If you have done any kind of scientific research, you must be familiar with the term quantitative research. It is a type of research, besides a type of qualitative research. It is called quantitative because the results of the research will be in the form of statistical numbers. This type is mainly used by researchers who are trying to research something by taking certain measurements. Let's see how to analyze quantitative research data.
Data analysis is a process for simplifying data in a form that is easier to interpret or understandable for those who read it. In data analysis, it means that you are trying to process data into information. Later, this information becomes a characteristic of data that is easy to understand and answers problems related to research
Data analysis is understanding the meaning of all the data that has been collected, then grouping them and summarizing them into something that is easy to understand. Until finally a general pattern of all of them was found, represented by statistical symbols, such as the mean µ (mean), the number Σ (sigma), the significance level α (alpha), the correlation coefficient ρ (rho) and others. The data analysis technique depends on the research objectives and the type of data that has been collected.
Data Analysis Stages
In analyzing the data, there were several simple steps taken, namely editing, scoring, coding, cleaning, tabulating data, descriptive analysis, and inferential analysis. Later, the results of sample analysis in statistical units are continued to predict population parameters. Meanwhile, the results of population analysis in parameter units have been completed or there is no follow-up
In the data analysis process, researchers need accurate and reliable data. So that it can be used in the research conducted. The key to quantitative data analysis (statistics) is simplification of the data. If you are going to analyze the data, then here are the steps:
- Preparation
Prepare all the data that has been collected, check the completeness or fill in the instruments in data collection.
- Tabulation
If your research uses a questionnaire / questionnaire / test, give a score (rating) according to what you have determined at the beginning of the research method. Give the code to the item that was scored earlier. Changing data, adjusting and modifying it according to the analysis technique to be applied. Usually, interval data will be converted to ordinal data (graded). Then the ordinal (interval) data is transformed into discrete data.
- Application of Data
(adjusted to the research approach)