2. Collecting Data
Once the problem is defined, the next step is to gather relevant data using appropriate methods such as surveys, interviews, or experiments. Ensuring data accuracy and reliability is paramount at this stage.
3. Cleaning and Organizing Data
Raw data often contains errors, inconsistencies, and missing values. Cleaning and organizing the data involve tasks like removing duplicates, handling missing values, and standardizing formats to prepare it for analysis.
4. Analyzing Data
With clean and organized data in hand, it's time to apply statistical techniques and analytical tools to derive insights. This step involves exploring the data, identifying patterns, and testing hypotheses.
5. Interpreting Results
Interpreting the results of the analysis involves making sense of the findings in the context of the research objectives. It requires critical thinking and the ability to draw meaningful conclusions from the data.
6. Drawing Conclusions
Based on the analysis and interpretation of results, conclusions are drawn regarding the research questions or hypotheses. This step involves summarizing key findings and assessing their implications.
7. Communicating Findings
