Languages spoken in Suffolk County, MA

In October 2015, the U.S. Census Bureau released the "2009-2013 American Community Survey" which provides information on "languages spoken at home" and "ability to speak English for the Population 5 Years and Over" for the United States as a whole, states including Puerto Rico and Washington D.C., selected counties, and selected cities and urban areas. The following provides aggregated survey information on languages spoken in Suffolk County [MA]

Table showing languages spoken in Suffolk County, MA

Population 5 years and over
Speak only English at home
Speak a language other than English at home
OTHER INDO-EUROPEAN LANGUAGES

French (incl. Patois, Cajun)

French Creole

Italian

Portuguese (incl. Portuguese Creole)

German (incl. Luxembourgian)

Yiddish

Other West Germanic languages

Scandinavian languages

Greek

Russian

Polish

Serbo-Croatian languages

Other Slavic languages

Other Indic languages

Other Indo-European languages

ASIAN AND PACIFIC ISLAND LANGUAGES

Chinese (incl. Cantonese, Mandarin, other Chinese languages)

Other Asian languages

Tagalog

Other Pacific Island languages

ALL OTHER LANGUAGES

Navajo

Other Native North American languages

Other and unspecified languages

BY STATE
BY COUNTY
BY CITY

Language	Number of speakers	Margin of Error	Speak English less than "Very Well"	Margin of Error
Population 5 years and over	694,481	84	127,628	2,647
Speak only English at home	434,642	3,064	(X)	(X)
Speak a language other than English at home	259,839	3,052	127,628	2,647
SPANISH AND SPANISH CREOLE	124,998	1,360	64,907	1,644
Spanish	125,000	1,360	64,905	1,644
OTHER INDO-EUROPEAN LANGUAGES	76,440	2,706	31,075	2,063
French (incl Patois, Cajun)	8,888	808	2,472	374
French	7,845	734	2,330	369
Patois	1,040	449	140	92
French Creole	23,791	1,978	11,787	1,473
Italian	6,118	632	1,864	309
Portuguese (incl Portuguese Creole)	12,106	1,392	6,143	795
Portuguese	12,100	1,393	6,145	795
Papia Mentae	(D)	(D)	(B)	-
German (incl Luxembourgian)	2,128	319	305	152
German	2,130	319	305	152
Yiddish	154	82	11	17
Other West Germanic languages	729	367	128	165
Dutch	665	379	130	165
Afrikaans	65	47	(B)	-
Scandinavian languages	367	127	(B)	-
Swedish	145	87	(B)	-
Danish	125	84	(B)	-
Norwegian	95	69	(B)	-
Icelandic	(D)	(D)	(B)	-
Greek	2,541	496	714	272
Russian	5,177	522	3,062	359
Polish	1,697	395	585	203
Serbo-Croatian languages	1,252	420	501	208
Serbocroatian	855	299	430	192
Croatian	235	244	(D)	(D)
Serbian	165	104	20	21
Other Slavic languages	706	263	169	83
Ukrainian	240	107	90	60
Czech	80	55	(B)	-
Slovak	(D)	(D)	(D)	(D)
Bulgarian	295	196	60	65
Macedonian	55	95	(B)	-
Slovene	(D)	(D)	(B)	-
Armenian	331	171	107	114
Persian	499	181	176	105
Hindi	1,967	473	314	158
Gujarati	963	339	256	213
Urdu	642	287	170	171
Other Indic languages	2,131	481	579	249
India nec3	185	165	40	41
Bengali	625	257	330	188
Panjabi	310	187	45	42
Marathi	125	85	(D)	(D)
Assamese	(D)	(D)	(B)	-
Nepali	805	341	135	139
Sinhalese	70	50	(B)	-
Other Indo-European languages	4,253	820	1,732	430
Jamaican Creole	375	197	45	43
Krio	(D)	(D)	(D)	(D)
Romanian	390	316	200	191
Irish Gaelic	665	326	60	37
Albanian	2,395	711	1,285	389
Lithuanian	250	154	95	78
Latvian	80	54	(D)	(D)
Pashto	(D)	(D)	(B)	-
Kurdish	70	78	30	41
ASIAN AND PACIFIC ISLAND LANGUAGES	44,152	1,174	25,588	897
Chinese (incl Cantonese, Mandarin, other Chinese languages4)	22,345	1,112	13,817	902
Chinese	14,645	1,122	9,500	824
Hakka	(D)	(D)	(B)	-
Cantonese	4,720	637	3,005	514
Mandarin	2,715	458	1,270	293
Formosan	205	90	45	33
Wu	40	36	(B)	-
Japanese	1,223	302	470	164
Korean	2,807	491	1,074	281
Mon-Khmer, Cambodian	1,106	353	592	225
Hmong	19	26	13	23
Thai	460	196	192	106
Laotian	106	81	22	24
Vietnamese	12,875	1,150	8,596	775
Other Asian languages	1,642	457	457	208
Kazakh	25	29	(D)	(D)
Turkish	710	241	205	123
Telugu	165	112	45	42
Kannada	130	84	(D)	(D)
Malayalam	105	56	(D)	(D)
Tamil	350	196	70	71
Tibetan	50	45	(B)	-
Burmese	105	110	100	107
Tagalog	1,249	346	271	150
Other Pacific Island languages	320	115	84	74
Indonesian	155	86	55	56
Malay	135	88	30	49
Bisayan	30	33	(B)	-
ALL OTHER LANGUAGES	14,249	1,382	6,058	876
Other Native North American languages	26	39	6	12
Keres	(D)	(D)	(B)	-
Tiwa	20	37	(D)	(D)
Hungarian	185	170	56	66
Arabic	5,981	928	3,152	655
Hebrew	987	261	49	38
African languages	6,867	994	2,714	507
Amharic	1,630	473	950	349
Berber	(D)	(D)	(D)	(D)
Chadic	(D)	(D)	(B)	-
Cushite	1,940	611	925	362
Sudanic	(D)	(D)	(D)	(D)
Swahili	440	295	60	45
Bantu	390	148	95	63
Mande	130	87	75	61
Fulani	160	137	60	61
Kru, Ibo, Yoruba	2,080	556	500	223
Efik	(D)	(D)	(B)	-
African	(D)	(D)	(D)	(D)
Other and unspecified languages	203	110	81	95
Finnish	50	53	(B)	-
Estonian	20	24	(B)	-
Arawakian	(D)	(D)	(B)	-
Chibchan	80	95	80	95
Uncodable	45	38	(B)	-

Notes

Number of speakers and Speak English less than "Very Well": Detailed-language estimates are rounded to the nearest multiple of five. Aggregate estimates ("language category" and "language sub-category" entries) are unrounded and appear in table B16001. Detailed-language estimates may not sum to aggregate estimates because of rounding.
Margin of Error and Margin of Error: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data. The effect of nonsampling error is not represented in these tables.
(D): Data withheld to avoid disclosure.
(B): Either no sample observations or too few sample observations were available to compute an estimate.
(X): Question does not apply.
-: Either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
3 N.E.C. stands for not elsewhere classified. These are languages where respondents indicated they spoke either Indian or Pakistan. For Indian, it cannot be determined if the respondent spoke a native American language or spoke a language from India. For Pakistan, respondents wrote in Pakistan but it cannot be determined which one of the languages spoken in Pakistan is actually being spoken. To distinguish these languages, n.e.c. is used to indicated they are not classified in any other language code.
This category includes literal write-ins of Chinese as well as Hakka, Kan, Hsiang, Cantonese, Mandarin, Fuchow, Formosan, and Wu.