Introduction:
This report analyses household expenditure data from 40 individuals, covering four spending categories: housing, food, goods, and services. The objective is to summarise the dataset and create several visualisations—including pie charts, bar charts, histograms, boxplots, and a Pareto chart—to better understand spending patterns and identify dominant categories.
library (HSAUR2)
## Loading required package: tools
data("household",package="HSAUR2")
head(household)
## housing food goods service gender
## 1 820 114 183 154 female
## 2 184 74 6 20 female
## 3 921 66 1686 455 female
## 4 488 80 103 115 female
## 5 721 83 176 104 female
## 6 614 55 441 193 female
summary(household)
## housing food goods service
## Min. : 184.0 Min. : 47.00 Min. : 6.0 Min. : 20.0
## 1st Qu.: 493.2 1st Qu.: 76.25 1st Qu.: 127.8 1st Qu.: 139.0
## Median : 768.0 Median : 268.00 Median : 294.5 Median : 262.0
## Mean : 828.4 Mean : 435.20 Mean : 873.7 Mean : 460.6
## 3rd Qu.:1033.5 3rd Qu.: 768.25 3rd Qu.: 948.2 3rd Qu.: 452.8
## Max. :1981.0 Max. :1308.00 Max. :6471.0 Max. :2063.0
## gender
## female:20
## male :20
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## Package 'qcc' version 2.7
## Type 'citation("qcc")' for citing this R package in publications.
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## Pareto chart analysis for defect
## Frequency Cum.Freq. Percentage Cum.Percent.
## Small Portions 95.000000 95.000000 23.631841 23.631841
## Overpriced 80.000000 175.000000 19.900498 43.532338
## Others 76.000000 251.000000 18.905473 62.437811
## Delay 66.000000 317.000000 16.417910 78.855721
## Not tasty 48.000000 365.000000 11.940299 90.796020
## Slow Service 27.000000 392.000000 6.716418 97.512438
## Cold Food 10.000000 402.000000 2.487562 100.000000
Conclusion:
The analysis shows that goods and housing have the highest average expenditures, while food and services are lower. Histograms and boxplots reveal large variation in goods spending, including several extreme values. The Pareto chart indicates that only a few complaint categories contribute to most issues. Overall, the visualisations provide a clear overview of the data and highlight the most significant patterns.