Understanding research and data analysis enables one to learn how to do data analysis in research. Data analysis is the process of manipulating data systematically to yield useful information. Research, on the other hand, entails conducting a study using defined methods to understand concepts or facts. The following steps help one to conduct reliable data analysis, especially when you do not want to buy research paper.
- Develop a hypothesis and research objectives for your study
- Identify clear, concise and measurable research questions
- Decide how you are going to conduct your study considering factors such as time and units involved
- Collect your data; either qualitative, quantitative or both
- Analyze your data using the most appropriate tools and methods such as SPSS, STATA e.t.c
- Interpret and visualize the results, and conclude with the initial research questions in mind
Types of Data Analysis in Research
Businesses and individuals adopt different types of data analysis in research, depending on the purpose of the study. The major ones are as discussed below:
Statistical Data Analysis
It adopts descriptive data analysis, which answers “why” by describing the various aspects of the data at hand. These may include the mean, deviation, frequency, and so forth. It also involves inferential data analysis that works on data sets, with the conclusion drawn depending on the sample used.
Predictive Data Analysis
This type of data analysis uses past data to establish what is likely to happen in the future.
Text Analysis
It is also known as data mining and it assists in identifying patterns from large data sets. It involves the use of business intelligence tools.
Diagnostic Data Analysis
This type of data analysis uses data to establish the cause of certain occurrences.
Prescriptive Data Analysis
It combines various data analysis methods to facilitate coming up with the most ideal decisions.
Data Analysis in Qualitative Research
Data analysis in qualitative research entails using qualitative data, which is non-numerical as opposed to quantitative data. Such data comes from interviews, focus groups, records, observations, and case studies. If your study entails qualitative research, you must conduct qualitative data analysis before arriving at conclusions. We can help you with qualitative data analysis using any tool. One can either use the deductive or inductive approach in analyzing such data. The former involves using questions that the researcher seeks to answer for conclusive information. On the other hand, the later has no pre-determined structure. Despite being more time-consuming, it is a thorough approach compared to the deductive one.
Data Analysis in Quantitative Research
Data analysis in quantitative research entails using quantitative data, which assumes numerical values. However, for this data to make sense, the researcher must analyze and interpret it, then draw the relevant conclusions. Methods of quantitative data analysis include cross-tabulation, trend analysis, Gap analysis, SWOT analysis, and Turf analysis among others. Depending on the data at hand, you must first assign logical scales before analyzing. You can then link it to descriptive statistics such as mean, frequency, mode, median, and others. For help with quantitative data analysis, we are your go-to professionals.
How to Analyze Data in Research
As you conduct any study, you must first familiarize yourself with how to analyze data in research. Some researchers may use only qualitative, quantitative, or categorical data. Others may use a blend of all, which complicates the process of data analysis. If you get to this point, you can get professional data analysis help from us. We will help you to collect, classify, analyze, interpret, and visualize the analyzed results.