Efer Again to the Table Presenting Data From Hypo College (Repeated Here as Table 10.1).

Korean J Anesthesiol. 2017 Jun; 70(3): 267–276.

Statistical data presentation

Junyong In

¹Section of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.

Sangseok Lee

ⁱⁱDepartment of Anesthesiology and Hurting Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea.

Received 2017 Mar 20; Accepted 2017 Apr 4.

Abstract

Data are ordinarily collected in a raw format and thus the inherent information is hard to empathize. Therefore, raw data demand to be summarized, candy, and analyzed. Nevertheless, no matter how well manipulated, the information derived from the raw data should be presented in an effective format, otherwise, it would exist a great loss for both authors and readers. In this commodity, the techniques of data and data presentation in textual, tabular, and graphical forms are introduced. Text is the master method for explaining findings, outlining trends, and providing contextual information. A table is all-time suited for representing individual information and represents both quantitative and qualitative data. A graph is a very effective visual tool every bit information technology displays data at a glance, facilitates comparison, and can reveal trends and relationships within the data such as changes over fourth dimension, frequency distribution, and correlation or relative share of a whole. Text, tables, and graphs for data and data presentation are very powerful communication tools. They can brand an article easy to empathize, attract and sustain the involvement of readers, and efficiently present large amounts of circuitous information. Moreover, as journal editors and reviewers glance at these presentations before reading the whole article, their importance cannot exist ignored.

Keywords: Information presentation, Data visualization, Graph, Statistics, Tabular array

Introduction

Data are a set of facts, and provide a partial picture of reality. Whether information are being collected with a certain purpose or collected data are beingness utilized, questions regarding what data the information are conveying, how the information can be used, and what must be washed to include more than useful data must constantly be kept in mind.

Since near data are available to researchers in a raw format, they must be summarized, organized, and analyzed to usefully derive information from them. Furthermore, each data set needs to be presented in a certain fashion depending on what information technology is used for. Planning how the data will be presented is essential before accordingly processing raw data.

Kickoff, a question for which an answer is desired must be clearly defined. The more detailed the question is, the more detailed and clearer the results are. A broad question results in vague answers and results that are hard to translate. In other words, a well-defined question is crucial for the data to be well-understood later. Once a detailed question is ready, the raw information must be prepared before processing. These days, data are oft summarized, organized, and analyzed with statistical packages or graphics software. Data must exist prepared in such a way they are properly recognized past the program existence used. The nowadays written report does non hash out this data training process, which involves creating a data frame, creating/changing rows and columns, irresolute the level of a factor, categorical variable, coding, dummy variables, variable transformation, data transformation, missing value, outlier treatment, and dissonance removal.

We depict the roles and appropriate use of text, tables, and graphs (graphs, plots, or charts), all of which are commonly used in reports, articles, posters, and presentations. Furthermore, we discuss the problems that must be addressed when presenting various kinds of information, and effective methods of presenting information, which are the end products of inquiry, and of emphasizing specific information.

Data Presentation

Information can be presented in one of the three ways:

–as text;

–in tabular form; or

–in graphical form.

Methods of presentation must be determined according to the data format, the method of assay to exist used, and the information to be emphasized. Inappropriately presented data fail to clearly convey information to readers and reviewers. Even when the same information is being conveyed, different methods of presentation must be employed depending on what specific data is going to be emphasized. A method of presentation must be chosen after carefully weighing the advantages and disadvantages of different methods of presentation. For piece of cake comparison of different methods of presentation, let united states of america await at a tabular array (Table 1) and a line graph (Fig. one) that present the same information [ane]. If 1 wishes to compare or introduce ii values at a certain time point, it is appropriate to employ text or the written language. However, a table is the most appropriate when all information requires equal attention, and it allows readers to selectively expect at information of their own interest. Graphs allow readers to understand the overall trend in data, and intuitively understand the comparing results betwixt 2 groups. Ane thing to always bear in listen regardless of what method is used, nonetheless, is the simplicity of presentation.

Line graph with whiskers. Changes in systolic claret pressure (SBP) in the two groups. Group C: normal saline, Grouping D: dexmedetomidine. *P < 0.05 indicates a significant increase in each group, compared with the baseline values. ^†P < 0.05 indicates a significant decrease noted in Group D, compared with the baseline values. ^‡P < 0.05 indicates a significant difference betwixt the groups (Adapted from Korean J Anesthesiol 2017; 70: 39-45).

Table 1

Modified Tabular array in Lee and Kim'south Research (Adapted from Korean J Anesthesiol 2017; seventy: 39-45)

Variable	Grouping	Baseline	After drug	1 min	3 min	5 min
SBP	C	135.i ± thirteen.4	139.2 ± 17.1	186.0 ± 26.6*	160.1 ± 23.two*	140.7 ± eighteen.3
	D	135.iv ± 23.8	131.9 ± 13.5	165.ii ± xvi.2*,‡	127.9 ± 17.5‡	108.4 ± 12.6†,‡
DBP	C	79.7 ± 9.8	79.iv ± 15.viii	104.8 ± 14.nine*	87.ix ± xv.5*	78.ix ± 11.6
	D	76.7 ± 8.3	78.4 ± 6.three	97.0 ± 14.v*	74.1 ± 8.three‡	66.v ± 7.2†,‡
MBP	C	100.iii ± 11.ix	103.five ± 16.8	137.2 ± 18.three*	116.9 ± 16.2*	103.9 ± 13.3
	D	97.7 ± 14.9	98.1 ± 8.7	123.4 ± thirteen.8*,‡	95.4 ± eleven.7‡	83.four ± 8.4†,‡

Text presentation

Text is the master method of carrying information as it is used to explain results and trends, and provide contextual information. Information are fundamentally presented in paragraphs or sentences. Text can be used to provide interpretation or emphasize certain data. If quantitative information to be conveyed consists of 1 or two numbers, it is more appropriate to use written language than tables or graphs. For instance, information nigh the incidence rates of delirium following anesthesia in 2016–2017 tin can be presented with the utilize of a few numbers: "The incidence rate of delirium following anesthesia was 11% in 2016 and xv% in 2017; no significant difference of incidence rates was plant between the two years." If this information were to be presented in a graph or a tabular array, information technology would occupy an unnecessarily large space on the page, without enhancing the readers' understanding of the data. If more data are to be presented, or other information such as that regarding data trends are to be conveyed, a table or a graph would exist more than appropriate. By nature, data take longer to read when presented equally texts and when the main text includes a long list of information, readers and reviewers may have difficulties in understanding the information.

Table presentation

Tables, which convey information that has been converted into words or numbers in rows and columns, take been used for nearly 2,000 years. Anyone with a sufficient level of literacy tin can hands understand the information presented in a table. Tables are the near appropriate for presenting individual information, and tin can present both quantitative and qualitative information. Examples of qualitative information are the level of sedation [2], statistical methods/functions [iii,iv], and intubation conditions [five].

The forcefulness of tables is that they can accurately present information that cannot be presented with a graph. A number such as "132.145852" can be accurately expressed in a table. Another force is that information with different units can be presented together. For example, blood pressure, middle rate, number of drugs administered, and anesthesia fourth dimension can be presented together in one table. Finally, tables are useful for summarizing and comparison quantitative information of dissimilar variables. However, the interpretation of information takes longer in tables than in graphs, and tables are not appropriate for studying data trends. Furthermore, since all data are of equal importance in a table, it is not piece of cake to identify and selectively choose the information required.

For a general guideline for creating tables, refer to the journal submission requirements ¹⁾.

Oestrus maps for meliorate visualization of information than tables

Heat maps assistance to further visualize the information presented in a table by applying colors to the background of cells. By adjusting the colors or color saturation, information is conveyed in a more visible style, and readers can quickly identify the data of interest (Table ii). Software such as Excel (in Microsoft Office, Microsoft, WA, USA) have features that enable easy creation of heat maps through the options available on the "conditional formatting" menu.

Table two

Difference between a Regular Tabular array and a Heat Map

Example of a regular table				Example of a rut map
SBP	DBP	MBP	HR	SBP	DBP	MBP	Hour
128	66	87	87	128	66	87	87
125	43	70	85	125	43	70	85
114	52	68	103	114	52	68	103
111	44	66	79	111	44	66	79
139	61	81	ninety	139	61	81	xc
103	44	61	96	103	44	61	96
94	47	61	83	94	47	61	83

Graph presentation

Whereas tables tin be used for presenting all the data, graphs simplify complex data by using images and emphasizing data patterns or trends, and are useful for summarizing, explaining, or exploring quantitative data. While graphs are constructive for presenting large amounts of data, they tin be used in place of tables to present pocket-sized sets of data. A graph format that best presents information must exist chosen so that readers and reviewers can hands sympathize the information. In the post-obit, nosotros describe frequently used graph formats and the types of data that are appropriately presented with each format with examples.

Scatter plot

Scatter plots present data on the x- and y-axes and are used to investigate an clan between 2 variables. A point represents each individual or object, and an association between ii variables can be studied by analyzing patterns across multiple points. A regression line is added to a graph to make up one's mind whether the association betwixt two variables can be explained or not. Fig. 2 illustrates correlations between hurting scoring systems that are currently used (PSQ, Pain Sensitivity Questionnaire; Pass, Pain Anxiety Symptoms Calibration; PCS, Pain Catastrophizing Calibration) and Geop-Pain Questionnaire (GPQ) with the correlation coefficient, R, and regression line indicated on the scatter plot [6]. If multiple points exist at an identical location as in this example (Fig. 2), the correlation level may not be clear. In this case, a correlation coefficient or regression line tin be added to further elucidate the correlation.

Besprinkle plot of GPQ scores and the other questionnaires. Score 1: sensitivity, ii: experience, 3: other. GPQ: Geop-Hurting Questionnaire, PSQ: Pain Sensitivity Questionnaire, PASS: Hurting Anxiety Symptoms Scale, PCS: Pain Catastrophizing Calibration (Adapted from Korean J Anesthesiol 2016; 69: 492-505).

Bar graph and histogram

A bar graph is used to bespeak and compare values in a discrete category or group, and the frequency or other measurement parameters (i.due east. mean). Depending on the number of categories, and the size or complexity of each category, bars may be created vertically or horizontally. The height (or length) of a bar represents the amount of information in a category. Bar graphs are flexible, and can be used in a grouped or subdivided bar format in cases of ii or more information sets in each category. Fig. 3 is a representative example of a vertical bar graph, with the x-centrality representing the length of recovery room stay and drug-treated grouping, and the y-axis representing the visual analog scale (VAS) score. The mean and standard deviation of the VAS scores are expressed as whiskers on the bars (Fig. 3) [seven].

Multiple bar graph with whiskers. Pain scores in the recovery room. ^*P < 0.05 compared with the control group. The nefopam group showed significant lower visual analogue scale (VAS) score at 0, five, 15, 30, 45 and threescore minutes on postanesthesia care unit compared with the control group (Adapted from Korean J Anesthesiol 2016; 69: 480-vi. Fig. 2).

Past comparing the endpoints of bars, i tin can identify the largest and the smallest categories, and understand gradual differences between each category. Information technology is advised to outset the x- and y-axes from 0. Illustration of comparison results in the x- and y-axes that exercise not start from 0 tin deceive readers' eyes and lead to overrepresentation of the results.

One course of vertical bar graph is the stacked vertical bar graph. A stack vertical bar graph is used to compare the sum of each category, and analyze parts of a category. While stacked vertical bar graphs are first-class from the aspect of visualization, they exercise not have a reference line, making comparison of parts of various categories challenging (Fig. 4) [eight].

Stacked bar graph. Compressed book of each component from the three operations. We checked the compressed volume of each component from the three operations; pelviscopy (with radical vaginal hysterectomy), laparoscopic anterior resection of the colon, and TKRA. TKRA: total knee replacement arthroplasty, RMW: regulated medical waste (Adapted from Korean J Anesthesiol 2017; lxx: 100-4).

Pie chart

A pie chart, which is used to represent nominal information (in other words, information classified in dissimilar categories), visually represents a distribution of categories. It is more often than not the most appropriate format for representing data grouped into a small number of categories. Information technology is also used for data that have no other mode of beingness represented aside from a table (i.e. frequency tabular array). Fig. 5 illustrates the distribution of regular waste from operation rooms past their weight [8]. A pie chart is too usually used to illustrate the number of votes each candidate won in an election.

Pie chart. Total weight of each component from the three operations. RMW: regulated medical waste (Adapted from Korean J Anesthesiol 2017; 70: 100-4).

Line plot with whiskers

A line plot is useful for representing time-serial data such as monthly precipitation and yearly unemployment rates; in other words, it is used to study variables that are observed over time. Line graphs are specially useful for studying patterns and trends beyond information that include climatic influence, big changes or turning points, and are also appropriate for representing non but time-series information, but also data measured over the progression of a continuous variable such every bit distance. As can be seen in Fig. 1, hateful and standard deviation of systolic blood pressure are indicated for each time point, which enables readers to easily empathise changes of systolic pressure over time [one]. If data are collected at a regular interval, values in between the measurements can be estimated. In a line graph, the 10-axis represents the continuous variable, while the y-axis represents the scale and measurement values. Information technology is as well useful to represent multiple data sets on a single line graph to compare and analyze patterns across unlike data sets.

Box and whisker chart

A box and whisker nautical chart does not brand any assumptions about the underlying statistical distribution, and represents variations in samples of a population; therefore, it is appropriate for representing nonparametric data. AA box and whisker chart consists of boxes that represent interquartile range (one to three), the median and the mean of the data, and whiskers presented as lines exterior of the boxes. Whiskers can be used to present the largest and smallest values in a set of information or but a function of the data (i.e. 95% of all the data). Information that are excluded from the data set are presented as individual points and are called outliers. The spacing at both ends of the box indicates dispersion in the information. The relative location of the median demonstrated within the box indicates skewness (Fig. 6). The box and whisker nautical chart provided as an example represents calculated volumes of an coldhearted, desflurane, consumed over the course of the ascertainment period (Fig. vii) [nine].

Box graph with whiskers. This graph is a standardized way of displaying the distribution of data based on the five-number summary; minimum, outset quartile, median, 3rd quartile, and maximum. The central rectangle represents from the outset quartile to the third quartile (the interquartile range [IQR]). A segment inside the rectangle shows the median and "whiskers" above and below the box show the locations of the minimum and maximum.

Box graph with whiskers. Calculated volume of desflurane consumed during the ascertainment period. The groups differed significantly. Data are expressed every bit median, minimum, outset interquartile, third interquartile, and maximum values. ^*P < 0.05 (Adjusted from Korean J Anesthesiol 2017; 70: 27-32).

Three-dimensional effects

Most of the recently introduced statistical packages and graphics software have the 3-dimensional (3D) effect feature. The 3D effects can add depth and perspective to a graph. However, since they may brand reading and interpreting data more difficult, they must simply be used later on careful consideration. The awarding of 3D effects on a pie chart makes distinguishing the size of each piece difficult. Even if slices are of similar sizes, slices farther from the front of the pie chart may appear smaller than the slices closer to the front (Fig. 8).

Simple pie chart (A) versus 3D pie chart (B). In the 3D pie chart, slices at the rear of the chart announced smaller than those at the front because of the false perspective.

Drawing a graph: example

Finally, we explicate how to create a graph by using a line graph as an example (Fig. 9). In Fig. 9, the mean values of arterial pressure were randomly produced and causeless to take been measured on an hourly basis. In many graphs, the x- and y-axes run across at the zippo indicate (Fig. 9A). In this example, information regarding the mean and standard deviation of mean arterial pressure measurements corresponding to t = 0 cannot be conveyed as the values overlap with the y-axis. The data can be clearly exposed past separating the nothing point (Fig. 9B). In Fig. 9B, the mean and standard deviation of different groups overlap and cannot be clearly distinguished from each other. Separating the data sets and presenting standard deviations in a single direction prevents overlapping and, therefore, reduces the visual inconvenience. Doing so as well reduces the excessive number of ticks on the y-axis, increasing the legibility of the graph (Fig. 9C). In the last graph, different shapes were used for the lines connecting different time points to further allow the data to be distinguished, and the y-centrality was shortened to get rid of the unnecessary empty space present in the previous graphs (Fig. 9D). A graph can be made easier to interpret by assigning each grouping to a dissimilar colour, changing the shape of a point, or including graphs of different formats [10]. The use of random settings for the scale in a graph may lead to inappropriate presentation or presentation of data that can deceive readers' eyes (Fig. 10).

Description of a graph. Virtual data are presented as mean with standard deviations. (A) A graph with default settings. (B) The axes are separated from each other. The data at 0 are displayed clearly. (C) The points and whiskers are jittered to avoid overlapping. Although i side of the whiskers are removed, it is all the same easy to empathize. However, this graph still has unnecessary blank space. (D) The lines are expressed in various means. A break is put in the y-axis. MBP: mean blood pressure.

An example of misleading graphs. Both plots use the same data set. (A) The readers might be thinking that the heart rates at i min are higher than others. (B) The heart rates are very stable during the written report. The readers should check the scale of the y-axis and baseline values when they look at the graphs.

Owing to the lack of infinite, nosotros could non discuss all types of graphs, but have focused on describing graphs that are oft used in scholarly articles. We have summarized the commonly used types of graphs according to the method of data analysis in Tabular array three. For general guidelines on graph designs, please refer to the journal submission requirements²⁾.

Table 3

Types of Charts Depending on the Method of Analysis of the Data

Analysis	Subgroup	Number of variables	Type
Comparison	Amid items	Ii per items	Variable width column chart
		Ane per item	Bar/column chart
	Over time	Many periods	Circular area/line nautical chart
		Few periods	Column/line nautical chart
Relationship		Two	Scatter chart
		3	Bubble chart
Distribution		Single	Column/line histogram
		Two	Scatter chart
		Three	Iii-dimensional area chart
Comparison	Irresolute over time	Only relative differences matter	Stacked 100% column chart
		Relative and absolute differences matter	Stacked column nautical chart
	Static	Elementary share of total	Pie nautical chart
		Accumulation	Waterfall chart
		Components of components	Stacked 100% column chart with subcomponents

Conclusions

Text, tables, and graphs are effective advice media that present and convey data and information. They help readers in understanding the content of enquiry, sustain their involvement, and effectively present large quantities of complex information. Every bit journal editors and reviewers will scan through these presentations before reading the entire text, their importance cannot be overlooked. For this reason, authors must pay as close attention to selecting appropriate methods of data presentation as when they were collecting data of good quality and analyzing them. In add-on, having a well-established agreement of different methods of information presentation and their advisable utilize will enable 1 to develop the ability to recognize and interpret inappropriately presented data or data presented in such a fashion that it deceives readers' eyes [eleven].

<Appendix>

Output for Presentation

Discovery and advice are the 2 objectives of data visualization. In the discovery phase, various types of graphs must be tried to empathize the rough and overall data the data are conveying. The communication phase is focused on presenting the discovered information in a summarized form. During this phase, it is necessary to shine images including graphs, pictures, and videos, and consider the fact that the images may look different when printed than how appear on a estimator screen. In this appendix, we discuss important concepts that one must be familiar with to impress graphs appropriately.

The KJA asks that pictures and images encounter the following requirement earlier submissionⁱⁱⁱ⁾

"Figures and photographs should be submitted as 'TIFF' files. Submit files of figures and photographs separately from the text of the paper. Width of effigy should exist 84 mm (1 column). Contrast of photos or graphs should exist at least 600 dpi. Contrast of line drawings should be at least 1,200 dpi. The Powerpoint file (ppt, pptx) is besides acceptable."

Unfortunately, without sufficient knowledge of estimator graphics, it is not piece of cake to understand the submission requirement to a higher place. Therefore, information technology is necessary to develop an agreement of prototype resolution, prototype format (bitmap and vector images), and the corresponding file specifications.

Resolution

Resolution is often mentioned to describe the quality of images containing graphs or CT/MRI scans, and video files. The higher the resolution, the clearer and closer to reality the paradigm is, while the reverse is true for depression resolutions. The most representative unit used to draw a resolution is "dpi" (dots per inch): this literally translates to the number of dots required to plant one inch. The greater the number of dots, the college the resolution. The KJA submission requirements recommend 600 dpi for images, and 1,200 dpi^iv) for graphs. In other words, resolutions in which 600 or 1,200 dots constitute one inch are required for submission.

There are requirements for the horizontal length of an epitome in improver to the resolution requirements. While at that place are no requirements for the vertical length of an image, it must not exceed the vertical length of a page. The width of a column on one side of a printed page is 84 mm, or iii.iii inches (84/25.iv mm ≒ 3.3 inches). Therefore, a graph must take a resolution in which ane,200 dots constitute 1 inch, and take a width of 3.3 inches.

Bitmap and Vector

Methods of image construction are important. Bitmap images can be considered as images drawn on section paper. Enlarging the image will enlarge the picture along with the grid, resulting in a lower resolution; in other words, aliasing occurs. On the other hand, reducing the size of the paradigm will reduce the size of the movie, while increasing the resolution. In other words, resolution and the size of an image are inversely proportionate to one another in bitmap images, and information technology is a drawback of bitmap images that resolution must be considered when adjusting the size of an prototype. To enlarge an paradigm while maintaining the same resolution, the size and resolution of the image must be determined before saving the image. An image that has already been created cannot avoid changes to its resolution according to changes in size. Enlarging an epitome while maintaining the same resolution volition increase the number of horizontal and vertical dots, ultimately increasing the number of pixels⁵⁾ of the image, and the file size. In other words, the file size of a bitmap image is affected by the size and resolution of the image (file extensions include JPG [JPEG]^{half dozen)}, PNG⁷⁾, GIF^eight), and TIF [TIFF]⁹⁾. To avert this complexity, the width of an prototype can be set to 4 inches and its resolution to 900 dpi to satisfy the submission requirements of most journals [12].

Vector images overcome the shortcomings of bitmap images. Vector images are created based on mathematical operations of line segments and areas between dissimilar points, and are not afflicted by aliasing or pixelation. Furthermore, they effect in a smaller file size that is not affected by the size of the image. They are unremarkably used for drawings and illustrations (file extensions include EPS¹⁰⁾, CGM¹¹⁾, and SVG¹²⁾).

Finally, the PDF^thirteen) is a file format developed by Adobe Systems (Adobe Systems, CA, United states) for electronic documents, and tin contain general documents, text, drawings, images, and fonts. They can as well contain bitmap and vector images. While vector images are used by researchers when working in Powerpoint, they are saved as 960 × 720 dots when saved in TIFF format in Powerpoint. This results in a resolution that is inappropriate for press on a paper medium. To save high-resolution bitmap images, the image must be saved as a PDF file instead of a TIFF, and the saved PDF file must be imported into an imaging processing programme such as Photoshop™(Adobe Systems, CA, Us) to be saved in TIFF format [12].

Footnotes

¹⁾Instructions to authors in KJA; section 5-(9) Table; https://ekja.org/index.php?body=educational activity

²⁾Instructions to Authors in KJA; section six-1)-(10) Figures and illustrations in Manuscript training; https://ekja.org/alphabetize.php?body=instruction

³⁾Instructions to Authors in KJA; section 6-1)-(10) Figures and illustrations in Manuscript grooming; https://ekja.org/index.php?torso=pedagogy

⁴⁾Resolution; in KJA, it is represented past "dissimilarity."

⁵⁾Pixel is a minimum unit of an image and contains data of a dot and color. Information technology is derived by multiplying the number of vertical and horizontal dots regardless of image size. For example, Full High Definition (FHD) monitor has 1920 × 1080 dots ≒ ii.07 one thousand thousand pixel.

^vi)Joint Photographic Experts Group.

^seven)Portable Network Graphics.

⁸⁾Graphics Interchange Format

⁹⁾Tagged Prototype File Format; TIFF

¹⁰⁾Encapsulated PostScript.

¹¹⁾Estimator Graphics Metafile.

¹²⁾Scalable Vector Graphics.

^thirteen)Portable Document Format.

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453888/

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