Chapter 3 – Data Handling

The process of collecting data is vital in creating valuable information. To collect data, you need to know what is the purpose of collecting it. The clarity in the purpose of collecting data will lead us to appropriate data, which in turn will give us desired information. 

The collection of data is the primary step in Data Handling. 

Let us take an example to understand the significance of data collection. Suppose you want to know the average temperature of your city for a week and you go online and find the temperatures of each day of the previous week. After collecting the data when you sit down to calculate your city’s average temperature, you realise the data does not match, and you notice that the temperature you collected is that of your neighbouring city. Thus the entire data you collected is not useful for the decision you wanted to make, i.e. to know your city’s temperature. 

Therefore, it is an essential step to know beforehand the goal for which the data is being collected.

The organisation of data is the most important step in handling data. Data handling is collecting, tabulating and, lastly, organising this data. The organisation of data allows us to make the data useful to us to make any decision and understand the information. 

Why is it important to organise data? Because the organisation of data helps us to interpret and understand data. Proper organisation of data allows us to make easy decisions, draw meaningful conclusions and re-use the data collected by us. 

You may have seen your report card is always in tabular form, and so is the menu at your favourite restaurant; this is an example of the organisation of data. In fact, most of the data we come across is found in tabular form.

The representative value of data shows us the central tendency of a group of data or observations. Different forms of data require different forms of representative or central value to explain or describe it.

• Arithmetic Mean
  Arithmetic mean is one of the most common forms of representative value of a group of data.
  The average arithmetic mean can be defined as follows.
  Arithmetic mean = Sum of observations number of observations
• Range
  When we subtract the lowest observation from the highest observation of data, we get as a result Range of the data.
  Range gives us an idea of the spread of information.
• Median
  When any data is arranged in an increasing or decreasing order, the value that lies in the middle of the data is the median.
  Thus in any given situation, the median of a data will have half of the data above it and half of the data below it.

In the previous chapters, we have seen that a bar graph represents data, using bars. The length of these bars depends on the frequency and scale we have chosen. Bar graphs serve the purpose of comparing the collected data effectively.

Data Handling is thus a process of assimilation and organisation of data. In this chapter, we learnt that data is the most important component of data handling and that different data types of data require different representative values.