Immigrants from Lithuania vs Burmese 1 or more Vehicles in Household

The statistical analysis conducted on geographies consisting of 117,713,976 people shows a substantial positive correlation between the proportion of Immigrants from Lithuania and percentage of households with 1 or more vehicles available in the United States with a correlation coefficient (R) of 0.528 and weighted average of 90.2%. Similarly, the statistical analysis conducted on geographies consisting of 464,980,772 people shows a poor positive correlation between the proportion of Burmese and percentage of households with 1 or more vehicles available in the United States with a correlation coefficient (R) of 0.156 and weighted average of 90.4%, a difference of 0.20%.

1 or more Vehicles in Household Correlation Summary

Measurement	Immigrants from Lithuania	Burmese
Minimum	85.3%	71.5%
Maximum	100.0%	100.0%
Range	14.7%	28.5%
Mean	95.4%	93.1%
Median	95.8%	94.1%
Interquartile 25% (IQ1)	94.8%	90.5%
Interquartile 75% (IQ3)	97.4%	96.4%
Interquartile Range (IQR)	2.6%	5.9%
Standard Deviation (Sample)	3.3%	5.7%
Standard Deviation (Population)	3.2%	5.7%

Demographics Similar to Immigrants from Lithuania and Burmese by 1 or more Vehicles in Household

In terms of 1 or more vehicles in household, the demographic groups most similar to Immigrants from Lithuania are Immigrants from Moldova (90.2%, a difference of 0.0%), Immigrants from Bahamas (90.2%, a difference of 0.040%), Immigrants from Zimbabwe (90.2%, a difference of 0.040%), Sioux (90.2%, a difference of 0.040%), and Sudanese (90.3%, a difference of 0.060%). Similarly, the demographic groups most similar to Burmese are Immigrants from the Azores (90.4%, a difference of 0.0%), Immigrants from Cameroon (90.4%, a difference of 0.010%), Marshallese (90.4%, a difference of 0.010%), Nicaraguan (90.4%, a difference of 0.010%), and Immigrants from Kenya (90.4%, a difference of 0.020%).

Demographics	Rating \| Rank	1 or more Vehicles in Household
Immigrants \| Korea	90.5 /100 \| #125	Exceptional 90.5%
Immigrants \| Cameroon	89.4 /100 \| #126	Excellent 90.4%
Immigrants \| Azores	89.1 /100 \| #127	Excellent 90.4%
Burmese	89.0 /100 \| #128	Excellent 90.4%
Marshallese	88.9 /100 \| #129	Excellent 90.4%
Nicaraguans	88.8 /100 \| #130	Excellent 90.4%
Immigrants \| Kenya	88.5 /100 \| #131	Excellent 90.4%
Immigrants \| South Africa	88.1 /100 \| #132	Excellent 90.4%
Immigrants \| Syria	87.5 /100 \| #133	Excellent 90.4%
Kenyans	87.0 /100 \| #134	Excellent 90.4%
Immigrants \| Oceania	86.9 /100 \| #135	Excellent 90.4%
Hungarians	86.5 /100 \| #136	Excellent 90.3%
Latvians	86.3 /100 \| #137	Excellent 90.3%
Syrians	86.3 /100 \| #138	Excellent 90.3%
Estonians	85.6 /100 \| #139	Excellent 90.3%
Sudanese	85.2 /100 \| #140	Excellent 90.3%
Immigrants \| Moldova	83.1 /100 \| #141	Excellent 90.2%
Immigrants \| Lithuania	83.0 /100 \| #142	Excellent 90.2%
Immigrants \| Bahamas	81.5 /100 \| #143	Excellent 90.2%
Immigrants \| Zimbabwe	81.5 /100 \| #144	Excellent 90.2%
Sioux	81.3 /100 \| #145	Excellent 90.2%