Displaying data in research is the last step of the research process. It is important to display data accurately because it helps in presenting the findings of the research effectively to the reader. The purpose of displaying data in research is to make the findings more visible and make comparisons easy. When the researcher will present the research in front of the research committee, they will easily understand the findings of the research from displayed data. The readers of the research will also be able to understand it better. Without displayed data, the data looks too scattered and the reader cannot make inferences.
There are basically two ways to display data: tables and graphs. The tabulated data and the graphical representation both should be used to give more accurate picture of the research. In quantitative research it is very necessary to display data, on the other hand in qualitative data the researcher decides whether there is a need to display data or not. The researcher can use an appropriate software to help tabulate and display the data in the form of graphs. Microsoft excel is one such example, it is a user-friendly program that you can use to help display the data.
Tables for displaying data in research
The use of tables to display data is very common in research. Tables are very effective in presenting a large amount of data. They organize data very well and makes the data very visible. A badly tabulated data also occurs, in case, you do not have knowledge of tables and tabulating data consult a statistician to do this step effectively.
Parts of a table
To know the tables and to tabulate data in tables you should know the parts or structure of the tables. There are five parts of a tables, namely;
The title of the table speaks about the contents of the table. The title should have to be concise and precise, no extra details. The title should be written in sentence case.
The column at the left-most of the table is called as stub. A stub has a stub-heading at the top of the column, not all tables have stub. The stub shows the subcategories that are listed along Y-axis.
The caption is the column heading, the variable might have subcategories which are captioned. These subcategories are provided on the X-axis, the captions are provided on the top of each column.
The body of the table is the actual part of the table in which resides the whole values, results, and analysis.
There can be many different types of notes that you may have to provide at the end of the table. The footnotes are provided just below the table and labeled as the source. The source generally are provided when the table has been taken from some other source. They are also provided for explaining some point in the table. Sometimes there is some part of the table that is taken from a source so it should also be mentioned.
Types of tables
Tables are the most simple means to display data, they can be categorized into the following;
These categories are based on the numbers of variables that need to be tabulated in the table. A univariate table has one variable to be tabulated; a bivariate table, as the name suggests, has two variables to be tabulated and a polyvariate table has more than two variables to be tabulated.
Graphs to display data
The purpose of displaying data is to make the communications easier. Graphs should be used in displaying data when they can add to the visual beauty of the data. The researcher should decide whether there is a need for table only or he should also present data in the form of a suitable graph.
Types of graphs
You can use a suitable graph type depending on the type of data and the variables involved in the data.
The histogram is a graph that is highly used for displaying data. A histogram consists of rectangles that are drawn next to each other on the graph. The rectangles have no space in between them. A histogram can be drawn for a single variable as well as for two or more than two variables. The height of the bars in the histogram represent the frequency of each variable. It can be drawn for both categorical and continuous variables.
The bar chart
The bar chart is similar to a histogram except in that it is drawn only for categorical variables. Since it is used for categorical variables, therefore, it is drawn with space between the rectangles.
The frequency polygon
A frequency polygon is also very much like a histogram. A frequency polygon consists of frequency rectangles drawn next to each other but the values taken to draw the rectangles is the midpoint of the values. The height of the rectangles describes the frequency of each interval. A line is drawn that touches the midpoints at the highest frequency level on Y-axis and it touches the X-axis on each extreme end.
The cumulative frequency polygon
The cumulative frequency polygon is also a frequency polygon, it is drawn using the cumulative frequencies on the Y-axis. The values on the X-axis are taken by using the endpoints of the interval. The endpoints of the interval are joined to each other the reason being that the cumulative frequency is always based on the upper limit of an interval.
The stem and leaf display
The stem and leaf display is another easy way to display data. The stem and leaf display if rotated to 90 degrees become a histogram.
The pie chart
The pie chart is a very different way to display data. The pie chart is a circle, as a circle has 360 degrees so it is taken in percentage and the whole pie or circle represent the whole population. The pie or circle is divided into slices or sections, each section represents the magnitude of the category or the sub-category.
The trend curve
The trend curve is also called as the line diagram. It is drawn by plotting the midpoints on the X-axis and the frequencies commensurate with each interval on the Y-axis. The trend curve is drawn only for a set of data that has been measured on the continuous, interval or ratio scale. A trend diagram or the line diagram is most suitable for plotting values that show changes over a period of time.
The area chart
The area chart is a variation of the trend curve. In area chart, the sub-categories of a variable can be displayed. The categories in the chart are displayed by shading them with different colors or patterns. For example, if there are both males and females category in the dataset both can be highlighted in this chart.
A scattergram is a very simple way to plot the data on a chart. The scattergram is used for data where the change in one variable affects the change in the other variable. The frequency against each interval is plotted with the help of dots.