Exam 13: Managing Data and Introducing Data Analysis

Soap and water is essential to the process of cleaning data.

The third stage of data analysis is the conclusions stage; the researcher draws a major or a minor conclusion from the data. In drawing conclusions, the researcher moves the interpretation along, from stating what it is that they see in the data, and what they think that means, to drawing some kind of conclusion about it.

The computer software package SPSS is useful:

For the most efficient management of a large qualitative data set:

Data management is the correct, safe and secure management of data.

A coding key is a guide, created by the researcher, to the codes used in coding the data before inputting the data into the computer.

Simple and small quantitative data sets can be analysed by simply counting the numbers and calculating simple statistics in relation to them.

The fourth and final stage in data analysis is:

Explain the role of research in the generation of theory.

When using a dedicated software package for data analysis, the researcher must code the data before inputting it into the computer.

Qualitative data analysis does not draw on statistics or statistical methods; this is because qualitative data is non-numerical data.

There are two different approaches to the analysis of data, quantitative data analysis and qualitative data analysis.

Data is 'cleaned' to ensure that it is accurate.

The fourth and final stage of data analysis is the theorisation stage. The researcher theorises their data by linking it with the theory, laid out the in the literature review carried out for the research.

Why is data management important?

Data management is:

CAQDAS stands for computer assisted qualitative data analysis software.

Atlas ti is a:

Computerised data analysis software packages are particularly helpful with:

Some research projects generate quantitative data, some generate qualitative data and some generate a mixture of both, this is known as mixed methods research.