Data analysis is the most crucial part of any research. Data analysis summarizes collected data. It involves the interpretation of data gathered through the use of analytical and logical reasoning to determine patterns, relationships or trends.
Cleaning data
* Did you capture and code your data in the right manner?
*Do you have all data or missing data?
* Do you have enough observations?
* Do you have any outliers? If yes, what is the remedy for outlier?
* Does your data have the potential to answer your questions?
Analyzing data
* Visualize your data, e.g. charts, tables, and graphs, to mention a few.
* Identify patterns, correlations, and trends
* Test your hypotheses
* Let your data tell a story
Reports the results
* Communicate and interpret the results
* Conclude and recommend
* Your targeted audience must understand your results
* Use more datasets and samples
* Use accessible and understandable data analytical tool
* Do not delegate your data analysis
* Clean data to confirm that they are complete and free from errors
* Analyze cleaned data
* Understand your results
* Keep in mind who will be reading your results and present it in a way that they will understand it
* Share the results with the supervisor oftentimes
Quantitative Analysis of Questionnaires by Bringing together the techniques required to understand, interpret and quantify the processes involved when exploring structures and relationships in questionnaire data, Quantitative Analysis of Questionnaires provides the knowledge and capability for a greater understanding of choice decisions. The ideal companion for non-mathematical students with no prior knowledge of quantitative methods, it highlights how to uncover and explore what lies within data that cannot be achieved through descriptive statistics. This book introduces significance testing, contingency tables, correlations, factor analysis (exploratory and confirmatory), regression (linear and logistic), discrete choice theory and item response theory. Using simple and clear methodology, and rich examples from a range of settings, this book: provides hands-on analysis with data sets from both SPSS and Stata packages; explores how to articulate the calculations and theory around statistical techniques; offers workable examples in each chapter with concepts, applications and proofs to help produce a higher quality of research outputs; discusses the use of formulas in the appendix for those who wish to explore a greater mathematical understanding of the concepts. Quantitative Analysis of Questionnaires is the ideal introductory textbook for any student looking to begin and or improve statistical learning as well as interpretation.
Analyzing Group Interactions by Analyzing Group Interactions gives a comprehensive overview of the use of different methods for the analysis of group interactions. International experts from a range of different disciplines within the social sciences illustrate their step-by-step procedures of how they analyze interactions within groups and explain what kind of data and skills are needed to get started. Each method is discussed in the same, structured manner, focusing on each method's strengths and weaknesses, its applicability and requirements, and the precise workflow to "follow along" when analyzing group interactions with the respective method. The analyzing strategies covered in this book include ethnographical approaches, phenomenology, content analysis, documentary method, discourse analysis, grounded theory, social network analysis, quantitative ratings, and several triangulative and mixed-method research designs. This volume is recommended for researchers at all levels that need guidance with the complex task of analyzing group interactions. The unified structure throughout the book facilitates comparison across the different methods and helps with deciding on the approach to be taken.
