Top 1000 Most Popular U.S. Baby Names Of 1970

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1970 Popular Names U.S. - Top 1000 Baby Names
				Change from 1969						Change from 1969
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Jennifer	46,157	2.520	2	12,455	1	Michael	85,302	4.477	0	99
2	Lisa	38,963	2.127	-1	-6,066	2	James	61,759	3.241	1	1,844
3	Kimberly	34,136	1.863	1	1,059	3	David	61,752	3.241	-1	-1,948
4	Michelle	34,050	1.859	-2	-272	4	John	58,525	3.071	0	-246
5	Amy	25,209	1.376	1	3,745	5	Robert	57,203	3.002	0	-1,122
6	Angela	24,927	1.361	1	3,872	6	Christopher	41,772	2.192	1	6,074
7	Melissa	23,737	1.296	-2	717	7	William	38,910	2.042	-1	1,281
8	Tammy	19,586	1.069	1	535	8	Brian	31,930	1.676	1	243
9	Mary	19,203	1.048	-1	-648	9	Mark	31,492	1.653	-1	-1,902
10	Tracy	18,468	1.008	7	3,360	10	Richard	30,456	1.598	0	-650
11	Julie	17,159	0.937	1	-579	11	Jeffrey	30,153	1.582	0	1,174
12	Karen	16,701	0.912	1	-937	12	Scott	28,592	1.501	0	-89
13	Laura	16,493	0.900	-3	-1,427	13	Jason	27,287	1.432	12	10,790
14	Christine	16,061	0.877	0	-694	14	Kevin	26,980	1.416	2	3,417
15	Susan	15,738	0.859	-4	-2,069	15	Steven	26,816	1.407	-1	267
16	Dawn	15,682	0.856	5	1,914	16	Joseph	26,736	1.403	-1	544
17	Stephanie	15,389	0.840	2	899	17	Thomas	26,685	1.400	-4	-784
18	Elizabeth	15,119	0.825	-2	-178	18	Eric	23,573	1.237	3	2,816
19	Heather	14,668	0.801	15	4,599	19	Daniel	23,530	1.235	-1	355
20	Kelly	14,610	0.798	-5	-1,718	20	Timothy	22,436	1.177	-3	-934
21	Tina	13,863	0.757	1	262	21	Charles	22,430	1.177	-2	753
22	Shannon	13,546	0.739	9	3,095	22	Anthony	21,185	1.112	-2	273
23	Lori	13,446	0.734	-3	-572	23	Paul	20,205	1.060	-1	-489
24	Patricia	13,405	0.732	-6	-1,547	24	Matthew	20,200	1.060	0	2,732
25	Cynthia	12,922	0.705	-2	-598	25	Kenneth	16,816	0.883	-2	-735
26	Pamela	12,909	0.705	-2	-448	26	Gregory	16,291	0.855	0	118
27	Sandra	11,247	0.614	-2	-942	27	Stephen	14,774	0.775	0	-324
28	Wendy	11,099	0.606	1	475	28	Todd	14,428	0.757	0	-324
29	Rebecca	10,855	0.593	-1	-95	29	Ronald	13,615	0.715	0	-1,009
30	Nicole	10,691	0.584	17	3,477	30	Donald	12,403	0.651	0	-374
31	Michele	10,096	0.551	-1	-462	31	Edward	12,294	0.645	1	-163
32	Donna	9,968	0.544	-6	-1,480	32	Andrew	11,998	0.630	1	710
33	Deborah	9,848	0.538	-6	-1,340	33	Patrick	11,740	0.616	-2	-938
34	Teresa	9,606	0.524	-2	-750	34	Shawn	10,951	0.575	7	2,680
35	Christina	9,586	0.523	2	263	35	Gary	10,722	0.563	0	-428
36	Denise	9,341	0.510	-1	-457	36	Douglas	10,415	0.547	-2	-832
37	Sharon	9,176	0.501	-1	-517	37	Sean	10,354	0.543	0	999
38	Linda	8,730	0.477	-5	-1,518	38	Keith	9,613	0.504	-2	166
39	Maria	8,677	0.474	1	292	39	Craig	9,373	0.492	0	590
40	Brenda	8,336	0.455	-2	-656	40	George	8,919	0.468	-2	-283
41	Barbara	8,026	0.438	-2	-782	41	Troy	8,448	0.443	1	353
42	Stacy	7,773	0.424	11	1,286	42	Jonathan	8,203	0.430	4	1,116
43	Andrea	7,710	0.421	5	508	43	Larry	8,105	0.425	-3	-180
44	Cheryl	7,441	0.406	-3	-904	44	Peter	8,058	0.423	-1	222
45	Kathleen	7,408	0.404	-3	-893	45	Jerry	7,424	0.390	0	134
46	Rhonda	7,379	0.403	-2	-539	46	Dennis	7,320	0.384	-2	-42
47	Debra	7,197	0.393	-4	-752	47	Bradley	6,823	0.358	6	430
48	Stacey	7,155	0.391	4	539	48	Frank	6,805	0.357	-1	-120
49	Tonya	7,138	0.390	5	971	49	Raymond	6,789	0.356	1	143
50	Nancy	7,063	0.386	-5	-835	50	Jeffery	6,705	0.352	-2	-36

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.