Tables, Charts and Graphs

11 Key excerpts on "Tables, Charts and Graphs"

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  Regional capacity development resource book on monitoring SDG4-Education 2030 in Asia-Pacific

  • UNESCO Office Bangkok and Regional Bureau for Education in Asia and the Pacific, UNICEF. East Asia and the Pacific Regional Office (Thailand)(Authors)
  • 2019(Publication Date)
  • UNESCO

    (Publisher)

  Charts are especially useful for: ● Faster understanding of numbers; ● Recognizing distributions in data, showing patterns and comparing trends; ● Easing comparing numerical information; ● Allowing information to be presented in various ways. There are numerous ways of visually presenting statistical information. In short, the main purpose of charts is to visually impart information that cannot be easily read and interpreted from a table of data. In other words, the advantage of charts is that they are visually more attractive than tables, and can ease presentations. With the help of computer software packages, graphical visualization of data can be made in a variety of ways. As mentioned, charts are not suitable for communicating detailed and precise information, and can be time-consuming and expensive to design. The following section will explain a few charts and provide a structured overview (Figures 19 and 20) to help decide on which chart is appropriate to pick for which purpose. 4.3.1 Explaining when to use certain charts LINE CHART: These are used to track changes over short and long periods of time. When smaller changes exist, line graphs are better to use than bar graphs. Line graphs can also be used to compare changes over the same period of time for more than one group. BAR CHART: These are used for categorical data or metric data that are transformed into categorical data and are used to compare things between different groups, or to track changes over time Categories are shown on the horizontal axis. Frequency, percentage, or proportion is shown on the vertical axis. Bars are separated from each other to emphasize the distinctness of the categories. The bars must be of the same width. The length of each bar is proportional to the frequency, percentage, or proportion in the category. Levels ought to be provided on both axes. However, when trying to measure change over time, bar graphs are best when the changes are larger.

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  Storytelling with Data

  A Data Visualization Guide for Business Professionals

  • Cole Nussbaumer Knaflic(Author)
  • 2015(Publication Date)
  • Wiley

    (Publisher)

  Next, let’s shift our discussion to the visuals we tend to think of first when it comes to communicating with data: graphs. Graphs While tables interact with our verbal system, graphs interact with our visual system, which is faster at processing information. This means that a well‐designed graph will typically get the information across more quickly than a well‐designed table. As I mentioned at the onset of this chapter, there are a plethora of graph types out there. The good news is that a handful of them will meet most of your everyday needs. The types of graphs I frequently use fall into four categories: points, lines, bars, and area. We will examine these more closely and discuss the subtypes that I find myself using on a regular basis, with specific use cases and examples for each. Chart or graph? S ome draw a distinction between charts and graphs. Typically, “chart” is the broader category, with “graphs” being one of the subtypes (other chart types include maps and diagrams). I don’t tend to draw this distinction, since nearly all of the charts I deal with on a regular basis are graphs. Throughout this book, I use the words chart and graph interchangeably. 44 choosing an effective visual Points Scatterplot Scatterplots can be useful for showing the relationship between two things, because they allow you to encode data simultaneously on a horizontal x‐axis and vertical y‐axis to see whether and what relation- ship exists. They tend to be more frequently used in scientific fields (and perhaps, because of this, are sometimes viewed as complicated to understand by those less familiar with them). Though infrequent, there are use cases for scatterplots in the business world as well. For example, let’s say that we manage a bus fleet and want to under- stand the relationship between miles driven and cost per mile.

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  Single Case Research Methodology

  Applications in Special Education and Behavioral Sciences

  • Jennifer R. Ledford, David L. Gast, Jennifer R. Ledford, David L. Gast(Authors)
  • 2018(Publication Date)
  • Taylor & Francis

    (Publisher)

  Graphic Displays of Data Types of Graphic Displays Line Graphs Bar Graphs Cumulative Graphs Semi-logarithmic Charts Guidelines for Selecting and Constructing Graphic Displays Figure Selection Graph Construction Data Presentation Using Computer Software to Construct Graphs Tables Summary Important Terms graphic display, abscissa, ordinate, origin, tic marks, axis labels, condition, phase, condition labels, figure caption, line graph, bar graph, cumulative graph, semi-logarithmic chart, scale break, blocking 7 Visual Representation of Data Amy D. Spriggs, Justin D. Lane, and David L. Gast Graphs should represent complex information without distortion, and should serve a clear pur- pose (Tufte, 2001). They should “induce the reader to think about the substance rather than about methodology, graphic design, the technology of graphic production, or something else” (Tufte, 2001, p. 1). Maximizing the impact of your data while minimizing consumer focus on “something else” can be done by following guidelines for graphing data that come from pro- fessional organizations (e.g., American Psychological Association [APA]), historical precedent, and empirical knowledge (i.e., research). In single case design (SCD) research, graphic displays are not only a way to share your outcomes with consumers of your research (as is also common in between-groups studies), but also to enable you to make formative decisions throughout the process of the study. Thus, well-designed graphics are essential in good SCD research. 158 • Amy D. Spriggs et al. Graphic displays (e.g., line graphs, bar graphs, cumulative graphs) and tables serve two basic purposes. First, they assist in organizing data during the data collection process, which facilitates formative evaluation. Second, they provide a detailed summary and description of behavior over time, which allows readers to analyze the relation between independent and dependent variables.

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  Single Case Research Methodology

  Applications in Special Education and Behavioral Sciences

  • Jennifer R. Ledford, David L. Gast, Jennifer R. Ledford, David L. Gast(Authors)
  • 2018(Publication Date)
  • Routledge

    (Publisher)

  7Visual Representation of Data

  Amy D. Spriggs, Justin D. Lane, and David L. Gast

  Important Terms

  graphic display, abscissa, ordinate, origin, tic marks, axis labels, condition, phase, condition labels, figure caption, line graph, bar graph, cumulative graph, semi-logarithmic chart, scale break, blocking

  • Graphic Displays of Data
  • Types of Graphic Displays
    • Line Graphs
    • Bar Graphs
    • Cumulative Graphs
    • Semi-logarithmic Charts
  • Guidelines for Selecting and Constructing Graphic Displays
    • Figure Selection
    • Graph Construction
  • Data Presentation
  • Using Computer Software to Construct Graphs
  • Tables
  • Summary

  Graphs should represent complex information without distortion, and should serve a clear purpose (Tufte, 2001). They should “induce the reader to think about the substance rather than about methodology, graphic design, the technology of graphic production, or something else” (Tufte, 2001, p. 1). Maximizing the impact of your data while minimizing consumer focus on “something else” can be done by following guidelines for graphing data that come from professional organizations (e.g., American Psychological Association [APA]), historical precedent, and empirical knowledge (i.e., research). In single case design (SCD) research, graphic displays are not only a way to share your outcomes with consumers of your research (as is also common in between-groups studies), but also to enable you to make formative decisions throughout the process of the study. Thus, well-designed graphics are essential in good SCD research.

  Graphic displays

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  Successful Statistics for Nursing and Healthcare

  • Roger Watson, Ian Atkinson, Patricia Egerton(Authors)
  • 2017(Publication Date)
  • Red Globe Press

    (Publisher)

  34 Presenting Data – using tables and diagrams to summarise and display Tables and diagrams are increasingly part of daily life. We often see them illus-trating issues in the media – for example graphing how prices have gone up in a certain timeframe, or showing the lengths of patient waiting lists in particular areas, or comparing the hours of sunshine in different holiday resorts. Tables and graphs are also very commonly used to illustrate results from clinical and healthcare research, and they are a tool in decision making for healthcare management. 4 In Chapter 4 we look at: ✔ frequency tables – relative frequencies percentage frequencies cumulative frequencies grouped frequencies ✔ diagrams – pictograms pie charts bar charts cumulative frequency charts histograms ✔ beware! – don’t be misled by diagrams So that we can understand the information to be obtained from tables, diagrams and graphs, we now look at how some of them are constructed. We assume that we have collected data (at appropriate levels of measurement) from relevant samples: when we have the lists of raw data our next job is to make sense of them! Here we shall deal with methods of descriptive statistics , and show how sets of numerical data can be turned into easily understood presen-tations using tables, diagrams and graphs. The manipulations and presentations we use can easily be done on the many spreadsheet, database and statistical packages available for computers. But no matter how sophisticated the software, it should still be ‘driven’ by someone who understands the processes involved – to avoid nonsensical results. The last thing we want is the notorious ‘GIGO’ = ‘Garbage In, Garbage Out’! 4.1 Frequency tables We start by returning to the data set in Table 2.5 which is produced from the questionnaire in Section 2.3 and we find ourselves looking at an apparently incomprehensible jumble of numbers.

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  An Essential Guide to Business Statistics

  • Dawn A. Willoughby(Author)
  • 2016(Publication Date)
  • Wiley

    (Publisher)

  C H A P T E R • 4 Graphical Representation OBJECTIVES This chapter explains how to: • construct charts to display qualitative data - bar chart - pie chart • draw graphs to display quantitative data - scatter diagram - histogram - time series plot - stem and leaf diagram • visually compare multiple data sets using a single graph or chart • understand some of the ways that diagrams can be misinterpreted • choose the appropriate diagram for your data KEY TERMS bar chart histogram pie chart scatter diagram stem and leaf diagram time series plot Introduction Graphs and charts provide a useful method for showing what your data mean in a visual way. When you are working with a small amount of data, a simple table may be sufficient for presenting the data and results. However, if you have collected large sets of data using a questionnaire or through interviewing then a diagram will help you to summarise your results in a concise way, highlight important facts and patterns in the data and describe comparisons between different data sets. When information is presented in a visual form, it is more likely that people will be able to understand and remember the results you are trying to show about the data you have collected. Whether you need to describe your results by writing a report, displaying details on a website or giving a verbal presentation to an audience, the use of graphs and charts is not always straightforward. You should aim to choose a diagram that is appropriate for the data you have collected, the audience you are writing for, and the type of results to be shown. It is also important that diagrams are drawn carefully and accurately so that the audience does not misinterpret their meaning because of the way in which the data are presented. Bar Charts Qualitative data are often displayed using a bar chart. This is a diagram drawn with rectangular bars where each bar represents a different category in the data set.

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  Experimental Methods for Science and Engineering Students

  An Introduction to the Analysis and Presentation of Data

  • Les Kirkup(Author)
  • 2019(Publication Date)
  • Cambridge University Press

    (Publisher)

  3 Graphical Presentation of Data 3.1 Overview: The Importance of Graphs Our ability to absorb and process information when it is presented in the form of a picture is so good that it is natural to exploit this talent when analysing data obtained from an experiment. When data are presented pictorially, trends or fea- tures in the data can be detected that we would be unlikely to recognise if the data were given only in tabular form. This is especially true in situations where a set of data consists of hundreds or thousands of values, which is a common occurrence when a computer is used to assist in data gathering. Additionally, a pictorial representation of data in the form of a graph is an excellent way to summarise many of the important features of an experiment. A graph can indicate: (i) the quantities being studied (ii) the range of values obtained through measurement (iii) the uncertainty in each value (iv) the existence or absence of a trend in the data gathered (for example, plotted points may lie in a straight line or a curve, or may appear to be scattered randomly across the graph) (v) which plotted points do not follow the general trend exhibited by most of the data. x–y graphs (also known as scatter plots or Cartesian coordinate graphs) are used extensively in science and engineering to present experimental data, and it is those that we will concentrate on in this chapter. 3.2 Plotting Graphs An x–y graph possesses horizontal and vertical axes, referred to as the x and y axes, respectively. Each point plotted on the graph is specified by a pair of numbers termed the coordinates of the point. For example, point A in Figure 3.1 has the coordinates x = 20, y = 50. The coordinates of the point may be written in shorthand as (x,y), which in the case of point A on Figure 3.1 would be (20,50). To assist in the accurate plotting of data, graph paper may be used on which are drawn evenly spaced vertical and horizontal gridlines as shown in Figure 3.1.

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  Single Subject Research

  Strategies for Evaluating Change

  • Thomas R Kratochwill(Author)
  • 2013(Publication Date)
  • Academic Press

    (Publisher)

  Relevant data that can be presented in simple graphic form have the best cost:benefit ratio. When preparing graphs for publication, obtain details of the format preferred by the editors. The Publication Manual of the Ameri-can Psychological Association (2nd ed.) has detailed guidelines (pp. 50-55) on the preparation of figures for the publications it sponsors. Since these guidelines have also been adopted by a large number of non-American Psychological Association journals (see Appendix B of the Manual), it is a useful addition to one's professional library. The editors of the Journal of Applied Behavior Analysis (JABA) have provided additional instructions on the preparation of graphs for intending authors (see JABA, 1976, 9, 24). . i Factors contributing to the determination of the proportions of a graph's rectangle are the accuracy with which particular dimensions repre-sent changes in the variable(s) of interest, the data to be displayed, the type of graph chosen to portray those data, and the space available for the display of the graph. Behavioral data are usually plotted as changes in the dependent variable over time as a function of the systematic introduction and/or withdrawal of the independent, experimental variable. The magnitude of these changes is expressed vertically on a line or column graph, and horizontally on a bar graph. Distortion of the relative magnitude of the data points is likely to result if the scale (usually the F scale) representing the dependent variable(s) is longer or has more widely spaced scale graduations than that for the independent variable(s). Distortion can also result when the escale is fore-shortened or attenuated, since vertical changes are emphasized when the data path fluctuates sharply close to the baseline (see Fig. 2.6). A scale-break should be used to notify a reader that the scale has been abbreviated.

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  Research Methods

  • Theresa White, Donald McBurney(Authors)
  • 2012(Publication Date)
  • Cengage Learning EMEA

    (Publisher)

  15. The summary data should be checked for invalid data, missing data, and outliers. 16. Figures should conform to the style described in this chapter and in the APA Publication Manual . Keep in mind that the purpose of a figure is to communicate information about your data. Suggestions for Further Reading C LEVELAND , W. S. (1994). The elements of graphing data (2nd ed.). Monterey, CA: Wadsworth Advanced Book Program. Despite the title, a high-level discussion of graphing techniques. M ILLSAP , R. E. & M AYDEU -O LIVARES , A. (2009). The SAGE handbook of quantitative methods in psy-chology . Thousand Oaks, CA: Sage. Valuable mathematical background for this chapter. M OSTELLER , F. , F EINBERG , S. E. , & R OURKE , R. E. K. (1983). Beginning statistics with data analysis . Reading, MA: Addison-Wesley. An excellent intro-duction to statistics, with an emphasis on explor-atory data analysis. T UFTE , E. R. (2001). The visual display of quantitative information (2nd ed). Cheshire, CT: Graphics Press. An enlightening discussion of graphing with many specific hints and examples. T UKEY , J. W. (1977). Exploratory data analysis . Reading, MA: Addison-Wesley. Very practical introduction to dealing with data. A CASE IN POINT Professor Smith ’ s Slide Presentation Professor Smith was about to present a paper on his research on food preferences at a psychology convention. As is customary, he gave an informal practice talk to the members of his department before going to the convention. The slides that he presented are shown in Figure 14.18. Following is a description of the data on which they are based: 1. The ratings of preference, on a scale of 1 to 5, of 10 subjects for four foods (1 = dislike intensely, 2 = dislike moderately, 3 = neutral, 4 = like moderately, 5 = like intensely). (Figure 14.18a) 2. Frequency distribution showing how many people liked one, two, three, or four of the sample foods.

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  Effective Writing

  Improving Scientific, Technical and Business Communication

  • John Kirkman, Christopher Turk(Authors)
  • 2002(Publication Date)
  • Routledge

    (Publisher)

  When things are easy, when there are few distractions, when people are highly motivated, then the better of two formats shows only a slight advantage, but as working conditions become less optimal the disadvantages of a poorer format become considerably greater. This is a point of particular relevance to technical communicators who are often designing information in relatively ideal conditions. Hence their intuitive feel for the differences between alternative formats may suggest that such differences are marginal. Indeed the differences may not even be available to intuition. This is why there is an advantage in having a body of research findings to which the technical communicator can turn.

  Dr Wright’s article, Behavioural Research and the Technical Communicator, from which this passage is taken, is a valuable record of that body of research.

  Fig. 10.14 Bar chart giving the same information as Fig. 10.13 , with greater visual impact (reproduced by permission of HMSO).

  Pie charts and surface charts

  Another type of chart, the pie chart, is useful for presenting information that is related to time or proportions. For example, the table in Fig. 10.20 presents the results of an analysis of outgoing telephone calls made by an organization during the first hour of a working day. The table certainly makes all the details available for scrutiny; but the clock-face analogue of the pie chart in Fig. 10.21 shows with greater impact the proportion of long-distance calls to local calls throughout the hour, especially the ‘rush’ of people who made long-distance calls as soon as work began.

  Fig. 10.15 Bar chart with helpful labelling, but with a suppressed zero.

  Fig. 10.16 Presentation of test results in bare numerical form.

  In drawing pie charts, remember that it is easiest for readers to read clockwise from the twelve o’clock position. Also, it is normally most effective to place larger segments first, provided that does not distort a time sequence.

  Another chart that is useful for showing proportions within rising figures over a period of time is a surface chart. A surface chart is a cross between a chart and a graph. The example in Fig. 10.22

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  Business Statistics for Contemporary Decision Making

  • Ken Black, Tiffany Bayley, Ignacio Castillo(Authors)
  • 2023(Publication Date)
  • Wiley

    (Publisher)

  Stem-and-leaf plots are another way to organize data. The numbers are divided into two parts, a stem and a leaf. The stems are the leftmost digits of the numbers and the leaves are the rightmost digits. The stems are listed individually, with all leaf values corresponding to each stem displayed beside that stem. LEARNING OBJECTIVE 2.3 Describe and construct dif- ferent types of qualitative data graphs, including pie charts, bar charts, and Pareto charts. Explain when these graphs should be used. Qualitative data graphs presented in this chapter are pie charts, bar charts, and Pareto charts. A pie chart is a circular depiction of data. The amount of each category is represented as a slice of the pie proportion- ate to the total. The analyst is cautioned in using pie charts because it is sometimes difficult to differentiate the relative sizes of the slices. The bar chart or bar graph uses bars to represent the frequencies of various qualitative categories. The bar chart can be displayed horizontally or vertically. A Pareto chart is a vertical bar chart that is used in the quality movement in business to graphically display the causes of problems. The Pareto chart presents problem causes in descending order to help the decision-maker determine which problems to solve first. Why Statistics Is Relevant The old clich “a picture is worth a thousand words” is put to the test in this chapter. Charts and graphs are effective visual tools: they present information quickly and easily. Charts and graphs are powerful in business because the human mind takes the quickest route to understand reality, and visual statistics are often the answer to understanding managerial problems. It is certainly not surprising that charts and graphs are heavily used by print and electronic media. Key Considerations Ethical considerations for the techniques learned in Chapter 2 begin with the data chosen for representation.

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