Conquering Excel
This week, I finally got around to analyzing how cultural and policy factors are actually correlating with literacy rates in Mexico and the United States. I’ve been working with four key variables—education funding for literacy, libraries per capita, national reading campaign strength, and my own Reading Culture Index (RCI)—and used Excel to calculate correlation coefficients for each one.
For the RCI, I created a 5-point scale based on five specific cultural indicators. Each country earned one point for meeting the following criteria:
- Reading is clearly valued in schools
- Frequent use of public libraries
- Presence of summer reading programs
- Literature has a noticeable presence on social media
- High search relevance of popular books
Mexico scored 3/5: reading is emphasized in schools (especially after their national campaign-Estrategia Nacional de Lectura, social media campaigns about reading have grown, and search interest in books has increased—especially during national initiatives. However, public library use remains low (because of the limited locations) and summer reading programs aren’t widespread yet.
The U.S. scored 4/5: reading is emphasized in school curricula, libraries are frequently used, and summer reading programs are common across libraries and schools. Literature does reasonably well on social media (like the infamous BookTok), but the search relevance of books isn’t consistently high, especially when compared to other entertainment content.
After entering ten years of data (2013–2023) into Excel, I used the correlation function to calculate the correlation between each variable and the adult literacy rate.
In Mexico, the strongest relationship was between reading campaign strength and literacy rate (r = 0.78), supporting the idea that national campaigns aligned with international goals—like the UN’s SDGs—are effectively raising awareness and engagement. The RCI followed closely with a correlation of r = 0.69, suggesting cultural shifts are also driving measurable improvements.
In the U.S., the highest correlation came from libraries per capita (r = 0.73), which reflects a strong infrastructure that likely boosts reading access. RCI had a moderate correlation of r = 0.56, and literacy funding trailed behind at r = 0.49, possibly due to inconsistent state-level implementation.
These results confirm that cultural value plays a significant role in improving literacy—not just policy or spending. Next, I’ll dig deeper into regional trends to see if local variations within each country tell a different story. Thanks for sticking around!
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