A bar graph is the most common method of statistical representation and it is used to create visual presentations of quantifiable data variables. This tool helps researchers to effectively manage large sets of data by categorizing them based on their numerical values.
Specifically, it breaks categorical data sets into groups based on numerical differences, and it is made up of response and predictor variables. It is important for researchers to know how to plot a bar graph as well as the different types of bar graphs that are available.
A bar chart or bar graph is a diagrammatic representation of data in quantities. It is a common statistical tool used for data categorization and it often highlights the differences in the numerical values of specific groups of data.
Typically, the data in a bar graph is represented using vertical or horizontal bars that are plotted in accordance with the statistical value of each data category. This means that the length or height of each bar is proportionally equivalent to the data that it represents.
In some instances, the bar chart can be plotted in clusters to show more than one measured group of data. Typically, one axis of the graph details specific data categories while the other axis highlights the measured value for comparison.
A bar chart can be categorized into two broad types, namely; horizontal and vertical bar charts. These groups are further subdivided into the various categories such as vertical stacked bar chart, horizontal grouped bar chart, and the like.
A horizontal bar chart is a type of bar graph that represents data variables using proportional horizontal bars. Here, the data categories are placed on the vertical axis of the graph while the numerical value is placed on the horizontal axis of the graph.
Horizontal bar charts are often used to represent comparisons between nominal variables. With this tool, you can display long data labels using horizontal rectangles and still have enough room for textual information.
A horizontal stacked bar chart is a graphical variation that is used for data segmentation. Typically, each horizontal bar in the graph represents a data category which is divided into subcategories using different colors within the same bar.
This type of bar graph is extremely useful for viewing the different segments that make up a data variable. It helps you to know which subcategory contributes the most to a data variable.
A horizontal grouped bar chart is a variant of a bar graph in which multiple data categories are compared and a particular color is used to denote a definite series across all data categories represented. It is also known as a clustered bar graph or a multi-set bar chart.
In simple terms, a horizontal grouped bar chart uses horizontal bars to represent and compare different data categories of 2 or more groups. The data categories are placed side by side so that it is easy to identify and analyze the differences in the same category across data groups.
A horizontal grouped bar chart is used for market performance evaluation and financial data comparison.
A segmented horizontal bar chart is a type of stacked bar chart. It is also called a 100% stacked bar graph because each horizon bar represents 100% of the discrete data value and all the bars are of the same length while numerical variations are indicated in percentages.
Other types of horizontal bars chart include a reverse horizontal bar chart and a basic horizontal bar chart.
A vertical bar graph is the most common type of bar chart and it is also referred to as a column graph. It represents the numerical value of research variables using vertical bars whose lengths are proportional to the quantities that they represent.
A vertical stacked bar chart is a type of bar graph that uses vertical bars to compare individual data variables. This statistical tool stacks data categories so that each bar shows the total number of subcategories that make up a data set.
A grouped vertical bar chart is also known as a cluster chart and shows information about different subcategories of a data set. It can be used to show several sub-groups of each category however if the chart contains too much information, it can become complicated and difficult to read and interpret.
Just as a segmented horizontal bar graph, this method of data representation uses vertical bars to show total discrete variables in percentages.
In the section, we’ll be giving you a step-by-step guide on how to construct different types of bar chart with excel. Learn how to use arrange your data into excel tables, select the kind of bar chart you want to construct, and how to visualize them.
Here is a step-by-step guide on how to represent data categories in a stacked bar graph using a spreadsheet
Here is a step-by-step guide on how to create a grouped bar chart graph in Excel:
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Formplus allows you to create powerful online surveys and questionnaires in minutes. It also offers multiple sharing options for you and respondents can fill and submit form responses even when they do not have access to the internet.
In addition to the form builder’s report summary tool, which generates custom visual reports in minutes, Formplus fully integrates with Google Sheets. Google Sheets integration automatically sends form responses to your spreadsheet, eliminating the need to export or import data.
Formplus also allows you to export form responses as a CSV file. This makes it easy for you to generate different types of bar graphs and charts for form data analysis.
A bar graph simplifies the data analysis process by helping you to manage large volumes of data easily. Plotting your research data in a bar chart would allow you to easily compare, visualize and comprehend different data variables at a glance.
Another advantage of using a bar graph for statistical analysis is that it helps you to map out and track data changes over a period of time. While pie charts depict only one data set, bar graphs effectively represent multiple data sets over time.
A bar chart is extremely useful for tracking customer base growth or revenue generation patterns.
In addition, a bar chart aids comparison across different sets of data because it clearly shows the relationship between each research variable and the fixed numerical value.
Researchers cannot use bar graphs to represent data gathered through qualitative observation methods.They exclusively represent quantifiable data variables, meaning data sets measurable with numerical values
Bar graphs can become extremely complex to understand; especially when dealing with large sets of data.
A bar chart does not account for any causative factors, key assumptions or patterns responsible for the statistical variations in a research data sample.
It is almost impossible to avoid plotting out quantitative data on a bar graph or chart. This is because this statistical tool aids data categorization for analysis. A researcher must understand the different types of bar graphs, the characteristics of each type. More importantly, how to plot out a bar graph on a data spreadsheet.
In this article, we have highlighted step-by-step guides for plotting different types of bar graphs. This includes horizontal bar graphs, segmented bar graphs, and cluster vertical graphs. Although bar graphs can become extremely complex to understand, they help. They help researchers to easily process large amounts of data and arrive at research outcomes.
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