Since the primary data is in raw form or haphazard, it is not easy to examine the unorganized data. The scientist or researcher has organized the data in an understandable and meaningful way. In this post, we will learn about the organization/ presentation of data in Statistics. The presentation of data in statistics is a vital aspect, as it transforms raw data into meaningful and understandable information.
Table of Contents
Classification/ Presentation of Data in Statistics
The classification is a widely used data organization technique which is further classified into three categories
- Tabulation (Frequency Distribution and Contingency Tables)
- Graphical Presentation of Data (Bar charts, Pie charts, scatter diagrams. line charts, etc.)
- Textual Presentation of Data (Descriptive Statistics)
Classification of Data
Classification is defined as the process of dividing a set of data into different groups or categories so that they are homogeneous with respect to their characteristics and mutually exclusive. In other words, classification is a method that divides a set of data into different heterogeneous groups or sorts the data into different heterogeneous groups, by sort we mean a systematic arrangement of objects, individuals, and units in such a way that different categories are created.
The data can be classified/presented/organized in different ways, such as color classification, age classification, gender classification, and grade classification.
Tabulation
The classification of data in tabular form with suitable headings of tables, rows, and columns is called tabulation. There are different parts or components of a table: (i) Title, (ii) Column Caption, (iii) Row Caption, (iv) Footnotes, (v) Source note.
- Table Number: A number is allocated to the table for identification, particularly when there are a lot of tables in the study.
- Title: The title of the table should explain what is contained in the table. The title must be concise, clear, brief, and set in bold type font on the top of the table. It may also indicate the time and place to which the data refer.
- Stub or Row Designations: Each row of the table should be given a brief heading called stubs or stub items. For columns, it is called the stub column.
- Column Headings or Captions: column designation is given on top of each column to explain to what the figures in the column refer. It should be concise, clear, and precise. This is called caption, or heading. Columns can also be numbered if there are four or more columns in a table.
- Body of the Table: The data should be organized/ arranged in such a way that any data point/ figure can be located easily. Various types of numerical variables should be arranged in ascending order from left to right in rows and from top to bottom in columns. The columns and rows totals can also be given.
- Source: At the bottom of the table, a note should be added indicating the primary and secondary sources from which data have been collected
- Footnotes and references: If any item has not been explained properly, a separate explanatory note should be added at the bottom of the table.
Importance of Tabulation
In Tabulation, data are arranged and it makes data brief.
- In tabulation, data is divided into various parts and for each part, there are totals and sub totals. Therefore, relationships between different parts can easily be established.
- Since data is organized in a table with a title and a number, data can be easily identified and used for the required purpose.
- Tables can be easily presented in the form of graphs.
- Tabulations make complex data simple making it easy to understand the data.
- Tabulation also helps in identifying mistakes and errors.
- Tabulation condenses the collected data and it becomes easy to analyze the data from tables.
- Tabulation saves time and costs as it is the easiest and most comprehensive method used to organize the data.
- Since tabulation summaries, the large scattered data, the maximum information may be gained/collected from these tables.
Limitations of Tabulation
- Tables contain only numerical data. The tables do not contain further details.
- Qualitative expressions are not possible through tables.
- Usually, tables are used by experts to conclude, but common men cannot understand them properly.
Examples of Tabulation
Consider, that a district is divided into two areas urban area and rural area, The Total population of the district is 271076 out of which only 46740 live in the urban area. The total male population of the district is 139699 and that of the urban area is 23083. The total unmarried population of the district is 112352 out of which 36864 are rural females. In the urban area unmarried people number 21072 out of which 12149 are males. Construct a table showing the population of the district by marital status, residence, and Gender.
Graphical Presentation of Data In Statistics
Visualization or Graphical presentation of data in statistics helps researchers visualize hidden information in a graphical/visual way. There are many types of graphical representations of the data:
- Bar Charts: Bar charts are used to represent the frequency, percentage, or magnitude of different categories or groups in rectangular form. Simple bar charts are used to compare different categories while multiple bar charts are used to compare multiple categories over time or across groups. The stacked bar charts are used to show the composition of each category.
- Pie Charts: Pie charts are used to represent the proportions of a whole as slices/sectors of a pie.
- Line Graphs: Line graphs are used to show trends over time or relationships between variables.
- Scatter plots: Scatter plots are used to visualize the relationship between two quantitative variables.
- Histogram: Histograms are similar to bar charts where the bars are adjacent, representing the frequency distribution of a continuous variable.
Textual Presentation of Data in Statistics
Textual presentation of data includes descriptive statistics. Descriptive statistics summarizes the data using numerical measures like mean, median, mode, range, and standard deviation.
Selection of the Right Method for the Presentation of Data
For the presentation of data in statistics, one should be careful in selecting the right method of data representation. The selection or choice of the right method depends on:
- Type of data: The visualization or textual presentation of data depends on the type of the data. For example, categorical data (such as gender, color, etc.) is often presented using bar charts or pie charts, while numerical data (such as age, marks, income, etc.) is better suited for histograms, line graphs, or scatter plots.
- Purpose: To show the trends of data over time, one can use a line graph. A pie chart is suitable for comparing proportions. Therefore, the selection of presentation of data depends on the purpose, use, or application of data in real life.
- Audience: The selection of different presentations of data depends on the familiarity of the audience with different types of graphs and charts. Simpler visualizations might be more effective for a general audience.
FAQS about Presentation of Data in Statistics
- What is meant by the presentation of data?
- What is the difference between tabulation, graphical presentation, and textual presentation of the data?
- What are the different parts of a table? explain in detail.
- Discuss different graphical representations.
- Discuss the selection of the right method depending on the type of data.
- What is the importance of tabulation in statistics?
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