SPSS Data Analysis Support Project

The raw data contained numerous inconsistencies and missing values that must be addressed before analysis. Complex Variable Recoding: Certain variables required intricate recording to fit the analysis model, which was challenging due to the data's complexity. Statistical Test Selection: Identifying and running the appropriate statistical tests for various data sets posed a challenge, especially with diverse data requirements.

Report Clarity:

Generating comprehensive reports that effectively communicated the analysis results to stakeholders was critical.

Solutions Data Cleaning Techniques:

Employed advanced data cleaning techniques to handle missing values, outliers, and inconsistencies, ensuring high-quality data for analysis. Strategic Recoding: Implemented systematic variable recoding strategies to transform data variables, facilitating robust statistical analysis accurately.

Expert Statistical Analysis:

Leveraged deep statistical knowledge to select and run the most appropriate tests, ensuring accurate and relevant results. Effective Reporting: Created detailed, easy-to-understand reports with visual aids and clear explanations, effectively conveying the analysis outcomes to stakeholders.