Data Analysis in Research/Dissertation Papers
- Author Carl Andrews
- Published March 31, 2016
- Word count 451
Purpose of Data Analysis
Data analysis forms an integral section of a research/dissertation paper. It encompasses a process aimed at generating answers to respective research questions by examining and interpreting data. In this, data analysis is important for numerous reasons as explained below:
a) It is essential in generating insights on pertinent issues raised in the research. Through data analysis, it is possible to unravel questions raised by the research questions that in turn produce new knowledge about the subject under study.
b) Data analysis is critical in refining the research process. Data analysis helps identify areas of the research process that require redesigning, further planning, and developing better research objectives.
c) Data analysis also plays an important role in determining the most appropriate sources of data for a particular study or type of studies.
Methods of Data Analysis
Data analysis can primarily divided into two main categories.
a) Descriptive analysis
b) Inferential analysis
Descriptive analysis entails a description of data collected from a certain sample. It deals with data that seeks to describe the characteristics of a particular sample. In this, descriptive statistics are key in data analysis. Such statistics include frequency distribution, measure of variability, central tendency, and bivariate descriptive statistics that include correlation and contingency tables.
Inferential analysis encompasses using statistical tests to find out possible relationships between research variables, or to support hypotheses statistically. Per se, inferential statistics involve numerical values that can be utilized by a researcher to draw conclusions on populations in line with the population’s characteristics obtained from a sample. Inferential analysis is mainly used in such scenarios as t-test, chi-square, and analysis of variance.
Steps in Data Analysis
Data analysis is done in numerous steps. Executing each step appropriately is essential in enhancing accuracy of the results to be obtained. These steps encompass:
a) Initial preparation: This step entails conducting an analytical study to evaluate the study objectives and the questions that need answering. This further looks at how the answers obtained from data analysis will contribute to the existing body of knowledge, best sources data, the most appropriate analytical techniques, and the target audience.
b) Determining appropriate data: This involves evaluating the available data to ensure that it is right for the intended type of analysis. As well, an analysis on the consistency of data sources should be done in cases where different data sources are being utilized.
c) Determining suitable methods and tools: This intends to determine whether the analytical approach of choice is appropriate in investigating the data being utilized in the research.
d) Results interpretation: This is a key step in data analysis and entails deriving conclusions from the data collected in respect to the research questions.
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