qqnorm(nils1$`Percent of Total`, main='Check for Normal Distribution')
qqline(nils1$`Percent of Total`)
From the above qqnorm,the data appears to be normally distributed
- Plotting the data completely to see what the percent of total households having accounts looks
like
when having physical branch
ggplot(nils1, aes(x = "Physical_branch", y = `Percent of Total`)) +
geom_bar(aes(fill=`Footprint`),stat="identity", color="black",position=position_dodge())
-From the above plot, houses having physical branch nearby appear to have a higher account
percentage
- Correlation test
cor.test(nils1$`Total Households`,nils1$`Households with account`)
# there is 92% correlation between these two variables
- Two sample t-test for percent of households with account having physical branch and without
physical
branch
t.test(physicalbranch_yes$`Percent of Total`,physicalbranch_no$`Percent of Total`)
- p-value is 0.128 which means that we fail to reject the null hypothesis that the number of
households
with account having physical branch nearby is equal to the number of households with account
not