical population without making any assumptions of the underlying statistical distribution.The spacing between the different parts of the box indicate the degree of dispersion (spread) and skewrness in the data, and show outliers.In addition to the points themselves, they allow one to visually estimate various L-estimators, notably the interquartile range, mid-hinge, range, mid-range, and tri-mean.Boxplots can be drawn either horizontally or vertically.Funnel Plot* A funnel plot is a graph designed to check for the existence of publication bias.* Funnel plots are commonly used in systematic reviews and meta-analyses.* In the absence of publication bias, it assumes that the largest studies will be plotted near the average, and smaller studies will be spread evenly on both sides of the average, creating a roughly funnel-shaped distribution.* Deviation from this shape can indicate publication bias.An example funnel plot showing no publication bias.Each dot represents a study (measuring the effect of a certain drug) y-axis: Size of the study (number of experimental subjects) x-axis: Show the study's (drug's measured average effect)Forest plot A forest plot, also known as a blobbogram, is a graphical display of estimated results from a number of scientific studies addressing the same question, along with the overall results. It was developed for use in medical research as a means of graphically representing a meta-analysis of the results of randomized controlled trials.In the last twenty years, similar meta-analytical techniques have been applied in observ ational studies (e.g. environmental epidemiology') and forest plots are often used in presenting the results of such studies also.Although forest plots can take several forms, they are commonly presented with two columns.The left-hand column lists the names of the studies (frequently randomized controlled trials or epidemiological studies), commonly in chronological order from the fop downwards.The right-hand column is a plot of the measure of effect (e.g. an odds ratio) for each of these studies (often represented by a square) incorporating confidence intervals represented by horizontal lines.The graph may be plotted on a natural logarithmic scale when using odds ratios or other ratio-based effect measures, so that the confidence intervals are symmetrical about the means from each study and to ensure undue emphasis is not given to odds ratios greater than 1 when compared to those less than 1.The area of each square is proportional to the study's weight In the meta-analysis.The overall meta-analyzed measure of effect is often represented on the plot as a dashed vertical line. This meta- analyzed measure of effect is commonly plotted as a diamond, the lateral points of which indicate confidence intervals for this estimate.A vertical line representing no effect is also plotted. If the confidence intervals for individual studies overlap with this line, it demonstrates that at the given level of confidence their effect sizes do not differ from no effect for the individual study.The same applies for the meta-analyzed measure of effect: if the points of the diamond overlap the line of no effect the overall meta- analyzed result cannot be said to differ from no effect at the given level of confidence.
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