Top 1000 Most Popular U.S. Baby Names Of 1915

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1915 Popular Names U.S. - Top 1000 Baby Names
				Change from 1914						Change from 1914
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Mary	58,187	5.683	0	12,842	1	John	47,576	5.401	0	9,628
2	Helen	30,866	3.015	0	7,645	2	William	38,564	4.378	0	8,811
3	Dorothy	25,154	2.457	0	6,372	3	James	33,775	3.834	0	7,512
4	Margaret	23,054	2.252	0	5,291	4	Robert	28,738	3.262	0	7,550
5	Ruth	21,878	2.137	0	6,039	5	Joseph	23,052	2.617	0	4,223
6	Mildred	15,254	1.490	1	3,604	6	George	22,307	2.532	0	4,704
7	Anna	15,119	1.477	-1	3,254	7	Charles	21,960	2.493	0	5,023
8	Elizabeth	14,103	1.377	0	2,736	8	Edward	15,889	1.804	0	3,571
9	Frances	12,787	1.249	0	3,110	9	Frank	15,006	1.703	0	3,004
10	Evelyn	11,595	1.132	1	3,089	10	Thomas	11,490	1.304	1	2,640
11	Marie	11,363	1.110	-1	2,534	11	Walter	11,256	1.278	-1	2,294
12	Virginia	10,952	1.070	2	3,351	12	Harold	10,444	1.186	2	2,881
13	Alice	10,525	1.028	-1	2,327	13	Paul	10,328	1.172	0	2,595
14	Florence	10,105	0.987	-1	2,219	14	Henry	10,138	1.151	-2	2,028
15	Lillian	9,546	0.932	1	2,192	15	Richard	9,143	1.038	2	2,474
16	Rose	9,375	0.916	-1	1,801	16	Raymond	8,981	1.019	0	2,160
17	Irene	8,323	0.813	5	2,126	17	Albert	8,825	1.002	-2	1,883
18	Louise	8,313	0.812	-1	1,665	18	Arthur	8,564	0.972	0	1,923
19	Catherine	8,181	0.799	-1	1,568	19	Harry	8,470	0.961	0	1,882
20	Edna	8,144	0.795	-1	1,855	20	Donald	7,116	0.808	3	2,281
21	Gladys	7,857	0.767	-1	1,630	21	Ralph	6,816	0.774	0	1,807
22	Josephine	7,606	0.743	1	1,710	22	Carl	6,613	0.751	2	1,806
23	Ethel	7,379	0.721	-2	1,175	23	Louis	6,518	0.740	-3	1,023
24	Ruby	7,237	0.707	0	1,612	24	Clarence	6,267	0.711	-2	1,358
25	Martha	7,216	0.705	2	1,784	25	Howard	6,103	0.693	1	1,613
26	Hazel	7,092	0.693	3	1,768	26	Fred	5,778	0.656	2	1,337
27	Grace	7,044	0.688	-2	1,450	27	Jack	5,748	0.652	0	1,262
28	Eleanor	7,036	0.687	0	1,662	28	Kenneth	5,681	0.645	2	1,503
29	Lucille	7,006	0.684	1	1,686	29	Francis	5,594	0.635	2	1,693
30	Thelma	6,762	0.660	-4	1,266	30	Willie	5,434	0.617	-5	725
31	Edith	6,761	0.660	0	1,552	31	David	5,394	0.612	-2	1,143
32	Pauline	6,334	0.619	2	1,635	32	Roy	5,052	0.573	0	1,200
33	Esther	6,321	0.617	2	1,667	33	Earl	4,908	0.557	0	1,066
34	Doris	6,292	0.615	2	1,863	34	Stanley	4,808	0.546	5	1,249
35	Gertrude	6,077	0.594	-3	1,139	35	Ernest	4,787	0.543	3	1,155
36	Annie	5,936	0.580	-3	1,136	36	Anthony	4,722	0.536	1	1,027
37	Beatrice	5,342	0.522	1	1,110	37	Lawrence	4,688	0.532	-1	985
38	Clara	5,285	0.516	-1	1,045	38	Joe	4,648	0.528	-4	936
39	Marjorie	5,119	0.500	6	1,407	39	Samuel	4,351	0.494	-4	647
40	Emma	5,044	0.493	-1	1,072	40	Herbert	4,341	0.493	2	1,088
41	Elsie	4,967	0.485	5	1,284	41	Eugene	4,321	0.491	2	1,110
42	Bernice	4,937	0.482	1	1,207	42	Alfred	4,232	0.480	-1	886
43	Ann	4,896	0.478	-3	1,008	43	Michael	4,081	0.463	-3	719
44	Julia	4,831	0.472	-2	1,018	44	Leonard	3,993	0.453	1	1,070
45	Agnes	4,795	0.468	-1	1,074	45	Elmer	3,802	0.432	1	924
46	Bertha	4,785	0.467	-5	926	46	Andrew	3,573	0.406	-2	608
47	Lois	4,775	0.466	4	1,343	47	Leo	3,527	0.400	0	872
48	Jean	4,603	0.450	6	1,322	48	Bernard	3,302	0.375	2	866
49	Katherine	4,488	0.438	-1	836	49	Peter	3,302	0.375	-1	678
50	Marion	4,456	0.435	0	906	50	Norman	3,262	0.370	4	927

United States name popularity data is provided by the Social Security Administration and is based on Social Security card applications.

Data for a given year is not made available until well into the next year.

Data reflects what was recorded and has not been edited for errors, so for example the gender associated with a name may be incorrect.

The more babies that are given a particular name, the higher the popularity ranking. If multiple names have the same usage, the tie is broken by assigning popularity rank in alphabetical order. Therefore in the case of names with fewer occurrences, names with the same number of occurrences may have vastly different rankings because they will be interranked alphabetically.

To safeguard privacy, the SSA does not include names with less than 5 occurrences.

Please note, we update the data each May when the SSA releases new figures. All data changes at that time, including previous years, which will change minutely based on new information.