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Data Analysis Method Used For Characteristics Of Physical Items

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The data analysis method is extremely important as it turns the dataset into a scientific story. It also interprets data to extract conclusions. To put it in another way, data analysis is the process of reducing large chunks of data into smaller but meaningful fragments. Whatever the purpose of your research will be, steps necessary for conducting data analysis remain more and less similar. It always starts from the organisation of data, passes through summarisation, and ends with categorisation. It explores the relationship between different variables. Also, it helps create a final meaningful story describing an event, problem, or solution to the problem under study. This article will discuss a similar data analysis method (content analysis) for the analysis of characteristics of physical items.

Characteristics of physical items by using the data analysis method can be done by both qualitative as well as quantitative content analysis. The quantitative content analysis focuses on counting and measuring physical quantities, while the qualitative content analysis focuses on interpreting and understanding ideas. In both types of content analysis, coding and categorisation are essential to analyse data. Content analysis is a useful method to study the characteristics of physical items as it is a standard procedure to quantify the occurrence of certain phrases, words, concepts, and subjects in collected data.

What Is Content Analysis?

Content analysis is a research method used to identify the characteristic of physical items in research. Its sole purpose is to identify the patterns in recorded information. To conduct content data analysis method, one must systematically collect data from the textual information that may be in written, visual as well as oral forms. The sources from which you can scrap data for content analysis include books, newspapers, speeches, interviews, web content, social media posts, photographs, and documentaries. However, hiring a good dissertation writing service UK is also a source to get content analysis.

How Is Content Analysis Used For Analysing Characteristics Of Physical Items?

The content analysis follows five simple steps. These steps aim to analyse physical data. This data analysis step starts with the identification and collection of data and ends by analysing the final results. The following section will briefly describe the five important steps of content analysis for analysing the characteristic of physical data.

Research Or Collect The Data That Describes The Characteristics Of Physical Items Involved In Your Study:

The first step in this data analysis method includes the selection of texts that you can analyse to explore the characteristics of the physical item or variables involved in a study. At this step, you need to select the medium, criteria for inclusion, and parameters such as date range and location. Generally, while analysing content at this step, any of the two situations may arise 1) too small availability of data that focuses your variables and 2) too large data availability. In the former case, you can select all data for analysis (no need to do sampling). In the latter case, you cannot consider all the information in the selected data analysis method; thus, sampling is the most appropriate way to work with a large dataset in content analysis.

Define The Units And Themes For Categorising:

After that, you need to decide at which level you will analyse the content of the chosen texts. Unit of meaning and set of categories are important to be done at this stage of content analysis. In the unit of meanings, you must measure the frequency of certain events, words, phrases and physical characteristics of items involved in a study. On the same ground, a set of categories describe the codes you will use. Coding can be done by making two types of categories, the first is objective characteristics, and the second is conceptual categorisation.

Set The Rules For Coding:

Once you have done defining the unit of meaning or themes of categorisation, the next step must be to organise the unit of meaning into the previously defined categories. In the case of more conceptual categories, the importance of defining the rules for the inclusion and exclusion of data in codes increases many folds. Concurrently, setting the rules for coding also becomes very important when more than one researcher is involved in a study.

Code The Text According To The Pre-Defined Rules:

This stage of the content analysis is all about reviewing the text and recording the relevant data into the pre-defined categories. The manual process of recording data under the categories formed at the previous stages of the content analysis is a bit lengthy process. Thus, you can speed up the process by using an array of computer programs such as Diction and QSR NVivo.

Analyse Results Based On Coding And Themes To Draw The Conclusion:

Following steps 1-4, you will be very closer to your destination. The only task left behind to be completed at this stage is to find patterns and draw conclusions based on the identified patterns. To transform your qualitative data into the quantitative one, a researcher can also use the statistical data analysis method to find correlation as well as regression. It will help you to best characterise the physical items to solve the scientific queries under observation in textual form by using statistical ways such as standard deviation or mean error bars.

Merits And Demerits Of Content Analysis:

On one side of the picture, the use of content analysis as a data analysis method for analysing the characteristics of physical items of research has a number of advantages. Unobtrusive data collection, transparency, and high flexibility are among some distinctive features of content analysis. However, whether you should select this data analysis method for your academic must be decided after reviewing its demerits as well.

The reductive, subjective and time-intensive nature of the content analysis limits its scope in the analysis of characteristics of physical items. Thus, making a wise decision about the section of the content analysis in your research must be based on the merits and demerits of this data analysis method. There are many firms in the UK that are offering services to buy dissertation when students are stuck in the content analysis part. You can get help from a reliable firm if you face any issues.

Final Thoughts:

Quantifying the characteristics of physical item is an overwhelming process unless and until you select the right data analysis method for it. The content analysis is the most appropriate method to study characteristics as it helps in understanding the content by taking semantic relationships and meaning into account to identify the patterns among physical items. I hope the brief introduction, steps, merits and demerits of content analysis will be useful for you to analyse the characteristics of physical items in research.

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