In the last 2 articles we have discussed how to gather the data and what techniques should be used in the process of data collecting. Once you gather the data you need to analyze the whole data meticulously. Data interpretation is one of the major and essential stages after the data-collecting process. Thus, in this article, we are going to discuss the data analysis and interpretation in detail. Let’s discuss this.
What is the Need for Data Interpretation?
Data analysis and interpretation are critical because it helps you to portray the present findings suitably. From the data analysis process, you can simplify the whole data into a specific manner and your result would be much clear by using the way of interpretation.
What is the Type of Data Analysis?
There are two types of data analysis qualitative and quantitative. We can analyze the data from questionnaires, interviews, and observation studies that we have already discussed in the previous article.
Qualitative Data Analysis
The qualitative data can be analyzed using theoretical frameworks such as grounded theory, activity theory, thematic theory, or distributed cognition style. In this analysis quality matters rather than quantity. The nature of elements, themes, patterns, and stories is represented by this method. It is difficult to major quantitative data such as a number by using this method. For example, counting the number of words.
Qualitative analysis can be done by using various ways.
- Experience of the user
- result of the task
- An evolution study of the document
Quantitative Data Analysis
It is exactly the opposite of qualitative analysis because it analyses the numerical content such as size, magnitude, and amount.
Quantitative analysis can be done by using three ways.
- Graphical representation
But while using this method you should care about the numbers while putting it.
Tools to Support the Data Analysis Process
In the process of data analysis, some technical tools are really helpful and effective to present and analyze the data.
- Statistical packages like SPSS
- Theme base or text-based tools
In the process of interaction design, data collection is critical to successful design. Data analysis can be done depending on the data gathering that was already done. You can choose various techniques in the process of Data collection by thinking twice. From this article become to know that after the data gathering, there is a crucial step to analyze and interpret the data effectively and appropriately.
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