Hi there,
This is my first post on this forum. I am rather confused at a question I have been assigned: I have data set with the context of over 65's & healthcare in the US. The variables are:
One of the questions in the assignment is 'Compute the skewness and kurtosis of the annual household income for both the married and unmarried individuals separately. Discuss.' How would one go about separating the binary 'marry' variable in order to compute skewness and kurtosis for income. Really do appreciate any help on this. If I didn't adhere to the forum conventions - apologises, again, my first post. Thank you in advance!
EDIT: SOLVED. NO NEED TO REPLY! THANKS.
This is my first post on this forum. I am rather confused at a question I have been assigned: I have data set with the context of over 65's & healthcare in the US. The variables are:
| sid | Subject ID |
| age | Age |
| famsze | Size of the family |
| educyr | Years of education |
| totexp | Total medical expenditure |
| retire | =1 if retired |
| female | =1 if female |
| white | =1 if white |
| hisp | =1 if Hispanic |
| marry | =1 if married |
| northe | =1 if North-East area |
| mwest | =1 if Mid-West area |
| south | =1 if South area (West is excluded) |
| phylim | =1 if has functional limitation |
| actlim | =1 if has activity limitation |
| msa | =1 if metropolitan statistical area |
| income | annual household income (in 1000 dollars) |
| injury | =1 if condition is caused by an accident/injury |
| priolist | =1 if has medical conditions that are on the priority |
| totchr | # of chronic problems |
| suppins | =1 if has supplementary private insurance |
| hvgg | =1 if health status is excellent, good or very good |
EDIT: SOLVED. NO NEED TO REPLY! THANKS.
