Qualitative data is usually subjective, rich, and contains in-depth information about the subject under study. Categorical data is another name for the qualitative data as mostly we analyse this data by grouping them into different categories. Qualitative data analysis is useful in determining traits, characteristics and frequency. One-to-one interviews, focus groups, case studies, observations, and longitudinal studies are some exploratory qualitative data collection methods. Usually, we can analyse this type of data by following several simple steps. Moreover, the sought after data analysis method for qualitative analysis includes narrative analysis, framework analysis, grounded theory, content analysis and narrative analysis. Thus, this article will be a complete guide for those who are planning to use the qualitative data analysis process for their undergraduate and graduate research. <\/p>\n\n\n\n
The analysis of qualitative data is the process of searching and organising observation notes, recorded interviews, and other forms of textual information for developing a detailed understanding of a process based on opinions, suggestions and experiences. The process of analysing the qualitative data is quite different from quantitative data analysis. The former includes theming, coding, and categorising the data.<\/p>\n\n\n\n
The latter includes the selection and application of statistical tools. The analysis process of the qualitative data starts from the collection of a large number of responses (by primary or secondary methods) and reducing it by using theming and coding practices. It also includes the identification of meaningful patterns, extraction of useful information from the data and presentation of findings as evidence of the main claim of the research. Due to its difficulty, many students prefer to get help from masters dissertation writers<\/a>.<\/p>\n\n\n\n Regardless of the method of data collection, to analyse the qualitative data, you can follow the following simple steps:<\/p>\n\n\n\n The qualitative research process starts with the selection of topics and the collection of data. Once an individual has collected all the necessary information for conducting qualitative analysis, the next step must be to arrange the data. Proper arrangement of data in this analysis is necessary as often qualitative data seems highly unstructured and does not makes sense at a single glance. Thus, for arranging the data, you can export data into an excel spreadsheet or can also manually type data.<\/p>\n\n\n\n After arranging the data, a researcher must organise the data immediately. In large data sets, a simple arrangement of data is sometimes not sufficient; thus, a proper data organisation process is important to sort data in a more orderly manner. A simple but most practical way of organising the data is to review the research objectives and then follow the sequence of the things asked in the research questions. <\/p>\n\n\n\n The most critical step in the qualitative data analysis on which the success of the whole analysis depends is coding. Coding aims to reduce a large amount of data by sorting, categorising, and assigning properties to the data collected for observing patterns. <\/p>\n\n\n\n Reliability and validity of the research are important ethical considerations for conducting research. Thus, in qualitative data analysis, data validation is not the only step. Rather, the researcher should keep the validation of data in mind throughout the research. Moreover, for data validation, the researcher must focus on two things. The first is whether the method or design he selected for a study is accurate or not. Similarly, the second is reliability which aims to monitor the extent of a method to produce accurate data. <\/p>\n\n\n\n Last but not least is the technique to conclude the data, which simply means the systematical arrangement of data so the audience can easily get your point. Thus, the concluding session must clearly state the method, relationship between variables and study limitations. <\/p>\n\n\n\n Qualitative data analysis involves the collection, organisation, and interpretation of non-statistical data. It involves the textual form of data, so we cannot run statistical software like SPSS, Python or any other to observe patterns among the raw data. Thus, the following is a brief description of five methods that helps in analysing all type of qualitative data, irrespective of the discipline.<\/p>\n\n\n\n It is a method that researchers use to find the existence of words, themes and ideas in the responses collected from interviews, case studies, focus groups and many more. Thus, content analysis is useful to quantify and analyse the relationship, meaning, and presence of certain words or concepts. Moreover, it further has two types, namely, conceptual analysis and relational analysis. The conceptual analysis measures the frequency and existence of certain words. The relational analysis further increases the understanding of a phenomenon by exploring relationships between the identified words and concepts in the given data. <\/p>\n\n\n\n Narrative analysis is the process of reformulation of participants\u2019 stories by considering the experiences of each participant. In other words, it is the double layered process that, at first, the participants interpret their life experiences, while at second, the researcher reconsiders the construction of narration. Thus, narrative analysis is a process of revision of data collected by primary means. If you are facing any issue in narrative analysis especially in your dissertation, you can hire our dissertation writing services UK<\/a>.<\/p>\n\n\n\n It is the form of thematic data analysis and an advanced form of qualitative data analysis. It consists of several steps like familiarisation, identification of themes, selection of thematic framework, mapping, coding, data interpretation and presentation of findings.<\/p>\n\n\n\n It is the qualitative data analysis method that primarily focuses on the construction of theory. Later, the researcher uses this theory to systematically arrange and organise the information. It is common to unveil social relationships and behaviour in social sciences. <\/p>\n\n\n\n It is the method of studying the written or spoken responses of participants or already published articles in the context of their social relations. It finds the purpose as well as the effect of different languages. Cultural rules, values, briefs, and conventions in communication are also the subjects of discourse analysis. Moreover, it also aims to explore the social, historical and political context of how different languages relate to one another.<\/p>\n","protected":false},"excerpt":{"rendered":" Qualitative data is usually subjective, rich, and contains in-depth information about the subject under study. Categorical data is another name for the qualitative data as mostly we analyse this data by grouping them into different categories. Qualitative data analysis is useful in determining traits, characteristics and frequency. One-to-one interviews, focus groups, case studies, observations, and longitudinal studies…<\/p>\n","protected":false},"author":6,"featured_media":3166,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[51],"tags":[1387,1385,1386],"class_list":["post-3165","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-education","tag-process-of-qualitative-data-analysis","tag-qualitative-data-analysis","tag-qualitative-data-analysis-process"],"yoast_head":"\nWhat Are The Five Steps Of Qualitative Data Analysis?<\/h2>\n\n\n\n
Arranging The Data<\/h3>\n\n\n\n
Data Organisation<\/h3>\n\n\n\n
Coding<\/h3>\n\n\n\n
Data Validation<\/h3>\n\n\n\n
Conclude Your Data<\/h3>\n\n\n\n
What Are The Five Methods Of Qualitative Data Analysis?<\/h2>\n\n\n\n
Content Analysis<\/h3>\n\n\n\n
Narrative Analysis <\/h3>\n\n\n\n
Framework Analysis<\/h3>\n\n\n\n
Grounded Theory<\/h3>\n\n\n\n
Discourse Analysis<\/h3>\n\n\n\n