# Analysis of Data : Quite a straight job

Statistical analysis is an integral part of PhD research. In your research journey, by the time you reach the stage of data analysis, you have already crossed the most difficult and challenging stages. Within the chapterisation scheme of your PhD thesis, in the Research Methodology chapter itself there is so much to do, from defining of the research problem, developing a sampling plan, conceptualisation and designing of the structure are fundamental, as well as puzzling. In comparison to all the above, isn’t data analysis a fairly straightforward task?

The job of data analysis comprises three main stages, respectively

1. Data cleaning, sorting and preparation

2. Descriptive analysis of data

3. Hypotheses testing and models

1. Data Cleaning, sorting and Preparation: At this stage the verification of the data is done for accuracy, cleaning out the data that is redundant and not of use, feeding the data in the computer in an organised manner, data transformation and creating a database that integrates the different measures together into one.

1. Descriptive analysis of data: This is the mandatory stage of any study, like the previous one. Whatever are the objectives and hypotheses of the study, descriptive statistics is done to bring out the fundamental aspects of the study. Thus, it becomes the pre requisite for almost all research that call for a quantitative analysis of data. By doing this, you can bring out the graphical analysis, which is a comprehensive description of the data. In the preliminary stage, descriptive statistics can be voluminous and may appear confusing, but the researcher has to tactfully select and organise them into summary tables and graphs, bringing out only the most relevant information and leaving out the unnecessary and repetitive component of the analysis.

1. Hypotheses testing and models: This is the third stage of data analysis which is what is the crux of the research as well and this is the investigating stage. The investigation is done, for questions, models or the hypotheses of the study. The scope of this stage is much more than the previous stage of descriptive statistics because it determines the true essence of the research. In descriptive statistics, we only bring out the facts that are existing in our collected data. We don’t go beyond that. While, in the case of hypotheses testing and models, on the basis of the collected data, we try to make judgements about the general population. This stage can also be referred to as inferential statistics as it helps to infer from the sample about what the population thinks or believes in.

Make sure, when you present your analysis, you don’t overload the reader with lots of information. If you so want and find the need, you may attach the extensive analysis in the appendices and present only the critical analysis summary in the report, which is connected to your objectives and hypotheses of the study. A comprehensive but complete analysis is important and significant to a research and a good statistical analysis decides the quality of the research.