subject: Auditing And Implementation Steps To Secondary Research And Data Analysis [print this page] In carrying out any form of research, a researcher is presented with two kinds of data to work with. Qualitative data deals with qualities that cannot be measured and are not tangible e.g. character traits like age, sex and ethnicity. Quantitative data deals with the quantity i.e. amount like 100 kgs, 50 cm, etc. The process undertaken to collect, compile and organize the collected data is referred to as data analysis. In analyzing the already collected and previous data, the researcher has to come up with a summary of the data. This is referred to as secondary research. The latter-going to the field is primary research. Data analysis and secondary research are the backbone of any research. When the two are used together, they enhance a successive research.
Any time of research starts with first coming up with a topic that you wish to research on. Since no one will believe your research without a candid report, you need to start by collecting data. This can either be done using the primary or secondary way of data collection. Primary data collection requires that you go to the field and collect raw data. This will be used later on in interpreting the research findings. The other way would be to use secondary data collection. This is a collection of already done research. It can be gotten from newspaper reviews, annual reports or any other already published journal. Data analysis is then done to prove the hypothesis. Since the research is meant to prove a point, the collected data is used to falsify or accept the hypothesis.
Data analysis is represented using empirical graphs and chats to show the research findings. The most popular and reliable way of representing these findings is by the use of the SPSS program. It gives detailed and summarized representations of all quantitative findings. Qualitative data analysis is used in making inferences about the research done. This is because every respondent gives a different answer to the questions being asked.
The final stage of compiling your research findings is done through the implementation and audit support. Data analysis implementation gives the conclusion and inferences of the research findings. Implementation and audit support gives the base of the research and helps in making recommendations and the way forward regarding the problem at hand. The research findings are then published in the audit and the cause of action adopted. The importance of an audit is that it gives credibility as well as adding value to the research. If its in a company, the research and analysis of data is best done by an outside body. The audit will then give confidence to both the employees and the share holders of the company. Implementation and audit support in data analysis is very important to every other company/organizations and companies. If people have doubts about any activity that is being carried out, the audit is used to clear up these claims. Its very important that after carrying out a research, that you produce an audit. It verifies details, prevents the occurrence or errors, makes it easy to do evaluation and also make future predictions.
