Tools of data collection

In this tutorial, we will discuss tools of data collection in research.

✰ Data is defined as the information recorded to represent facts. Some important points about data are worth mentioning here, ⟹ Data represent facts about hypothesized variables. ⟹ Data is analyzed to determine consistency with prediction. Prediction is in the form of setting up of hypothesis. ⟹ If data and prediction are consistent, then null hypothesis is supported. ⟹ If data and prediction are inconsistent, hypothesis is not supported and is rejected.

Types of data

Types of data

1. Primary and secondary.

2. Objective and subjective.

3. Qualitative and quantitative.

1. Primary and secondary:

1. Primary and secondary:

Primary Data: ✰ Those which are collected afresh and for the first time, and thus happen to be original in character. ✰ It is based on surveys, observations, and experimentation. It is expensive and difficult to acquire. It is reliable as it has been obtained directly with a specific problem in view. Secondary Data: ✰ Primary data is collected for the purpose of the current research project, whereas secondary data is collected for some other research purpose. ✰ Those which have already been collected by someone else and which have already been passed through the statistical process. ✰ Secondary data is collected from external sources, such as TV, radio, the Internet, magazines, books and newspapers. ✰ It is an inexpensive and a quick method to obtain information. Sometimes, it is the only way when the original source is inaccessible.

2. Objective and subjective.

2. Objective and Subjective:

Objective: ✰ Objective data are independent of any single person’s opinion or the researcher. Subjective: ✰ Subjective data can be dependent upon an individual’s opinion or the researcher.

3. Qualitative and quantitative.

3. Qualitative and Quantitative.

Qualitative: ✰ Qualitative data is the description of things made without assigning numeric values. For example, facts generated from the unstructured interviews. It needs the researcher’s interpretation. Quantitative: ✰ Quantitative data entail measurements in which the numbers are used directly to represent the properties of things. It is ready for statistical analysis. A larger sample is required in quantitative data and with proper sampling design, the ability to generalize is also high.

Also read important topic for UGC NET Paper 1

⟹Collecting data:

You Should Learn Sampling methods for Better Performance.

You should practice previous year solution on this topic. GO Below ☟