Figure 4.2 shows a histogram of the loan-to-value ratios. The histogram reveals features of the ratio distribution, such as its skewness and the peak at 0.175, which are not evident from the tables in the previous example. The following statements create the histogram:
ods graphics off; title 'Home Loan Analysis'; proc univariate data=HomeLoans noprint; histogram LoanToValueRatio; inset n = 'Number of Homes' / position=ne; run;
By default, PROC UNIVARIATE produces traditional graphics output, and the basic appearance of the histogram is determined by the prevailing ODS style. The NOPRINT option suppresses the display of summary statistics. The INSET statement inserts the total number of analyzed home loans in the upper right (northeast) corner of the plot.
Figure 4.2: Histogram for Loan-to-Value Ratio
The data set HomeLoans
contains a variable named LoanType
that classifies the loans into two types: Gold and Platinum. It is useful to compare the distributions of LoanToValueRatio
for the two types. The following statements request quantiles for each distribution and a comparative histogram, which are
shown in Figure 4.3 and Figure 4.4.
title 'Comparison of Loan Types'; options nogstyle; ods select Quantiles MyHist; proc univariate data=HomeLoans; var LoanToValueRatio; class LoanType; histogram LoanToValueRatio / kernel(color=red) cfill=ltgray name='MyHist'; inset n='Number of Homes' median='Median Ratio' (5.3) / position=ne; label LoanType = 'Type of Loan'; run; options gstyle;
The ODS SELECT statement restricts the default output to the tables of quantiles and the graph produced by the HISTOGRAM statement,
which is identified by the value specified by the NAME= option. The CLASS statement specifies LoanType
as a classification variable for the quantile computations and comparative histogram. The KERNEL option adds a smooth nonparametric
estimate of the ratio density to each histogram. The INSET statement specifies summary statistics to be displayed directly
in the graph.
The NOGSTYLE system option specifies that the ODS style not influence the appearance of the histogram. Instead, the CFILL= option determines the color of the histogram bars and the COLOR= option specifies the color of the kernel density curve.
Figure 4.3: Quantiles for Loan-to-Value Ratio
Comparison of Loan Types |
Quantiles (Definition 5) | |
---|---|
Quantile | Estimate |
100% Max | 1.0617647 |
99% | 0.8974576 |
95% | 0.6385908 |
90% | 0.4471369 |
75% Q3 | 0.2985099 |
50% Median | 0.2217033 |
25% Q1 | 0.1734568 |
10% | 0.1411130 |
5% | 0.1213079 |
1% | 0.0942167 |
0% Min | 0.0651786 |
Comparison of Loan Types |
Quantiles (Definition 5) | |
---|---|
Quantile | Estimate |
100% Max | 1.312981 |
99% | 1.050000 |
95% | 0.691803 |
90% | 0.549273 |
75% Q3 | 0.430160 |
50% Median | 0.366168 |
25% Q1 | 0.314452 |
10% | 0.273670 |
5% | 0.253124 |
1% | 0.231114 |
0% Min | 0.215504 |
The output in Figure 4.3 shows that the median ratio for Platinum loans (0.366) is greater than the median ratio for Gold loans (0.222). The comparative histogram in Figure 4.4 enables you to compare the two distributions more easily. It shows that the ratio distributions are similar except for a shift of about 0.14.
Figure 4.4: Comparative Histogram for Loan-to-Value Ratio
A sample program for this example, univar1.sas, is available in the SAS Sample Library for Base SAS software.