Data handling

Data Handling Definition

The data handling definition is the research process that is used to collect, record, organise and analyse data. The purpose of these steps is to collect empirical evidence to identify if the research findings support/disprove existing theories and if it rejects or accepts the null/alternative hypothesis.

There are many aspects of data handling that researchers need to keep in mind:

• data collection
• the type of data handling
• ethical duties
• how data handling and analysis will be done

Steps of Data Handling

There are several steps of data handling that researchers need to follow in a somewhat specific order. Each of the steps of data handling needs to be completed to a high standard as this can have a knock-on effect on the quality of the research and its findings.

If the stages are not done to these high standards then this can reduce the ethical standards of the research, and the reliability and validity of the results

The data handling cycle is the steps of data handling, these are:

1. plan the research
2. collect the data
3. analyse the data
4. report findings

Data collection

The first step of data collection is to plan the research that will be carried out. This includes designing the research such as the materials, type of participants, procedure and data analysis methods that the research will use.

The following step of data handling is data collection. This is the method that the researcher uses to collect data that will be later analysed.

Two main types of data are collected in psychology research; primary and secondary data. The type of data collected is determined by the type of research method that the researcher uses in the study.

An important thing for researchers to keep in mind during the data collection stage is that the data needs to be stored securely. The participant's personal details should not be revealed to anyone. The purpose of this is to ensure that the ethical responsibilities that researchers have towards participants are not tarnished.

The Types of Data Handling

The next step of data handling is to analyse data. The type of data handling affects how it is analysed later. There are two types of data handling; qualitative and quantitative data.

The type of data obtained depends on the research method used. Some examples of research methods that collect qualitative or quantitative data are listed below.

Qualitative data is usually analysed using procedures called thematic analysis or content analysis.

Quantitative data is usually presented in tables, graphs and statistics. Illustrative quantitative data handling examples used in psychology research include:

• frequency tables
• bar charts
• histograms
• scatter diagrams

Qualitative data is usually presented in written reports documenting summaries.

Data Handling Examples

Some data handling examples are:

• Normal distributions: This is a data handling example that involves measuring how the values of the data fall around the mean score. Understanding if data is normally distributed is crucial because it influences what statistical tests can be later used. Ideally, researchers want to collect normally distributed data.

• Descriptive statistics: Descriptive statistics are statistics that describe the variables that are being investigated in the research. Types of descriptive statistics that are commonly measured in psychology research are:
  • Mean: this is the most common descriptive statistic that is measured. This is calculated by adding all the values together and dividing it by the number of data points there are in the analysis.
  • Mode: this is the most common number that is identified in the data
  • Median: this is measured by putting the data in numerical order and identifying the middle-value
  • Range: this is a measure of dispersion which means that it measures the spread of the data. This can be identified by misusing the smallest number from the largest
• Computation: Researchers often express data in various forms such as standard form, decimal form, fractions and percentages. On some occasions, researchers may convert one numerical form to another. During working out and reporting computations, researchers need to follow psychological guidelines, for instance, significant figures need to be reported to two significant figures.

The final step of data handling is to report the results using data analysis. In this stage, researchers write a scientific report that describes the details of the research. When reporting the results, researchers need to state whether the findings support/ disprove the hypotheses proposed at the start of the experiment.