Data Analysis Overview
Definition of Data Analysis
According to Braceros (2015), data analysis involves understanding collected data using statistical treatment (quantitative analysis) or thematic analysis (qualitative analysis). It serves as the basis for claims and conclusions, satisfying the study's objectives.
Purposes of Data Analysis:
- To turn raw data into meaningful information.
- To summarize and describe data.
- To answer research questions or problems.
- To make inferences about the population.
- To verify the study's results.
Research Methods in Data Analysis
1. Quantitative Research Methods
Survey Method
- Researchers collect data from a sample population at a single time or over multiple periods.
- Respondents provide information about their beliefs, opinions, characteristics, and behaviors.
Experimental Method
- Determines if an intervention influences an outcome.
- A treatment group receives the intervention, while a control group does not.
- Uses random sampling and random assignment.
Content Analysis
- Focuses on analyzing messages or symbols.
- Defines variables or categories for the study.
- Uses coding sheets to record information and infer results.
2. Qualitative Research Methods
Interviews & Focus Group Discussions
- Conducted through face-to-face, telephone, email, or online methods.
- Uses open-ended, unstructured questions to collect in-depth insights.
Historical Research
- Uses primary and secondary sources to analyze past events.
- Establishes the authenticity and credibility of sources.
Observation-Based Research
- Direct Observation: Researchers gather data by observing subjects in their natural environment.
- Participant Observation & Ethnography: Researchers participate in the group they are studying while taking field notes.
Quantitative Data Analysis
Data Coding
- Encoding Data: Assign numerical codes to variable attributes (e.g., Male = 1, Female = 2).
- Creating a Codebook: Documents coding procedures for computerized data processing.
- Data Entry & Statistical Analysis: Uses software like SPSS (Statistical Package for the Social Sciences) for statistical analysis.
Statistical Analysis
Descriptive Analysis
Summarizes data meaningfully using statistical tools:
- Measures of Central Tendency (Mean, Median, Mode)
- Measures of Variability (Range, Variance, Standard Deviation)
- Percentage and Frequency Count
Inferential Analysis
- Estimates population parameters and tests hypotheses.
- Uses statistical tests such as:
Comparison Tests
| Comparison Test | Parametric | What is being compared? | Samples |
|---|---|---|---|
| T-test | Yes | Means | 2 samples |
| ANOVA | Yes | Means | 3 samples |
| Wilcoxon Signed Rank | No | Means | 2 samples |
Comparison: Qualitative vs. Quantitative Research Methods
| Attributes | Qualitative Research | Quantitative Research |
|---|---|---|
| Analytical Objectives | Describes individual experiences and beliefs | Describes characteristics of a population |
| Type of Questions | Open-ended questions | Closed-ended questions |
| Data Collection | Interviews, observations, focus groups | Surveys, experiments, structured observations |
| Data Type | Descriptive (words, themes) | Numerical (statistics) |
| Flexibility | Questions evolve based on responses | Pre-defined questions and structure |
Comments
Post a Comment