Lauren-Akhidenor/Analysis-for-Bungoma-Kenya.

# Maize Productivity in Bungoma County, Kenya: Socioeconomic and Agronomic Drivers of Smallholder Output ---- > **Impact:** Transformed smallholder survey data into actionable insights, revealing how land access, training, and farming practices influence maize productivity and rural livelihoods in Kenya. ----- ## 📌 Project Overview ----- Maize (*Zea mays L.*) is Kenya’s staple crop and a key driver of rural livelihoods. However, productivity remains far below potential due to constraints such as land limitations, low input efficiency, and inconsistent access to agricultural training. This project analyzes survey data from **59 maize farmers** across four sub-counties in Bungoma County (Chwele, Sirisia, Tongaren, and Webuye West) to understand how socioeconomic factors and farming practices influence maize output. ---- ## Study Area ---- *Figure: Bungoma County, Kenya* --- ## Objectives ---- - Assess socioeconomic characteristics of maize farmers - Evaluate maize farming practices in the region - Analyze access to agricultural training - Examine productivity and output drivers --- ## Data & Methodology --- ### Data - Sample size: **59 farmers** - Source: Primary survey data ### Tools Used - Microsoft Excel → data cleaning, coding, summary statistics, visualization - SPSS → descriptive statistics, regression, correlation, t-tests ### Data Preparation - Removed duplicates and inconsistencies - Standardized categorical variables - Coded binary responses (Yes = 1, No = 0) --- ## Exploratory Analysis (Excel) --- ### 📌 Summary Statistics - Average age of household head: **51.9 years** - Average household size: **6.3 persons** - Average land available: **3.46 acres** - Average maize plot size: **2.41 acres** - Average farming experience: **20.83 years** - Average maize output: **22.02 units (self-reported; assumed bags)** ## Excel Visual Explorations *Farmer Distribution by Sub-county* *Gender Distribution* *Access to Agricultural Training* ## 📉 …