Credit Risk Analytics

 Week 2 assignment asks to submit frequency distribution programs for 3 data variables and describe the output in terms of the values the variables take, how often they take them and the presence of missing data. The program creates 3 frequency distributions and 1 cross table distribution Program LIBNAME mydata "/courses/d1406ae5ba27fe300 " access=readonly; DATA new; set mydata.gapminder; /* Insert meaningful lables to the variables */ label country="country" oilperperson="Oil per person" incomeperperson="Income per person ($) (based on 2010 dollar exchange rate)" incomecategory="Income category" polityscore="Democracy score" armedforcesrate="Armed forces personnel"; run; /* Formatting the dataset to make it ready for frequency distribution */ proc format; value incomecategory low-<5000 = 'Less than 5000' 5000-<10000 = '5000 to 10000' 10000-<15000 =...

Data set chosen I have chosen the GapMinder data set for my research question. I have also selected some additional data from the GapMinder website to substantiate my research. Research questions a) Is there any relation between the income per person (incomperperson) of a country versus polity score (polityscore). The question I try to answer is if the income per person in each country has any bearing on the democratic nature of the country. b) Do high oil consuming (oilperperson) and high income countries (incomeperperson) have a higher democracy score (polityscore)? c) Are there any other influences to democracy like the influence of armed security forces? Hypothesis 1. Poorer countries are less democratic. 2. Highly urbanised and high oil consuming countries tend to be more democratic. 3. Some countries due to historical reasons will have a higher democracy score with low income levels and vice versa. 4. High oil consuming countries will highly correlate with hi...