Immigrants from Lithuania vs Bolivian Female Poverty Among 18-24 Year Olds

The statistical analysis conducted on geographies consisting of 116,192,815 people shows no correlation between the proportion of Immigrants from Lithuania and poverty level among females between the ages 18 and 24 in the United States with a correlation coefficient (R) of -0.048 and weighted average of 17.4%. Similarly, the statistical analysis conducted on geographies consisting of 182,623,221 people shows a poor positive correlation between the proportion of Bolivians and poverty level among females between the ages 18 and 24 in the United States with a correlation coefficient (R) of 0.199 and weighted average of 17.4%, a difference of 0.13%.

Female Poverty Among 18-24 Year Olds Correlation Summary

Measurement	Immigrants from Lithuania	Bolivian
Minimum	2.6%	2.6%
Maximum	60.0%	47.4%
Range	57.4%	44.8%
Mean	14.4%	16.9%
Median	12.3%	16.2%
Interquartile 25% (IQ1)	7.8%	11.4%
Interquartile 75% (IQ3)	17.2%	21.2%
Interquartile Range (IQR)	9.3%	9.8%
Standard Deviation (Sample)	11.6%	8.7%
Standard Deviation (Population)	11.3%	8.7%

Demographics Similar to Immigrants from Lithuania and Bolivians by Female Poverty Among 18-24 Year Olds

In terms of female poverty among 18-24 year olds, the demographic groups most similar to Immigrants from Lithuania are Immigrants from Venezuela (17.4%, a difference of 0.13%), Immigrants from Hong Kong (17.5%, a difference of 0.23%), Immigrants from Colombia (17.3%, a difference of 0.41%), Immigrants from North Macedonia (17.6%, a difference of 0.80%), and Maltese (17.6%, a difference of 0.86%). Similarly, the demographic groups most similar to Bolivians are Immigrants from Venezuela (17.4%, a difference of 0.0%), Immigrants from Hong Kong (17.5%, a difference of 0.10%), Immigrants from Colombia (17.3%, a difference of 0.54%), Immigrants from North Macedonia (17.6%, a difference of 0.67%), and Maltese (17.6%, a difference of 0.73%).

Demographics	Rating \| Rank	Female Poverty Among 18-24 Year Olds
Koreans	100.0 /100 \| #10	Exceptional 16.9%
Thais	100.0 /100 \| #11	Exceptional 17.0%
Immigrants \| Pakistan	100.0 /100 \| #12	Exceptional 17.0%
Immigrants \| Poland	100.0 /100 \| #13	Exceptional 17.1%
Tongans	100.0 /100 \| #14	Exceptional 17.1%
Cubans	100.0 /100 \| #15	Exceptional 17.2%
Peruvians	100.0 /100 \| #16	Exceptional 17.2%
Immigrants \| Taiwan	100.0 /100 \| #17	Exceptional 17.3%
Immigrants \| Colombia	100.0 /100 \| #18	Exceptional 17.3%
Immigrants \| Lithuania	100.0 /100 \| #19	Exceptional 17.4%
Immigrants \| Venezuela	100.0 /100 \| #20	Exceptional 17.4%
Bolivians	100.0 /100 \| #21	Exceptional 17.4%
Immigrants \| Hong Kong	100.0 /100 \| #22	Exceptional 17.5%
Immigrants \| North Macedonia	100.0 /100 \| #23	Exceptional 17.6%
Maltese	100.0 /100 \| #24	Exceptional 17.6%
Immigrants \| South Central Asia	100.0 /100 \| #25	Exceptional 17.6%
Immigrants \| Fiji	100.0 /100 \| #26	Exceptional 17.7%
Colombians	100.0 /100 \| #27	Exceptional 17.7%
Venezuelans	100.0 /100 \| #28	Exceptional 17.7%
Portuguese	100.0 /100 \| #29	Exceptional 17.8%
Immigrants \| South Eastern Asia	100.0 /100 \| #30	Exceptional 17.8%