VBA Anova Analysis

In this ANOVA-based data analysis project, I led a comprehensive data cleansing and statistical evaluation initiative to analyze key product quality attributes across multiple categories. The goal was to identify statistically significant differences in performance metrics such as firmness, stickiness, cohesiveness, and gloss, using a structured and methodical approach grounded in data science and statistical testing.

The process began with meticulous data cleaning in Excel, where I resolved formatting issues, handled missing values, and standardized inconsistent entries to ensure the dataset was reliable and ready for analysis. Once the raw data was transformed into a structured table, I categorized product lots and types based on their physical and sensory characteristics.

Using one-way ANOVA (Analysis of Variance), I evaluated each product attribute to determine whether variations between product groups were statistically significant. Key findings included:

Firmness: Strong statistical significance with a p-value < 0.0001, indicating major differences across product lots.

Stickiness, Cohesiveness, and Gloss in Dish: Also demonstrated significant variance between groups, based on low p-values.

To enhance the interpretability of the results, I performed post-hoc tests (such as Tukey’s HSD) to pinpoint exactly which groups differed. This was especially useful for identifying top-performing product types. For instance, a clear distinction was observed between products labeled as "Lather Type: Oily" and "Lather Type: Waxy," which had significantly different attribute profiles.

The project concluded with the creation of a comprehensive summary report, featuring:

A detailed table outlining each product attribute

Mean values across groups

Statistical significance (p-values)

Post-hoc comparison outcomes

This final deliverable offered actionable insights into product development, quality control, and formulation optimization. By combining data cleaning, ANOVA testing, and Excel-based data visualization, the analysis provided valuable input for product improvement strategies and evidence-based decision-making.

If you're seeking support with data-driven product evaluation, statistical modeling, or quality analysis in Excel, this is exactly the type of work I specialize in.