Introduction
Data handling is a concept in statistics used to collect raw data, then organise and present the processed data that can be analysed further to take important decisions. So, generally the raw data is converted into meaningful information after going through the following three steps:
-
Collection
The raw data collected from the sources like newspapers, questionnaires etc.
- Organization
The collected data is saved into tables using tally marks.
- Presentation
The organised data from tables are presented into graphs, charts or histograms.
A school teacher handles students' attendance register to store daily attendance of students is a real life example of data handling. In this case, the teacher collects raw data from the students and organises into an attendance table which is already printed in the register. The organised data from the register tables can further be used to analyse such as how many students are absent frequently or on a specific day of the week. This analysis of absentees would help the head of the school to take decisions on how to normalise the full attendance of school.
The other scenarios where data handling can be observed are in tax collection from people, weather forecasts, agriculture to predict harvesting and crop health monitoring.
Data Handling lessons
Learn Collection, Organization And Frequency Distribution Of Data
- Introduction to data and information
- What is data in statistics?
- Collection of data
- Organization of data
- What is frequency in statistics?
- Tally marks in frequency distribution
- Types of frequency distribution
Data Handling, Presentation and Interpretation
- Presentation of data
- Pictograph
- Bar graph (Column graph)
- Double bar graph
- Histogram
- Pie Graph or Pie Chart
- Line graph
