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 |
0 Response to computing skewness and kurtosis of a binary variable with two mutually exclusive options
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