Data Analysis Is – Definition, Techniques, Methods, and Examples.
Data Analysis Is – Definition, Techniques, Methods, and Examples.

Data Analysis Is – Definition, Techniques, Methods, and Examples.

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Data Analysis Is – the process or effort to transform data into new information so that the characteristics of the data become easier to understand and useful for solving problems.

This time, will provide a lesson on Data Analysis, where this lesson will be explained clearly, based on Understanding, Techniques, Methods, and Examples.

Definition of Data Analysis is

Understanding data analysis is a process or effort to transform data into new information so that the characteristics of the data become easier to understand and useful for solving problems, especially those related to research.

Data Analysis Is

Data analysis can also be defined as activities carried out to transform research data into new information that can be used in conclusions.

In general, the purpose of data analysis is to explain the data in a way that is easier to understand and then draw conclusions. Conclusions from data analysis are obtained from samples, which are usually carried out on a test basis.

Data analysis technique

Examples of Data Analysis Techniques

When writing data collection techniques, we must place a scientific paper in chapter 3, whether it is a thesis, scientific paper, thesis, or research report. This is due to reasons with the research method used.

Examples of Quantitative Research Data Analysis Techniques

When writing a number of steps, quantitative data analysis methods, which in this case cannot be separated from a number of methods that can be used, for example when determining the research sample according to the existing sections.

In writing after the method of collecting a series of data, this also applies to each model of scientific work, for example, in the preparation of abstracts and research proposals.

When doing this, it must be based on certain procedures and steps. Here are some of the steps:

  • The trial stage, namely testing the quality data process, both in terms of reliability and reliability of the material uniting tool.
  • The data description stage is the process of compiling the material and presenting it in the form of tables or diagrams with different sizes of central tendency and variance measures. The aim is to understand the characteristics of the sample data from this study.
  • The hypothesis testing stage is the process of checking the proposal, whether it can be accepted or rejected, whether it makes sense or not. Based on this step, conclusions or decisions will be made later.
  • Collection of materials, the initial stage of the activities of the analyst is the collection of materials for analysis.
  • The editing phase, namely the process of checking clarity and completeness related to filling out data collection tools.
  • The coding stage, which is the process of identifying and classifying all operators in the data collection tool, based on the variables being studied.

Data analysis method

Research methods

Method as an effort to find, develop, and test true knowledge, scientific work (a research) can achieve what is expected accurately and purposefully using the scientific method.

While the research method is a strategy that is usually carried out in the collection and analysis needed to answer the task.

This research is quantitative research with an experimental approach. Experimental research is research that is carried out intentionally to provoke an event or situation.
be a way of searching.

The causal relationship between two factors is intentional and caused by the researcher by eliminating or reducing the exclusion of other factors that can interfere.

Analytical methods differ from analyst techniques, although they sound similar. This method is more related to the more general approach and contains the methods of this approach. The research results are broadly divided into 2 parts, namely qualitative and quantitative methods.

While in the quantitative method itself there are various types of analytical methods, such as correlation, regression, comparative, descriptive and the like.

Analyst Quantitative method is a source processing approach using statistical or mathematical methods collected from secondary data. The advantage of this method is a more measurable and comprehensive conclusion.

Quantitative Data Analysis Method Consists Of Several Techniques Such As:

  • Descriptive analysis, we describe the results of the collected data, such as using statistical indicators such as mean, median, mode and standard deviation.
  • Comparative analysis, we compare one real event with another phenomenon, or we compare the same occurrence in different groups of subjects.
  • Correlation analysis, we see the relationship between one event with another phenomenon, which is not proven theoretically.
  • Causality analysis, we again question the causality between several phenomena, which theoretically should influence each other.

Quantitative data analysis methods are more widely used in the fields of exact sciences, economics, engineering, and medicine. Although today many social studies are part of the application and influence of this science. Therefore, quantitative approaches are often used in methodological approaches.

The qualitative data analysis method is a method of processing in-depth observation data, interviews, and literature data. The advantage of this method lies in the depth of the research trials.

Qualitative data analysis methods are widely used in the fields of social science, law, sociology, and politics. Although not entirely in the social field, qualitative methods must be used.

How can one investigate the philosophical aspects of some articles in the field of law, if without in-depth study. Of course, for such a question a qualitative method is needed. Qualitative analysis methods consist of various forms of analytical methods, such as:

  • This method of analysis must Regulate quality materials to be more accurate, why is this necessary? because, as we know, in qualitative research there is no such thing as a specific measure, not to mention the use of standard scales, as in quantitative research.
  • This data analysis method requires material coding which must be done because the size of the data is mainly in verbal and not numerical form, so that researchers can code to combine several ways, which have the same meaning.
  • Data analysis methods Connect one concept with another concept that can influence each other, the size of the relationship or influence cannot be described with numbers.
  • This analyst legitimizes the existing results by comparing other concepts which, in our opinion, contradict the conclusion.

Example of Data Analysis

For example, the qualitative research, “The practice of micro-artists on Instagram.” Researchers interviewed several rising artists. Hypothesis developed.

For example, is that celebrities see Instagram (IG) followers as viewers who are always waiting for their presence in the latest publications, for example, artists that their fans expect during a show.

However, one of the informants turned out to be a follower as a potential consumer who would buy a product that agreed to it. This case was excluded by the researcher, because he did not confirm the hypothesis developed based on other data.

Or, researchers are looking for new data to see if celebrities tend to perceive followers as audiences or consumers.

In the transcript, several informants said that the fans are very important, because without them, they are nothing, no one likes musicians without audience or artists without fans. We found the transcript as follows:

  • Fans are very important because without them we are nothing. As an artist without an audience.
  • Followers are essential to engagement, those who judge how we publish, how viewers rate their favorite artists
  • Fans are important because this is our selling point. Without this, we cannot earn.

The results of previous studies (obtained from literature studies) show that celebrities see their fans as followers, so that online images of celebrities must always be properly guarded.

That’s the friend we can convey this subject matter. Hopefully with what we have conveyed in this article, it can provide understanding and be useful for all of you. AMEN.

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