Python & Excel
- Statistical Analysis
- Hypothesis Testing
- Kruskal-Wallis Test
- Dunn’s Post Hoc Test
- Spearman Correlation
- Regression Analysis
Understanding the Impact of Household Characteristics on Spending Behavior
Household expenditure is a key measure of financial wellbeing and living standards. Understanding how spending varies across different household groups helps governments, businesses, and researchers identify the factors that influence consumer behavior and economic stability.
The dataset used in this study comes from the UK Living Costs and Food Survey (LCF), which captures household spending patterns alongside demographic, employment, and housing characteristics.
Determine whether household expenditure differs according to occupational class, housing tenure type, number of adults, number of children, and household income.
Is there a statistically significant relationship between household characteristics and total household expenditure?
| Variable | Type |
|---|---|
| Total Expenditure | Numerical |
| Income | Numerical |
| Occupational Class | Categorical |
| Tenure Type | Categorical |
| Number of Adults | Categorical |
| Number of Children | Categorical |
Used to compare household expenditure across different household groups.
Used to assess the relationship between household income and household expenditure.
Statistical significance was assessed using α = 0.05.
Households in higher managerial and professional occupations consistently spent more than other occupational groups.
Spending patterns differed significantly between owned households, private renters, and public renters.
Comparison of average total expenditure across household occupational classes.
Expenditure increased as the number of children increased.
Households with more adults generally had higher expenditure.
Comparison of average expenditure according to the number of adults living in the household.
Household composition is one of the strongest drivers of spending behavior.
Each point represents one household. The regression line illustrates the overall relationship between weekly household income and weekly household expenditure.
Income and expenditure showed a strong positive association.
Spearman’s ρ = 0.75
Generally: Higher-income households spend more.
The Kruskal–Wallis test was used to determine whether household expenditure differed significantly across the categories within each household characteristic.
Household characteristics ranked by their Kruskal–Wallis H statistic. Higher values indicate greater differences in expenditure between groups.
Number of Adults showed the highest Kruskal–Wallis H statistic, indicating the largest differences in household expenditure across groups. This was followed by Occupational Class, Tenure Type, and Number of Children.