Qualitative Research Reports

• The abstract is a condensed summary of completed research
• It gives a compendium of the work done in research

Introduction

• The introduction of a qualitative project should include a review of relevant literature, similar to the introduction of a quantitative study
• The author should discuss why a qualitative methodological approach was selected

Method

• The method explains the qualitative methodology used in the study

Data Analysis and Interpretation

• This analyzes results through themes

Conclusion

• The final section of a qualitative report may be labeled "Discussion," "Conclusion," "Implications," "Recommendations," or "Applications"
• The label depends on the research nature, audience, and purpose

Discussion

• Discussions and explanations of results should give a more logical and empirical basis for the conclusion after data analysis and interpretation
• Transcripts and personal narration of events act as proof of themes and categories and are mentioned verbatim
• The results of the investigation are compared and contrasted with reviewed literature and studies
• Researchers highlight the essence of lived experiences of respondents

Key Components of the Discussion Section

• Findings are briefly restated, highlighting themes from participant experiences.
• The study maintains a central focus on the essence of the phenomenon in the discussion and ensures the essence of the phenomenon remains central to the discussion
• Interpretation of themes and patterns explores what the themes reveal beyond surface-level descriptions
• Participant quotes are used as evidence, interwoven with the researcher's analysis

Comparison with Existing Literature

• The study discusses similarities and differences between current findings and previous research
• The study is situated within the broader context of phenomenological and related fields

Theoretical and Philosophical Implications

• The findings contribute to the use of phenomenology as a research approach

Presentation of Data

• Common tools for data presentation in quantitative research include figures, graphs, and tables
• These tools present one or more data series clearly and allow readers to see results from data analysis through statistical methods

Graphs

• Shows relations, comparisons, and distributions in a data set using absolute values, percentages, or index numbers
• Lines should be clean, simple, and avoid extraneous details
• Information should be presented on the horizontal and vertical axes clearly and systematically
• Facts can be shown in ascending or descending order
• A set of related data is called a data series

Types of Graphs

• Area graphs show the relationship of different parts to a whole over time
  • They handle four to six data series
  • Enrollment statistics over five years, or regional sales for a year are examples
• Column graphs show the differences in individual values vertically between different time periods or groupings
  • They work best with one to three data series
  • Total monthly phone calls or orders received by method each month are examples
• Bar graphs show the differences in individual values horizontally
  • This graph is suitable for showing results from one or two data series, but not for different time periods
  • An example would be indicating the popularity of the top survey answers
• Line graphs feature values at different points in time, using equal time intervals along the horizontal axis
  • Effective for displaying four to six data series
  • Example: Trends in monthly customer service calls handled
• Pie graphs show the proportions of each segment of a whole
  • This graph handles only one data series
  • An example would be the proportion of funding provided from each level of government in the past year

Graph Elements

• Colors should have enough contrast between the background and each data series for clear visibility and match the slide's color scheme
• Depth indicates whether the graph is 2D or 3D and is an aesthetic choice
• All graph types except pie graphs have two axes, for data values and for time scale or data separation
  • Set the axes to suit the data, with legible labels
  • Unclear axes can lead to misinterpretation

Data Labels

• Data labels are used when the data value in a graph needs to be more clearly indicated
• It's a text box that contains the actual data value
• Should be placed close to the graphical representation of the datapoint
• Text should be legible and have sufficient contrast with the color underneath

Title

• The title should focus on interpreting the data, not on the data itself
• The title helps the audience interpret the graph properly
• Instead of "Sales 1996-2001," use "Sales Up 42% from 1996 to 2001"

Legend

• If there are more than one data series on a graph, text labels should indicate each series instead of using a legend on the graph
• Explanatory text should be placed using text boxes

Tables

• Tables provide exact values and illustrate results efficiently
• They allow researchers to present a large amount of data in a small amount of space

Elements of a Table

• Title
• Rows
• Columns
• Column labels or titles
• Data