¶ … real life example, we would compare the quarterly sales over 4 years. For this the following values would be made
Line Graphs
Pie Charts
Colum Chart
Scatter Charts
Misleading charts and graphs
Graphs and charts are tools for statistical analysis of data and information. Graphs and charts help identify and illustrate in a meaningful manner, the trends and details of the data.
Sometimes, data or information involves very large volume of data and would be too cumbersome to get them printed or to make non-technical people understand the trends and details of the data. On such occasions, using graphs and charts to represent the data in a simple and understandable manner is useful (Bhaduri and Ghosh, 2014).
Therefore it can be said that a graph or a chart shows thousands of information in a picture and help convey information quickly and easily to the user. The salient features of the data are highlighted by graphs and charts. Often relationships between various sets of data cannot easily be related. Graphs and charts helps relate and compare such data sets.
Graphs and charts therefore help to convey to the users comparisons and relationships, distribution, trends, composition, flow and/or process and location that are sought to be obtained from a data set.
Easy-to-understand formats that clearly and effectively communicate important points is enabled by graphs and charts by the condensation of large amounts of information.
The selection of the type of chart or graph to be used, the purpose of the graph or chart needs to be considered in terms of what one wants to present. For example, one could choose between expressing certain data set in the form of frequencies, percentages or categories.
Also the type of data that one is working with needs to be considered while selecting the chart or graph type.
While categorical data are grouped into non-overlapping categories such as grade, race, and yes or no responses, this can be represented by bar graphs, line graphs and pie charts. On the other hand continuous data are measured on a scale or continuum like such as weight or test scores which can be best represented through tools like histograms (Dehmer and Emmert-Streib, n.d.).
In this question we would discuss the types of charts and graphs that can be used for quantitative analysis.
There are also several types of quantitative data such as:
Discrete Data -- this is data that has distinct values or observations like 5 customers, 17 points, 12 steps etc.
Continuous Data -- this type of data is represents any value or observation within a finite or infinite interval like conversion rate, visits, page views, bounce rate, height, weight etc. (Forsyth, 2013).
Quantitative data can be summarized through mean, median, mode, standard deviation etc. And for this column chart, bar chart, line chart, Histogram etc. can be used.
In this question we would look into the usefulness of bar and line graphs and pie charts, column charts and scatter charts for analysis of quantitative data.
Types of Graph
Bar Graphs
Direct comparison of two or more sets of data is done by the use of bra graphs. This is used when the number of time intervals is small and when there is time series data.
Such graphs generally tend to have 0 as the baseline if all values are positive integers. Zero would be the midpoint of the scale in cases where the values include both positive and negative integers such as in the case of graphing differences in means.
However the scale ranges should not vary between graphs and should be standardized whenever possible. It is best not to use 3-D features in a bar graph as such graphs are complex in nature and makes them ineffective in conveying results to most audiences. It also leads to distortion of data.
Both horizontal and vertical bars can be included in bar graphs. But horizontal bar charts are rarely used to portray time series. In order to have the maximum effect of comparison of data and information in a bar graph, the columns should be sorted in some systematic order, most often according to size of value, to have visually effective schema.
The standardized grade scale is used to order findings by a particular category. Without the presence of a standard base line, stacked bar graphs that are composed of one or more segmented bars where each one of the segment represents the relative share of a total category, are not very effective in conveying data and for comparison especially in among the second, third or subsequent segments (Hsin-Yi Tsai, Yu-Lun Huang and Wagner, 2009).
It is preferable to create a bar graph that groups these values together, side by side when the graphing data from two or more different series, or different classes within the same series.
Taking a real life example, we would compare the quarterly sales over 4 years. For this the following values would be made:
The Revenue in dollars would be placed along one axis.
The time i.e. quarter number, would be plotted along another axis.
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