Bar Graphs
Bar graphs are a visual representation of data using bars of different heights or lengths to show the frequency or distribution of categories. The length or height of each bar corresponds to the value it represents. They are commonly used to compare and contrast different categories or to track changes over time.
8 Key excerpts on "Bar Graphs"
eBook - ePub- Jim Fowler, Lou Cohen, Philip Jarvis(Authors)
- 2013(Publication Date)
- Wiley(Publisher)
...(See also the dot plot in Section 5.3.) 4.3 Bar graph Portraying information by means of a bar graph is particularly useful when dealing with data gathered from discrete variables that are measured on a nominal scale. A bar graph uses lines (i.e. bars) to represent discrete categories of data, the length of the line being proportional to the frequencies within that category. Suppose 31 nest boxes are placed in a wood, and 15 become occupied by blue tits, 10 by great tits, 4 by tree sparrows and 2 by nuthatches. A frequency table may be constructed: f blue tit 15 great tit 10 tree sparrow 4 nuthatch 2 — n = 31 Using these data, a bar graph may be constructed, as shown in Fig. 4.2. Fig. 4.2 Bar graph showing nest box occupancy. Fig. 4.3 Frequency distribution of orchid counts. In its final form, the horizontal dashed lines are omitted; they are included here to show that the height of the bar corresponds to the respective frequency. When observations are counts of things the bar graph is a useful way to present a frequency distribution. Illustrators often replace each bar with a vertical rectangle, or block, whose adjacent sides are touching. The frequency distribution of orchid counts shown as a dot diagram in Fig. 4.1 is shown as a bar graph in Fig. 4.3, where the height of each block is still proportional to the frequency in each category because the width of each block is equal. When presented in this form the diagram is usually referred to as a histogram. Histograms are especially useful for presenting frequency distributions of obervations measured on continuous variables, as we show in Section 4.4. 4.4 Histogram The histogram is especially useful for presenting distributions of observations of continuous variables. In a histogram the area of each block is proportional to the frequency...
- Bruce B. Frey(Author)
- 2018(Publication Date)
- SAGE Publications, Inc(Publisher)
...Audrey Michal Audrey Michal Michal, Audrey Priti Shah Priti Shah Shah, Priti Bar Graphs Bar Graphs 168 170 Bar Graphs Bar Graphs (also called bar charts) are a type of data visualization in which data points are represented by rectangular bars. Typically, the bars extend vertically from the bottom of the x- axis up to the data value, which is plotted along the y -axis; thus, the height of the bar (physical magnitude) is analogous to the numerical magnitude of the data point; bars may also be horizontal with length representing magnitude. Each data point is either labeled along the x -axis or referenced in a legend in a separate location near the graph. This entry discusses how Bar Graphs are used, factors that affect comprehension of Bar Graphs, and implications for educational research. Bar Graphs are often used to communicate scientific results, qualitative trends, and statistical analyses, such as main effects and interactions. Because data points are aligned along a common axis, Bar Graphs can facilitate comparison between individual data points; for instance, a user can quickly assess whether the data points are the same or different. Additionally, a user can easily compare differences between data points by judging the relative sizes of height gaps between bars. Global patterns, such as linear trends, are also salient in Bar Graphs. Thus, Bar Graphs are generally better for visualizing qualitative data patterns than exact values, which are more easily extracted from tables. In Figure 1, a simple bar chart shows the percentage of times different classroom assessment formats were used by a sample of teachers. Figure 1 Percentage of times for different classroom assessment formats Factors That Affect Comprehension The visual features of a bar graph, such how the bars are organized and how far apart the bars are from one another, can affect comprehension...
eBook - ePubStatistics
The Essentials for Research
- Henry E. Klugh(Author)
- 2013(Publication Date)
- Psychology Press(Publisher)
...These are also plotted from the data of Table 2.2. The histogram consists of a series of adjacent bars whose heights represent the number of subjects obtaining a score and whose location on the abscissa represents the value of the score. Notice that the vertical lines marking off the bars do not originate from the center of the score interval but from its edges. The edges of the individual bars mark the theoretical limits of the score intervals along the abscissa. Figure 2.4 Histogram of the examination scores tallied in Table 2.2. Figure 2.4a A histogram of the examination scores tallied in Table 2.2. Sometimes frequency polygons, or histograms of two different distributions, will both be plotted on the same set of coordinates. If the differences between the distributions are subtle, this procedure may highlight them. Whether one uses a frequency polygon or a histogram to represent data is largely a matter of personal preference. 2.7 Bar Charts Bar charts are the preferred graphs when data are discrete, that is, when they result from the process of counting. This convention is somewhat fluid in psychology, where ordinal scales are concerned, but it should be followed without exception for nominally scaled data, that is, for nonorderable countables. The bar chart is very much like the histogram except that spaces are left between the bars in the bar chart. Bar charts sometimes use the vertical axis to represent categories and the horizontal axis to represent frequency of occurrence. Study the bar chart in Figure 2.5 where we have graphed the enrollment in introductory courses for science departmennts at a typical college. Figure 2.5 A bar chart of enrollment in introductory science courses. 2.8 Grouped Frequency Distributions We now consider a more complex kind of frequency distribution called a grouped frequency distribution, but first we call your attention to the approximate nature of all continuous measurements...
eBook - ePub- Hugh Coolican(Author)
- 2018(Publication Date)
- Routledge(Publisher)
...Chapter 14 Graphical representation of data This chapter deals with the representation of data sets in charts or graphs. In a bar chart frequencies of data in discrete categories are presented for comparison and this must be done fairly, without visual distortion. Line charts are useful for demonstrating a time series – changes over time in a measure of a person or group. Interval data points, grouped into continuous categories, can be represented graphically as a histogram or as a frequency polygon. Tukey (1977) promoted techniques of exploratory data analysis with an emphasis on thorough examination of patterns before submitting data sets to tests of statistical significance. Two methods are included here: stem and leaf diagrams, and box-plots. SPSS procedures are included for common types of chart. Graphs in general People who dislike statistics nevertheless tend to like drawing graphs. However they are also prone to putting far too many of them into a report to make it look more interesting. It’s worth stopping to think, just what is a graph or chart for? It is not to make your report look more scientific or credible. Basically it transmits useful information to your reader. It should be a way of summing up at a glance the main features of your data or some important aspect of them. If it doesn’t do that, if it isn’t easy to understand completely (without referring to the text in your report) or if it presents the absolutely obvious, then it isn’t a good or useful chart. Before you rush to produce what many students find to be the most artistic part of a psychological research report, do take note of some cautionary advice. Over-production and decoration – don’t scatter charts around your report showing every conceivable arrangement of data and in a profusion of pretty colours and patterns. You should be very parsimonious and only produce what will be helpful, not distracting, to your reader...
eBook - ePubStatistics: An Introduction: Teach Yourself
The Easy Way to Learn Stats
- Alan Graham(Author)
- 2017(Publication Date)
- Teach Yourself(Publisher)
...In fact, if you are creating these sorts of charts using a spreadsheet or computer graphing package you will probably find that vertical bar charts are more correctly referred to as column charts. In situations where the names are rather wordy, there may not be enough space to write them along the horizontal axis. In this case, it would make sense to draw the bars horizontally rather than vertically, as shown in Figure 3.3. With a spreadsheet or graphing package, such a chart may simply be referred to as a bar chart. Figure 3.3 Horizontal bar chart In general, then, horizontal bars are useful when there is quite a large number of categories and some of the category names are long. Two other forms of bar chart are worth mentioning – the compound and component bar chart. A compound bar chart is a bar chart where the bars are grouped two or three at a time in order to convey information about more than one measure. For example, the compound bar chart in Figure 3.4 shows the average life expectancy in 2014 for a selection of four particular continents. The added dimension here is that the bars are arranged in pairs to show the information for men and women separately. Notice that there is a key (sometimes called a legend) on the right matching the shading of the bars, which shows which bars refer to men and which to women. Figure 3.4 Compound bar chart Source : Statista, The Statistics Portal, www.statista.com/statistics/270861/life-expectancy-by-continent/ The main feature of this bar chart is that it enables the reader to interpret two different sets of information – for example it reveals that women have a greater life expectancy than men but also that the continent of Africa has a lower life expectancy than other continents. A component bar chart can be drawn with each bar split up to reveal its component parts...
eBook - ePubStatistical Literacy at School
Growth and Goals
- Jane M. Watson(Author)
- 2013(Publication Date)
- Routledge(Publisher)
...The perception, held by some for many years, that “the graph” was the start and finish of data handling, should be fast disappearing. The wide range of graphical representations that are available sometimes leads to frustration for teachers when they have a limited time to cover graphing and want to cover just the important types of graphs. There are also occasionally disputes among textbook writers and curriculum developers about details of graph production. When is a bar graph a histogram? When does one leave gaps between bars? When does one connect dots with lines? What are the rules to construct the whiskers on a box-and-whisker plot? These issues are not dealt with here and no attempt is made to provide a comprehensive coverage of all possible graphical representations. Specific curriculum documents provide guidance. 4 What is important, and the emphasis of this chapter, is the story that graphs tell about data: how graphs are created to tell the story and how they are interpreted once created. One type of graph however deserves special attention because it is used for some of the tasks introduced in later sections. In some curriculum documents and materials it is referred to as a “line plot,” 5 reflecting the scaled base line above which dots or Xs are piled to represent data values. Because of the confusion with the term line graph, referring to a graph where straight lines connect data points, the term stacked dot plot is used here. 6 It is a more visual phrase that can assist students in distinguishing it from other forms, particularly the line graph. Because graphing of various sorts has been in the mathematics curriculum for a long time, there has been considerable research on student understanding. Some aspects of the cognitive demands of coordinate graphing are common to the needs of plotting algebraic functions as well as statistical representations, whereas other demands are different for the fields of algebra and statistics...
eBook - ePubStatistics for Psychologists
An Intermediate Course
- Brian S. Everitt(Author)
- 2001(Publication Date)
- Psychology Press(Publisher)
...see.” During the past two decades, a wide variety of new methods for displaying data have been developed with the aim of making this particular aspect of the examination of data as informative as possible. Graphical techniques have evolved that will provide an overview, hunt for special effects in data, indicate outliers, identify patterns, diagnose (and criticize) models, and generally search for novel and unexpected phenomena. Good graphics will tell us a convincing story about the data. Large numbers of graphs may be required and computers will generally be needed to draw them for the same reasons that they are used for numerical analysis, namely that they are fast and accurate. This chapter largely concerns the graphical methods most relevant in the initial phase of data analysis. Graphical techniques useful for diagnosing models and interpreting results will be dealt with in later chapters. 2.2. Pop Charts Newspapers, television, and the media in general are very fond of two very simple graphical displays, namely the pie chart and the bar chart. Both can be illustrated by using the data shown in Table 2.1, which show the percentage of people convicted of five different types of crime. In the pie charts for drinkers and abstainers (see Figure 2.1), the sections of the circle have areas proportional to the observed percentages. In the corresponding bar charts (see Figure 2.2), percentages are represented by rectangles of appropriate size placed along a horizontal axis. Fig. 2.1. Pie charts for drinker and abstainer crime percentages. Fig. 2.2 Bar charts for drinker and abstainer crime percentages. Table 2.1 Crime Rates for Drinkers and Abstainers Crime Drinkers Abstainers Arson 6.6 6.4 Rape 11.7 9.2 Violence 20.6 16.3 Stealing 50.3 44.6 Fraud 10.8 23.5 Despite their widespread popularity, both the general and scientific use of pie charts has been severely criticized...
- Nicoleta Gaciu(Author)
- 2020(Publication Date)
- SAGE Publications Ltd(Publisher)
...3 Graphical representation of data Chapter Objectives In this chapter, we will: introduce the concept of graphical representation of educational data present key principles for the graphical representation of data consider the essential features of different methods to visualise quantitative data understand how to create and work with tables and graphs in R correctly demonstrate examples from educational research to illustrate the use of graphs and tables for different types of variables and scales of measurement. The graphical representation of data is the process of transformation of data into information through a wide range of graphical displays, including graphs, maps, pictograms and tables in a symbolic representation. This process is a vital part of data analysis that facilitates the process of identifying, interpreting and understanding patterns or trends, which may not be visible in the raw data. It is also a useful and accurate communication tool for a range of educational stakeholders. A proper understanding of graphical display is one of the most important aspects of data analysis for students, teachers and researchers, helping them to avoid mistakes when summarising large data sets and analysing relevant patterns in quantitative data. For anyone engaged in educational research, it is very helpful to find relevant patterns in the graphical representation of data before performing any statistical tests or transforming statistical values into more meaningful concepts. The graphical representation of data depends on the type of quantitative data. For example, to organise and summarise categorical data, a bar graph can be used. For a time series, a line graph is recommended. Small data sets are usually easier to interpret if data is displayed in tabular form...
