Analyzing And Organizing A Data Essay

Quantitative research is done to find the accurate facts by evaluating the problems like opinion, behaviour by using numerical data. This research is based on theories, hypothesis, collecting, analysing the data to make the research accurate.

Collects numerical data that can be quantified. Research with numbers. Focus on measuring, collecting and drawing relationships through statistical analysis and experimentation.

The researcher must set a clear hypothesis, showing the relationship between independent and dependent variables. In quantitative research tools are used to collect numerical data. The information can be gathered using questionnaires or some type of equipment. Quantitative data is efficient at testing a hypothesis, but can miss contextual detail. In quantitative research, the researcher is often objectively separated from the subject matter. One of the ways quantitative research is different from qualitative research is that quantitative research requires extraction of large amounts of statistical data. Qualitative research is focused in on personal viewpoints and opinions of a smaller number of subjects (typically). Qualitative research can take more time than quantitative research (McCusker & Gunaydin,

It is essentially research based on numerical data, including collection and analysis. For example, asking questions with yes or no answers to be able to gather a number of statistics for the search. There are a number of methods used for data collection with the quantitative approach to research, these include, questionnaires, surveys, experiments observation schedules and measuring tools. With quantitative research there are two types of sampling methods, probability and non-probability. Probability is the likelihood of the population of the research will be included into the final sample, when every unit has more than zero chance of being selected.

Quantitative research methods are objective as it uses measurements and analysis of statistical data to answer the study question. The researchers’ opinions do not affect the outcome of the study, ensuring that the study is unbiased. Another advantage is quantitative research uses numbers and statistics which is understood universally (Houser,2008).

A quantitative study has objective stances, logic, and numbers focusing on unchanging data and details (Babbie, E.R., 2010). The aim of quantitative research is to classify features, count the features, and construct statistical models to explain what was observed (McNabb, D.E., 2008). It has eight characteristics:

In defining quantitative research the term can be dichotomized. Firstly, research refers to creative, systematic work with the intention to increase the knowledge of man and thereby devise new applications (OECD, 2002). In addition Gray (1997) stated that research should improve performance and that the results should be

The quality of the study will depend on how carefully the researchers entered the data into software programs and verified its correctness. Verification can occur visually or by entering the data twice. Cleaning the data involves the identification of possible outliers by looking at the frequency distribution of the data in a graphical format, such as a scatterplot, followed by testing suspected outliers statistically. Visual inspection of the data should also reveal the presence of wild codes, which are values that make no sense. The data in its final form must therefore be verified for correctness and cleaned of outliers and wild codes.

Coding the data is a systematic way in which data is condensed into smaller easily analyzed units (Lockyer, 2004). By coding the surveys received by BIMs it enables the company to analyze and interpret the data to draw an informed conclusion. The coding enables the research team to identify mistakes, and outliers, which improves the data’s validity (Lockyer, 2004). To code BIMS’ data, the surveys must be numbered, and all corresponding data must be manually entered into Microsoft Excel, which increases the cost, time, and risk. The data is at risk of being entered incorrectly. Next, the raw data must be cleaned to ensure validity, relevancy, and accuracy. After the data was imported into Excel, the data must be reviewed for mistakes. One error that was identified was that a six was entered into Excel even though a five was observed. By coding and cleaning the data, the researcher will proactively identify errors or outliers while enabling a computer to complete statistical analysis and

Quantitative Research- a research based on experimental data, a survey that proves the actuality of the theory.

Quantitative research involves collecting data, which can be expressed numerically. The design is well structured with pre-determined outcomes. It frequently involves testing a hypothesis, which then can be analysed from the data deductively using statistical methods. Using numerical data is easier to analysis mathematical, so larger sample sizes can be utilised compared to qualitative research, therefore giving a better representative of the population; along with simplifying the process of making a generalisation. Another advantage is that studies can easily compare to similar findings (Kruger, 2003). The disadvantages are the results are limited and might not provide a proper understanding of the topic. Also, statistics and leading questions can be used to give a false representation of the data when summarising.

To conduct quantitative research, the first step is defining the problem, identifying the objectives and goals, and establishing research questions or hypothesis. It is followed by data collection and analysis with the application of various numerical and statistical approaches. Quantitative research is more factual in terms that we get concrete data with evidence to prove the results of our research.

According to Naoum (2013) quantitative research is “enquiry into a social or human problem based on testing a hypothesis or a theory composed of variables, measured with numbers and analysed with statistical procedures in order to determine whether the hypothesis or the theory hold true”(Naoum 2013,p.39). The approach is objective in nature and not abstract. It is associated with tangible, measurable and numerical data that may be analysed to produce conclusive and generalized answer. It is mostly applied when researchers want to prove or disprove a set of hypothesis and when enquiring realities about the theory, query or attributes (Saunders et al. 2012) by using primary collected data (Fellows 2003). Quantitative research is more structured and well defined that allow the researcher to do extensive planning before the actual research starts. In most cases the actual work tends to be consistent with the predetermined research question and conceptual framework (Bell 2014). This allows for easy forecast of ethical challenge and a plan on how to handle the challenges can be put in place before the actual work begins. It may be carried out by survey, structured interview or observation (Saunders et al. 2012).

Quantitative research design is an excellent way of finalizing results and proving or disproving a hypothesis. The structure has not changed for centuries, so is standard across many scientific fields and disciplines. After statistical analysis of the results, a comprehensive answer is reached, and the results can be legitimately discussed and published. Quantitative experiments

Quantitative research methods are utilized to study the natural phenomena. So, it includes survey methods, formal methods, and numerical methods.