njiririkinyanjui/Descriptive-Statistics

Analysis of banking across Kenya, Rwanda, Tanzania, and Uganda # Descriptive-Statistics * Analysis of banking across Kenya, Rwanda, Tanzania, and Uganda * As a data scientist i was tasked with the work of predictiing which individual are most likely to have or use a bank account. * From the data we see that the male population has a 53% chance of having a bank account compared to the female population who have a chance of 47% to have a bank account. * We dropped the null hypothesis for if there was a significance in the average ages of male and females becaus eit had a p-value of less than 0.05 * We investigated and saw that theres a weak positive correlation between respondent age and household size and a weak positive correlation between respondent age and year. Hence the data had a week correlation * From the principal component analysis we were able to come up with the followintg conclusions, Together the first two principal components contain 100% of the information. The first principal component analysis contains 53.098% of the variance and the second component analysis contains 46.902% off the variance. * From the t-test statistics we were able to invistigate Males have a higher standard error to females, at 95% confidence interval (CI), males have a higher CI to females and males have a higher standard deviation (std) to females