Quantitative and Qualitative Softwares PDF

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Looks at statistics involving qualitative and quantitative softwares used....

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A multitude of software programs designed for use with quantitative and qualitative data is available today. Quantitative research, predominantly statistical analysis, is still common in the social sciences and such software is frequently used among social science researchers. Most notably, statistical packages find applications in the social sciences. The main demand made of such packages in social science research is that they be comprehensive, flexible, and can be used with almost any type of file. There is a whole range of software packages and tools for data analyses and visualisation - from Access or Excel to dedicated packages, such as SPSS, Stata and Nvivo for qualitative (textual and audio-visual) data analysis (QDA). Thus the aim of this essay is to write detailed notes about all the computer softwares and practical steps in chronological order involved in analyzing quantitative data, qualitative data and mixed methods data with practical examples. Data Analysis software is defined as a tool that is used to process and manipulate information, analyze the relationship and correlation between the dataset by providing quality analysis like transcription analysis, discourse analysis, grounded theory methodology and content analysis, and decision-making methods using the Statistical and Analytical Capabilities, based upon these capabilities data analysis software is classified as exploratory data analysis and confirmatory data analysis (Yauch, 2003). Data Analysis helps in the form of clarification, understanding or interpretation of the individuals and things to assist within the meaningful and symbolic content of qualitative and quantitative information (Creswell, 2009). Qualitative and Quantitative are two fundamental methods of aggregating and interpreting data in the analysis. These strategies can be used independently or at the same time since all of them have the same objectives. Quantitative analysis is often related to numerical analysis where data is collected, classified, and then computed for definite findings using a set of statistical methods (Yauch, 2003). Qualitative analysis, on the other hand, is concerned with the analysis of information that cannot be quantified and is related to the understanding and insights of objects (Yauch, 2003). Quantitative and Qualitative research data analysis strategies provide tools that help in transcription analysis, cryptography and text interpretation, algorithmic abstraction, content analysis, and discourse analysis that helps users to avoid wasting time and manage large amounts of information, increase flexibility, and improve validity and suitability of information analysis (Maxwell, 2002). 1|Page

To begin with, Statistical Package for Social Science (SPSS) is one of the computer software’s of analyzing quantitative and qualitative data. Statistical Package for Social Science (SPSS) is the most popular quantitative analysis software program used by social scientists. Made and sold by IBM, it is comprehensive, flexible, and can be used with almost any type of data file. However, it is especially useful for analyzing large-scale survey data. It can be used to generate tabulated reports, charts, and plots of distributions and trends, as well as generate descriptive statistics such as means, medians, modes and frequencies in addition to more complex statistical analyses like regression models. For example, the excel file can be loaded with all the data. Once all the data is collected, it is important to keep the excel file ready with all data inserted using the right tabular forms. Data can then be imported into SPSS. There is need to import raw data into SPSS through the excel file. Once the data is imported, then SPSS will analyze it. Depending on what the researcher wants to analyse, he or she can give desired commands in the SPSS software. Each tool has guidelines on how it should be used and the researcher can feed in all the options to get the most accurate results. The results from the software are given efficiently and accurately, providing researchers a better idea of appropriate future studies and a direction for moving forward. The ultimate objective of the SPSS is to help arrive at conclusions based on specific research. The software helps you to derive conclusions and predict the future easily with minimum statistical deviation. It is also difficult to account for weights, strata and group effects with SPSS. Secondly, STATA is another software of analyzing quantitative and qualitative data which is an interactive data analysis program that runs on a variety of platforms. It can be used for both simple and complex statistical analyses. STATA uses a point-and-click interface as well as command syntax, which makes it easy to use (Berg, 2012). STATA also makes it simple to generate graphs and plots of data and results. Analysis commands are entered into the command window and the review window records those commands. The variables window lists the variables that are available in the current data set along with the variable labels, and the results appear in the results window. STATA has 4 separate windows for typing in commands and for viewing results. The command window is for writing and running commands interactively. In the review window the researcher can view (and activate) the command lines he or she previously 2|Page

wrote. Clicking a command in the review window reproduces the command int command window for editing and rerunning. In the variables window all variables and labels are listed. Clicking on a variable name in the variables window reproduces that name in the command window. Thirdly, Statistical Analysis System is another computer software of analyzing qualitative data and examples of this include HTML, RTF, excel, etc. In addition to statistical analysis, it also allows programmers to perform report writing, graphics, business planning, forecasting, quality improvement, project management and more. Statistical Analysis System is a great program for the intermediate and advanced user because it is very powerful; it can be used with extremely large datasets and can perform complex and advanced analyses (Leedy, 2014). Statistical Analysis System is good for analyses that requires the researcher to take into account weights, strata, or groups. Unlike SPSS and STATA, SAS is run largely by programming syntax rather than point-and-click menus, so some knowledge of the programming language is required. Furthermore, NVivo is another a software used for qualitative and mixed-methods research. Specifically, it is used for the analysis of unstructured text, audio, video, and image data, including (but not limited to) interviews, focus groups, surveys, social media, and journal articles. NVivo is designed to help users to organize, analyze, and find insights in unstructured or qualitative data such as: interviews, open-ended survey responses, articles, social media, and web content. In NVivo, coding is the process of gathering related material into a container called a Node (Bryman, 2012). When the researcher opens a node, he or she can see all the references in the project coded to the node. There are several types of codes in NVivo. Theme nodes are codes that represent the themes or topics that the researcher can find in their data. Relationships record the connection between two project items. Sentiment codes are positive and negative nodes created by auto coding of sentiment. NVivo supports deductive (pre-set coding scheme, often based on emerging themes from a literature review) and inductive (codes generated while examining the collected data) approaches to coding. MAXQDA is another computer software for qualitative, quantitative, and mixed methods data analysis which is used by thousands of people worldwide. MAXQDA was released in 1989 and it has a long history of providing researchers with powerful, innovative and easy to use analytical tools that help make a research project successful (Maxwell, 2002). It is used to analyze 3|Page

interviews, reports, tables, online surveys, focus groups, videos, audio files, literature, images, and more. Users can easily organize and categorize any kind of unstructured data, search and retrieve information, test theories and create impressive illustrations and reports. In the beginning, the data is prepared and then imported and organized in a MAXQDA project. The researcher starts the analysis by exploring the data, particularly by intensive reading of the interviews and writing initial memos and case summaries. The researcher then develops categories for their analysis using the interview guide as a starting point. In steps 3 and 4, the focus is on coding and this is called first coding cycle “basic coding” in which the researcher applies broad codes to the interview transcripts. The researcher continues the coding process and work on the category system. Category by category, the coded text segments are systematically processed: if necessary, sub-categories are created, and the data is “fine” coded in a second coding cycle. Analysis options after coding presents several analysis options for the coded data available in MAXQDA, such as the visual tools or the tools for case and group comparisons. In the final step, hints are given on how to write up results and how to ensure transparency in documenting the analysis process. Finally, Quirkos is another computer software that is used to analyze qualitative data and it helps users to sort, manage, and understand text data. Consumers can use it to tag or code relevant sections of data, and compare themes across hundreds of different sources. Moreover, the program assists qualitative researchers to understand and analyze data such as interview transcripts, surveys, and articles. It's designed to be easy to learn, visual, and affordable across the economic divide. The program allows users to see connections in their qualitative research. Quirkos shows them their topics becoming connected as they code their data. The software can overlap and cluster views, visualize correlations between topics. It can be concluded that the ability to prospect and clean the large information is important within the 21st century. There are many other Data Analysis software tools available in the market like Dedoose, Annotations and many more. It is up to the researchers to decide the appropriate data analysis tool based on their needs, development, revenue, cost of the organization.

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REFERENCES

Berg, B. L. & Howard, L. (2012). Qualitative Research Methods for the Social Sciences. (8th ed). USA: Pearson Educational Inc. Bryman, A. (2012). Social Research Methods. 4th edition. New York: Oxford University Press. Creswell, J. W. (2009). Research Design Qualitative, Quantitative and Mixed Methods Approach. (3rd ed). London: SAGE Publication. Leedy, P. & Ormrod, J. E. (2014). Practical Research Planning and Design. (10th ed). Edinburgh: Pearson Educational Inc. Maxwell, J. A. & Loomis, D. (2002). Mixed Method Design: An alternative approach in Tashakkor, A. & Teddlie, C. eds: Handbook of Mixed Methods in Social and Behavioural Research, pp241-271. Thousand Oaks, C A: SGAE Publication. Yauch, C. A. and Steudel, H. J. (2003). Complementary use of Qualitative and Quantitative Cultural Assessment Methods, Organizational Research Methods, Vol. 6, No. 4, pp. 465-481.

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