3Is-Q2-Data-Analysis-Methods

By examining a variety of similar cases in different settings.

The effect of political views on the perception of morality in a community.

To understand the personal stories and insights of individuals.

It is labor intensive and time-consuming.

To ensure the accuracy and quality of data.

To provide a structured approach to data analysis, often used in applied policy research.

A research method that involves generating theory from data systematically gathered and analyzed.

NVivo, Atlas ti 6.0, Hyper RESEARCH 2.8, Max QDA.

It helps in organizing data, identifying patterns, and drawing conclusions based on qualitative data.

Interpreting data to draw conclusions and insights.

Word and phrase repetitions.

Formulating the story through connecting the categories.

Results and Discussions.

Identify the questions that can be answered through the collected data.

To infer whether each respondent was actually interviewed or not.

Enhancing school performance through improved school policies.

Identifying the most commonly used words and phrases, as well as responses with unusual emotions.

A method of analyzing non-numerical data to understand concepts, opinions, or experiences.

Quantitative analysis uses statistical methods, while qualitative analysis focuses on interpretation and understanding.

To correct errors that are common in large data sets, check for outliers, and clear out any data that may hamper the accuracy of the results.

Noticable patterns.

Primary and secondary data.

Identify broad ideas, concepts, behaviors, or phrases.

Non-quantifiable elements such as events, behaviors, activities, and meanings.

Developing and applying codes.

Familiarization.

To ensure the accuracy and reliability of data before analysis.

Compliance with pre-set standards and absence of bias.

The structure and meaning of stories told by individuals.

Qualitative data analysis focuses on understanding meaning and context, while quantitative data analysis focuses on numerical data and statistical relationships.

To categorize and organize data for analysis.

To understand the most common responses and insights.

To ensure that respondents were chosen according to the research criteria.

The process of determining whether the data meets pre-set standards and is free from bias.

Summarizing the data.

Inquiries, Investigations, and Immersion.

A method for systematically analyzing the content of communication.

Social, cultural, political, and historical contexts.

Deep engagement with the data to understand its context and nuances.

Identifying words and phrases most commonly used by respondents and those with unusual emotions.

Grouping and assigning values to responses from the survey.

Qualitative methods do not have universally applicable techniques.

Identifying themes, patterns, and relationships.

Identifying themes, patterns, and relationships.

The social context in which the communication occurs.

Noteworthy quotations from the transcript.

Analyzing social media comments regarding perception of an advertisement campaign.

Thematic analysis, which involves identifying and analyzing themes within the data.

Familiarization, identifying a thematic framework, indexing, charting, and interpreting data.

To categorize data according to the thematic framework established.

Themes and common responses to questions.

Search for missing information.

Aspects of the issue that were not mentioned by respondents.

Using the stories and experiences shared by people.

Identifying themes, patterns, and relationships.

To categorize data according to themes.

The process of asking questions to gather information.

The systematic examination of data to uncover insights.

Analyzing responses from interviewees.

Analyzing the data.

To compare research findings to phenomena from a different area and discuss similarities and differences.

Read the data several times.

The social behaviors of individuals experiencing Bulimia Nervosa.

To analyze how individuals construct their self-identities within their culture.

Preparation of Qualitative Data.

Textual, visual, or audio data such as interviews, open-ended survey responses, and observations.

Developing and applying codes.

Manual coding.

It helps to categorize and interpret responses.

Qualitative data.

The process of transforming a mass of data into meaningful insights.

An action of labeling a theme or an idea.

Comparing and contrasting collected data with the findings of literature review.

Using statistical methods to describe, summarize, and compare data.

To determine the cause of a phenomenon.

Identifying a thematic framework.

The researcher and the environment.

To identify patterns, themes, and insights within qualitative data.

Responses on the perception of the Anti-terrorism bill can be coded as 'positive' or 'negative'.

Several stages, including familiarization, identifying a thematic framework, coding, charting, mapping, and interpretation.

Identifying themes, patterns, and relationships.

For the assistance provided.

Identifying themes, patterns, and relationships.

Developing and applying codes.

No, qualitative studies cannot be repeated to generate the same results.

Structuring and interpreting data to understand what it represents.

Interviews, observations from the field, or surveys.

Experiences of Healthcare Providers during the height of the Pandemic.

How do youth construct their self-identities within their culture?

Interpretation.

The ways in which language is used in texts and spoken communication to construct meaning.

Summarizing data into a visual format to facilitate comparison and analysis.

Identifying patterns and connections.

The initial organization of raw data to try to make sense of it.

Interconnecting and linking the categories of codes.

Identifying themes, patterns, and relationships.

Transcribe your data.

Data Editing.

Data Coding.

Summarizing the data.

A systematic method for data analysis that provides a structured framework for managing and analyzing qualitative data.

To systematically organize and analyze responses.

Revisiting research objectives.

A framework.

Patterns and connections.

Identifying themes, patterns, and relationships.

Investigating the functions of language used in different contexts such as social, cultural, political, and historical.

Why a certain phenomenon happened.

Ensuring that the interviewer asked all the questions, not just a few required ones.

Data Editing and Data Coding.

Word and phrase repetitions.

To highlight major themes within findings and possible contradictions.

To ensure that the procedure was duly followed.

Organizing data into a visual format for easier analysis.

Documented information such as texts, media, or physical items.

Developing and applying codes.