Half Sigma

The single women of Amarillo, Texas

Having recently discovered that Amarillo, Texas has a surplus of single women, I thought I’d look up some of these women on an online dating service. Here are quotes from some of their profiles:

“My faith is in God. I love Jesus and want to live my life in a way that is pleasing to Him.”

“Love having God in my life. He's helped me through some very tough and scary stuff. Need to know that is a priority in my potential match. At least the believing in Him part!”

“I have a relationship with Jesus, not a religion. I would never date a non-believer. I am seeking a godly man who loves the Lord and seeks to please Him with his life.”

“I also love music and children, worshiping the Lord Jesus Christ, and spending time with my family."

"I love GOD.”

“I simply believe that Jesus Christ is the son of God he came, died for our sins, rose from the dead, and now sits at the right hand of the Father God. And He will return one day.”

It seems that in order to date a woman in Amarillo, Texas, you need to love God and Jesus, or at least be willing to pretend that you do.

You also have to love other people’s kids, because nearly all these women have at least two of them.

Besides these two flaws, they seem like nice people.

* * *

In contrast, if you find a Manhattan woman’s dating profile that says anything about religion, it is likely to say something like:

“I have been becoming more spiritual with age and believe in the power of the universe.”

I think that’s code-speak for believing in the post-Christian goddess of Mother Nature religion. Yuck! I think it's easier to deal with Jesus. At least Jesus is a Republican.

The unmarried and middle-aged, by education

I used data from the Census Bureau’s 2006 American Community Survey. The charts below show the percentage of never married 41-45 year old non-Hispanic whites by education level. There is one chart for each sex.

For men, as education increases, the likelihood of being never married decreases. This is no doubt because the less education a man has, the more of a loser he is, and the less likely it is that a woman would be interested in marrying him.

Women who are high school dropouts are more likely to be never married, probably because they are white trash and behave more like the black underclass in which it’s considered normal to have children without husbands.

Women with high school degrees or some college are the least likely to be never married. But as a woman’s education level increases beyond that, her chance of being never married increases.

The chart does not tell us the cause and effect. Maybe women with more education are less desirable mates, or maybe they are too picky and no man is good enough for them. Or maybe the cause and effect run in the opposite direction. Women who are unmarried pursue more education in order to console themselves in their loneliness.

Percentage of whites who never married, by sex

Here are some more interesting charts. They tell us the percentage of non-Hispanic (or non-Spanish surname for 1970) whites who were never married, by sex, and by year of census (2006 vs. 1970).

First of all, we observe that in 1970, non-Hispanic white people were much less likely to be in the never married category.

Another thing that has changed is the male/female disparity between 1970 and 2006. What do I mean? In 1970, 6.9% of men aged 41-45 were never married, compared to 5.1% of women. This is not a very big difference, and can be entirely explained away if you believe that 2.6% of men are homosexual compared to only 1.1% for women.

In 2006, 16.7% of men aged 41-45 were never married, compared to 10.6% of women. The unmarried gap has increased from 1.8 percentage points to 6.1 percentage points.

This indicates that most omega males born between 1925 and 1930 were able to find wives. But omega males born between 1961 and 1966 wind up never being able to find a wife. In modern times, women would rather become the second trophy wife of an older alpha male or never marry at all, than settle for an omega male.

* * *

An alternative explanation is that men don't need to get married in 2006 because women are willing to give them premarital sex. In 1970, a man had to marry in order to get a woman to put out.

Unmarried male/female ratio by MSA

The 2000 5% PUMS Census data is coded by “metropolitan statistical area.” There is a lot of interesting data to look at, and it’s a lot easier to run this than trying to manually enter super=PUMA codes.

Once again, we are looking only at unmarried non-Hispanic whites age 25-40.

Frequency Distribution
Cells contain: -Row percent -N of cases		sex
		1 Male	2 Female	ROW TOTAL
	0: Not identifiable or not in an MSA	56.0 1,936,288	44.0 1,520,522	100.0 3,456,810
	4: Abilene, TX	53.9 2,934	46.1 2,510	100.0 5,444
	8: Akron, OH	54.7 25,483	45.3 21,068	100.0 46,551
	12: Albany, GA	50.8 1,634	49.2 1,582	100.0 3,216
	16: Albany-Schenectady-Troy, NY	53.7 31,087	46.3 26,835	100.0 57,922
	20: Albuquerque, NM	51.1 15,734	48.9 15,069	100.0 30,803
	22: Alexandria, LA	59.9 3,165	40.1 2,116	100.0 5,281
	24: Allentown-Bethlehem-Easton, PA/NJ	56.9 23,110	43.1 17,486	100.0 40,596
	28: Altoona, PA	54.0 5,007	46.0 4,268	100.0 9,275
	32: Amarillo, TX	48.0 4,677	52.0 5,072	100.0 9,749
	38: Anchorage, AK	56.7 9,944	43.3 7,609	100.0 17,553
	44: Ann Arbor, MI	57.8 19,950	42.2 14,554	100.0 34,504
	45: Anniston, AL	56.9 2,825	43.1 2,136	100.0 4,961
	46: Appleton-Oskosh-Neenah, WI	56.9 15,075	43.1 11,436	100.0 26,511
	48: Asheville, NC	53.1 8,384	46.9 7,393	100.0 15,777
	50: Athens, GA	58.7 5,399	41.3 3,800	100.0 9,199
	52: Atlanta, GA	55.0 123,060	45.0 100,573	100.0 223,633
	56: Atlantic City, NJ	54.1 10,506	45.9 8,905	100.0 19,411
	58: Auburn-Opekika, AL	58.6 3,373	41.4 2,381	100.0 5,754
	60: Augusta-Aiken, GA-SC	51.1 10,147	48.9 9,702	100.0 19,849
	64: Austin, TX	56.4 47,359	43.6 36,672	100.0 84,031
	68: Bakersfield, CA	50.1 10,435	49.9 10,376	100.0 20,811
	72: Baltimore, MD	55.5 76,905	44.5 61,639	100.0 138,544
	74: Barnstable-Yarmouth, MA	50.3 4,359	49.7 4,299	100.0 8,658
	76: Baton Rouge, LA	55.0 15,920	45.0 13,008	100.0 28,928
	84: Beaumont-Port Arthur-Orange,TX	59.6 8,913	40.4 6,031	100.0 14,944
	86: Bellingham, WA	56.3 5,911	43.7 4,582	100.0 10,493
	87: Benton Harbor, MI	55.6 4,965	44.4 3,960	100.0 8,925
	88: Billings, MT	54.2 4,864	45.8 4,110	100.0 8,974
	92: Biloxi-Gulfport, MS	52.8 9,320	47.2 8,344	100.0 17,664
	96: Binghamton, NY	54.1 9,141	45.9 7,766	100.0 16,907
	100: Birmingham, AL	52.8 19,912	47.2 17,824	100.0 37,736
	102: Bloomington, IN	52.8 5,474	47.2 4,895	100.0 10,369
	104: Bloomington-Normal, IL	56.9 5,751	43.1 4,362	100.0 10,113
	108: Boise City, ID	54.8 15,907	45.2 13,128	100.0 29,035
	112: Boston, MA-NH	52.4 180,063	47.6 163,428	100.0 343,491
	115: Bremerton, WA	56.1 7,537	43.9 5,892	100.0 13,429
	116: Bridgeport, CT	55.9 9,055	44.1 7,131	100.0 16,186
	120: Brockton, MA	54.2 9,352	45.8 7,898	100.0 17,250
	124: Brownsville-Harlingen-San Benito, TX	54.7 1,498	45.3 1,242	100.0 2,740
	126: Bryan-College Station, TX	54.2 3,746	45.8 3,165	100.0 6,911
	128: Buffalo-Niagara Falls, NY	54.7 42,759	45.3 35,429	100.0 78,188
	132: Canton, OH	52.3 13,683	47.7 12,489	100.0 26,172
	136: Cedar Rapids, IA	51.1 7,536	48.9 7,224	100.0 14,760
	140: Champaign-Urbana-Rantoul, IL	54.2 5,972	45.8 5,038	100.0 11,010
	144: Charleston-N.Charleston,SC	54.4 13,914	45.6 11,652	100.0 25,566
	152: Charlotte-Gastonia-Rock Hill, NC-SC	56.2 48,227	43.8 37,532	100.0 85,759
	154: Charlottesville, VA	48.7 5,113	51.3 5,391	100.0 10,504
	156: Chattanooga, TN/GA	56.3 13,860	43.7 10,737	100.0 24,597
	160: Chicago, IL	55.2 258,080	44.8 209,158	100.0 467,238
	162: Chico, CA	55.1 6,676	44.9 5,438	100.0 12,114
	164: Cincinnati-Hamilton, OH/KY/IN	54.2 53,444	45.8 45,148	100.0 98,592
	166: Clarksville- Hopkinsville, TN/KY	59.5 4,056	40.5 2,762	100.0 6,818
	168: Cleveland, OH	54.9 77,920	45.1 64,097	100.0 142,017
	172: Colorado Springs, CO	55.7 16,793	44.3 13,374	100.0 30,167
	174: Columbia, MO	52.6 5,436	47.4 4,904	100.0 10,340
	176: Columbia, SC	58.0 15,333	42.0 11,089	100.0 26,422
	180: Columbus, GA/AL	57.4 3,555	42.6 2,635	100.0 6,190
	184: Columbus, OH	54.5 58,121	45.5 48,575	100.0 106,696
	188: Corpus Christi, TX	60.2 4,809	39.8 3,175	100.0 7,984
	192: Dallas-Fort Worth, TX	55.3 143,045	44.7 115,769	100.0 258,814
	193: Danbury, CT	56.1 5,853	43.9 4,587	100.0 10,440
	195: Danville, VA	62.2 2,757	37.8 1,677	100.0 4,434
	196: Davenport, IA-Rock Island -Moline, IL	54.5 9,576	45.5 7,997	100.0 17,573
200: Dayton-Springfield, OH	53.8 32,022	46.2 27,464	100.0 59,486
202: Daytona Beach, FL	55.8 14,806	44.2 11,729	100.0 26,535
203: Decatur, AL	59.1 4,059	40.9 2,811	100.0 6,870
204: Decatur, IL	52.4 3,139	47.6 2,850	100.0 5,989
208: Denver-Boulder, CO	56.0 97,527	44.0 76,608	100.0 174,135
212: Des Moines, IA	51.9 14,949	48.1 13,867	100.0 28,816
216: Detroit, MI	55.9 151,190	44.1 119,198	100.0 270,388
218: Dothan, AL	55.2 3,539	44.8 2,873	100.0 6,412
219: Dover, DE	50.9 3,471	49.1 3,342	100.0 6,813
224: Duluth-Superior, MN/WI	54.4 7,149	45.6 5,987	100.0 13,136
228: Dutchess Co., NY	53.4 8,844	46.6 7,727	100.0 16,571
229: Eau Claire, WI	60.6 6,130	39.4 3,993	100.0 10,123
231: El Paso, TX	55.8 4,311	44.2 3,412	100.0 7,723
232: Elkhart-Goshen, IN	55.6 5,499	44.4 4,399	100.0 9,898
236: Erie, PA	51.7 10,155	48.3 9,493	100.0 19,648
240: Eugene-Springfield, OR	53.7 13,293	46.3 11,469	100.0 24,762
244: Evansville, IN/KY	54.0 9,217	46.0 7,858	100.0 17,075
252: Fargo-Morehead, ND/MN	55.2 5,804	44.8 4,714	100.0 10,518
256: Fayetteville, NC	61.9 7,066	38.1 4,340	100.0 11,406
258: Fayetteville-Springdale, AR	58.9 10,592	41.1 7,404	100.0 17,996
260: Fitchburg-Leominster, MA	53.4 5,754	46.6 5,024	100.0 10,778
262: Flagstaff, AZ-UT	55.5 3,431	44.5 2,746	100.0 6,177
264: Flint, MI	56.6 8,813	43.4 6,744	100.0 15,557
265: Florence, AL	56.7 3,955	43.3 3,023	100.0 6,978
267: Fort Collins-Loveland, CO	58.1 10,087	41.9 7,276	100.0 17,363
268: Fort Lauderdale-Hollywood-Pompano Beach, FL	55.8 51,041	44.2 40,393	100.0 91,434
270: Fort Myers-Cape Coral, FL	55.2 12,635	44.8 10,264	100.0 22,899
271: Fort Pierce, FL	55.4 8,207	44.6 6,604	100.0 14,811
272: Fort Smith, AR/OK	51.9 5,256	48.1 4,879	100.0 10,135
275: Fort Walton Beach, FL	60.1 6,038	39.9 4,002	100.0 10,040
276: Fort Wayne, IN	53.4 15,679	46.6 13,666	100.0 29,345
284: Fresno, CA	48.9 13,302	51.1 13,910	100.0 27,212
288: Gadsden, AL	61.1 3,090	38.9 1,969	100.0 5,059
290: Gainesville, FL	58.1 8,366	41.9 6,038	100.0 14,404
292: Galveston-Texas City, TX	55.6 6,332	44.4 5,066	100.0 11,398
297: Glens Falls, NY	52.7 4,918	47.3 4,413	100.0 9,331
298: Goldsboro, NC	54.8 2,317	45.2 1,913	100.0 4,230
300: Grand Rapids, MI	54.7 31,221	45.3 25,879	100.0 57,100
301: Grand Junction, CO	56.0 3,563	44.0 2,795	100.0 6,358
306: Greeley, CO	56.0 4,423	44.0 3,469	100.0 7,892
308: Green Bay, WI	56.1 10,360	43.9 8,106	100.0 18,466
312: Greensboro-Winston Salem-High Point, NC	55.6 35,680	44.4 28,461	100.0 64,141
315: Greenville, NC	52.2 3,541	47.8 3,239	100.0 6,780
316: Greenville-Spartanburg-Anderson SC	55.3 22,227	44.7 17,964	100.0 40,191
318: Hagerstown, MD	50.4 4,034	49.6 3,969	100.0 8,003
320: Hamilton-Middleton, OH	53.8 11,326	46.2 9,730	100.0 21,056
324: Harrisburg-Lebanon--Carlisle, PA	52.6 21,195	47.4 19,127	100.0 40,322
328: Hartford-Bristol-Middleton- New Britain, CT	55.0 23,664	45.0 19,373	100.0 43,037
329: Hickory-Morgantown, NC	57.5 12,006	42.5 8,892	100.0 20,898
330: Hattiesburg, MS	50.7 2,934	49.3 2,858	100.0 5,792
332: Honolulu, HI	62.3 11,505	37.7 6,970	100.0 18,475
335: Houma-Thibodoux, LA	54.6 2,819	45.4 2,341	100.0 5,160
336: Houston-Brazoria, TX	54.2 89,544	45.8 75,722	100.0 165,266
344: Huntsville, AL	57.3 10,949	42.7 8,165	100.0 19,114
348: Indianapolis, IN	53.1 59,909	46.9 52,827	100.0 112,736
350: Iowa City, IA	58.4 5,326	41.6 3,799	100.0 9,125
352: Jackson, MI	53.1 5,528	46.9 4,886	100.0 10,414
356: Jackson, MS	50.7 8,046	49.3 7,817	100.0 15,863
358: Jackson, TN	53.0 2,182	47.0 1,934	100.0 4,116
359: Jacksonville, FL	54.0 34,306	46.0 29,244	100.0 63,550
360: Jacksonville, NC	67.1 3,849	32.9 1,886	100.0 5,735
361: Jamestown-Dunkirk, NY	52.9 4,500	47.1 4,008	100.0 8,508
362: Janesville-Beloit, WI	52.2 5,643	47.8 5,175	100.0 10,818
366: Johnson City-Kingsport--Bristol, TN/VA	54.3 11,412	45.7 9,619	100.0 21,031
368: Johnstown, PA	62.8 9,037	37.2 5,352	100.0 14,389
371: Joplin, MO	50.9 4,391	49.1 4,238	100.0 8,629
372: Kalamazoo-Portage, MI	52.4 14,992	47.6 13,602	100.0 28,594
374: Kankakee, IL	50.9 2,891	49.1 2,784	100.0 5,675
376: Kansas City, MO-KS	54.1 59,175	45.9 50,267	100.0 109,442
380: Kenosha, WI	52.0 5,498	48.0 5,074	100.0 10,572
381: Kileen-Temple, TX	60.3 7,413	39.7 4,883	100.0 12,296
384: Knoxville, TN	55.5 21,978	44.5 17,629	100.0 39,607
385: Kokomo, IN	54.7 3,401	45.3 2,812	100.0 6,213
387: LaCrosse, WI	57.6 4,568	42.4 3,357	100.0 7,925
388: Lafayette, LA	55.3 7,760	44.7 6,278	100.0 14,038
392: Lafayette-W. Lafayette, IN	55.9 6,614	44.1 5,215	100.0 11,829
396: Lake Charles, LA	52.6 4,626	47.4 4,163	100.0 8,789
398: Lakeland-Winterhaven, FL	54.9 13,451	45.1 11,034	100.0 24,485
400: Lancaster, PA	54.6 14,347	45.4 11,933	100.0 26,280
404: Lansing-E. Lansing, MI	51.8 15,359	48.2 14,297	100.0 29,656
408: Laredo, TX	60.2 390	39.8 258	100.0 648
410: Las Cruces, NM	56.8 2,350	43.2 1,785	100.0 4,135
412: Las Vegas, NV	57.9 50,734	42.1 36,817	100.0 87,551
428: Lexington-Fayette, KY	57.3 12,470	42.7 9,288	100.0 21,758
432: Lima, OH	56.2 5,213	43.8 4,068	100.0 9,281
436: Lincoln, NE	57.2 11,418	42.8 8,552	100.0 19,970
440: Little Rock--North Little Rock, AR	53.8 16,643	46.2 14,311	100.0 30,954
442: Longview-Marshall, TX	54.8 3,385	45.2 2,797	100.0 6,182
448: Los Angeles-Long Beach, CA	56.4 284,830	43.6 219,926	100.0 504,756
452: Louisville, KY/IN	53.7 34,836	46.3 30,042	100.0 64,878
460: Lubbock, TX	51.8 5,620	48.2 5,219	100.0 10,839
464: Lynchburg, VA	53.4 5,641	46.6 4,929	100.0 10,570
468: Macon-Warner Robins, GA	57.7 7,521	42.3 5,518	100.0 13,039
472: Madison, WI	52.6 20,628	47.4 18,596	100.0 39,224
476: Manchester, NH	57.3 6,295	42.7 4,686	100.0 10,981
480: Mansfield, OH	62.8 5,178	37.2 3,070	100.0 8,248
488: McAllen-Edinburg-Pharr-Mission, TX	56.6 1,743	43.4 1,338	100.0 3,081
489: Medford, OR	52.3 5,306	47.7 4,844	100.0 10,150
490: Melbourne-Titusville-Cocoa-Palm Bay, FL	57.8 16,491	42.2 12,059	100.0 28,550
492: Memphis, TN/AR/MS	55.8 23,104	44.2 18,308	100.0 41,412
494: Merced, CA	52.3 3,070	47.7 2,803	100.0 5,873
500: Miami-Hialeah, FL	59.1 26,566	40.9 18,384	100.0 44,950
508: Milwaukee, WI	55.2 51,945	44.8 42,178	100.0 94,123
512: Minneapolis-St. Paul, MN	53.1 123,593	46.9 109,322	100.0 232,915
516: Mobile, AL	53.8 13,598	46.2 11,666	100.0 25,264
517: Modesto, CA	52.5 10,155	47.5 9,195	100.0 19,350
519: Monmouth-Ocean, NJ	54.1 33,649	45.9 28,500	100.0 62,149
520: Monroe, LA	47.8 3,212	52.2 3,513	100.0 6,725
524: Montgomery, AL	58.3 7,997	41.7 5,711	100.0 13,708
528: Muncie, IN	50.6 4,356	49.4 4,252	100.0 8,608
533: Myrtle Beach, SC	56.6 7,526	43.4 5,782	100.0 13,308
534: Naples, FL	52.0 5,929	48.0 5,482	100.0 11,411
535: Nashua, NH	54.9 5,798	45.1 4,771	100.0 10,569
536: Nashville, TN	53.0 45,858	47.0 40,643	100.0 86,501
540: New Bedford, MA	56.9 6,895	43.1 5,214	100.0 12,109
548: New Haven-Meriden, CT	55.9 13,135	44.1 10,344	100.0 23,479
556: New Orleans, LA	55.0 34,118	45.0 27,863	100.0 61,981
560: New York-Northeastern NJ	54.4 465,152	45.6 390,122	100.0 855,274
566: Newburgh-Middletown, NY	54.1 10,091	45.9 8,568	100.0 18,659
572: Norfolk-VA Beach--Newport News, VA	57.1 42,735	42.9 32,063	100.0 74,798
579: Ocala, FL	52.8 6,804	47.2 6,071	100.0 12,875
580: Odessa, TX	59.3 4,514	40.7 3,094	100.0 7,608
588: Oklahoma City, OK	55.2 28,818	44.8 23,345	100.0 52,163
591: Olympia, WA	53.0 7,349	47.0 6,514	100.0 13,863
592: Omaha, NE/IA	57.0 24,095	43.0 18,191	100.0 42,286
596: Orlando, FL	57.7 58,977	42.3 43,311	100.0 102,288
601: Panama City, FL	58.4 5,678	41.6 4,047	100.0 9,725
608: Pensacola, FL	56.5 14,196	43.5 10,913	100.0 25,109
612: Peoria, IL	52.8 10,558	47.2 9,420	100.0 19,978
616: Philadelphia, PA/NJ	54.6 161,697	45.4 134,712	100.0 296,409
620: Phoenix, AZ	55.3 104,586	44.7 84,660	100.0 189,246
628: Pittsburgh, PA	54.1 84,793	45.9 72,021	100.0 156,814
640: Portland, ME	50.1 11,573	49.9 11,533	100.0 23,106
644: Portland, OR-WA	53.7 74,892	46.3 64,540	100.0 139,432
648: Providence-Fall River-Pawtucket, MA/RI	50.7 39,807	49.3 38,711	100.0 78,518
652: Provo-Orem, UT	53.9 8,070	46.1 6,901	100.0 14,971
656: Pueblo, CO	54.4 3,014	45.6 2,526	100.0 5,540
658: Punta Gorda, FL	57.3 3,635	42.7 2,704	100.0 6,339
660: Racine, WI	50.5 5,328	49.5 5,226	100.0 10,554
664: Raleigh-Durham, NC	55.8 40,604	44.2 32,174	100.0 72,778
668: Reading, PA	54.2 11,979	45.8 10,142	100.0 22,121
669: Redding, CA	49.4 4,861	50.6 4,974	100.0 9,835
672: Reno, NV	56.4 12,879	43.6 9,975	100.0 22,854
674: Richland-Kennewick-Pasco, WA	53.4 4,878	46.6 4,259	100.0 9,137
676: Richmond-Petersburg, VA	53.9 26,793	46.1 22,876	100.0 49,669
678: Riverside-San Bernadino, CA	54.5 57,983	45.5 48,419	100.0 106,402
680: Roanoke, VA	53.9 8,704	46.1 7,451	100.0 16,155
682: Rochester, MN	53.4 4,127	46.6 3,595	100.0 7,722
684: Rochester, NY	54.8 37,181	45.2 30,649	100.0 67,830
688: Rockford, IL	54.5 10,963	45.5 9,141	100.0 20,104
689: Rocky Mount, NC	54.2 2,596	45.8 2,191	100.0 4,787
692: Sacramento, CA	52.0 47,446	48.0 43,876	100.0 91,322
696: Saginaw-Bay City-Midland, MI	54.7 13,042	45.3 10,800	100.0 23,842
698: St. Cloud, MN	61.0 7,000	39.0 4,471	100.0 11,471
700: St. Joseph, MO	58.4 4,163	41.6 2,971	100.0 7,134
704: St. Louis, MO-IL	54.6 84,673	45.4 70,523	100.0 155,196
708: Salem, OR	57.7 9,806	42.3 7,176	100.0 16,982
712: Salinas-Sea Side-Monterey, CA	54.4 6,056	45.6 5,069	100.0 11,125
716: Salt Lake City-Ogden, UT	56.5 42,524	43.5 32,695	100.0 75,219
724: San Antonio, TX	53.0 25,647	47.0 22,741	100.0 48,388
732: San Diego, CA	57.3 93,588	42.7 69,661	100.0 163,249
736: San Francisco-Oakland-Vallejo, CA	55.3 160,228	44.7 129,558	100.0 289,786
740: San Jose, CA	59.0 50,250	41.0 34,957	100.0 85,207
746: San Luis Obispo-Atascad-P Robles, CA	55.0 7,047	45.0 5,774	100.0 12,821
747: Santa Barbara-Santa Maria-Lompoc, CA	51.5 9,925	48.5 9,341	100.0 19,266
748: Santa Cruz, CA	55.4 9,821	44.6 7,899	100.0 17,720
749: Santa Fe, NM	51.9 3,118	48.1 2,887	100.0 6,005
750: Santa Rosa-Petaluma, CA	51.9 14,590	48.1 13,525	100.0 28,115
751: Sarasota, FL	53.6 16,405	46.4 14,197	100.0 30,602
752: Savannah, GA	57.0 6,384	43.0 4,814	100.0 11,198
756: Scranton-Wilkes-Barre, PA	54.4 25,670	45.6 21,529	100.0 47,199
760: Seattle-Everett, WA	56.2 112,822	43.8 87,843	100.0 200,665
761: Sharon, PA	55.7 4,000	44.3 3,181	100.0 7,181
762: Sheboygan, WI	51.8 3,964	48.2 3,687	100.0 7,651
768: Shreveport, LA	52.1 8,024	47.9 7,368	100.0 15,392
772: Sioux City, IA/NE	52.3 3,378	47.7 3,083	100.0 6,461
776: Sioux Falls, SD	51.3 5,630	48.7 5,350	100.0 10,980
780: South Bend-Mishawaka, IN	56.3 9,337	43.7 7,257	100.0 16,594
784: Spokane, WA	54.7 17,149	45.3 14,200	100.0 31,349
788: Springfield, IL	56.1 5,198	43.9 4,062	100.0 9,260
792: Springfield, MO	55.8 13,014	44.2 10,304	100.0 23,318
800: Springfield-Holyoke-Chicopee, MA	52.4 21,136	47.6 19,170	100.0 40,306
804: Stamford, CT	54.5 11,898	45.5 9,930	100.0 21,828
805: State College, PA	61.4 5,477	38.6 3,439	100.0 8,916
812: Stockton, CA	52.1 10,354	47.9 9,536	100.0 19,890
814: Sumter, SC	65.2 2,019	34.8 1,076	100.0 3,095
816: Syracuse, NY	54.3 27,873	45.7 23,442	100.0 51,315
820: Tacoma, WA	54.7 24,134	45.3 19,970	100.0 44,104
824: Tallahassee, FL	56.7 8,101	43.3 6,198	100.0 14,299
828: Tampa-St. Petersburg-Clearwater, FL	54.3 83,716	45.7 70,564	100.0 154,280
832: Terre Haute, IN	55.5 5,041	44.5 4,049	100.0 9,090
840: Toledo, OH/MI	54.2 21,125	45.8 17,834	100.0 38,959
844: Topeka, KS	50.0 5,423	50.0 5,431	100.0 10,854
848: Trenton, NJ	49.4 8,357	50.6 8,553	100.0 16,910
852: Tucson, AZ	52.7 23,557	47.3 21,116	100.0 44,673
856: Tulsa, OK	55.5 20,829	44.5 16,688	100.0 37,517
860: Tuscaloosa, AL	56.6 4,372	43.4 3,359	100.0 7,731
864: Tyler, TX	54.1 3,596	45.9 3,055	100.0 6,651
868: Utica-Rome, NY	55.1 11,522	44.9 9,385	100.0 20,907
873: Ventura-Oxnard-Simi Valley, CA	52.4 16,955	47.6 15,413	100.0 32,368
876: Vineland-Milville-Bridgetown, NJ	55.2 3,883	44.8 3,147	100.0 7,030
878: Visalia-Tulare-Porterville, CA	51.4 4,863	48.6 4,607	100.0 9,470
880: Waco, TX	50.0 3,748	50.0 3,754	100.0 7,502
884: Washington, DC/MD/VA	53.8 135,796	46.2 116,642	100.0 252,438
888: Waterbury, CT	56.2 3,622	43.8 2,828	100.0 6,450
892: Waterloo-Cedar Falls, IA	57.6 4,251	42.4 3,131	100.0 7,382
894: Wausau, WI	58.3 5,106	41.7 3,653	100.0 8,759
896: West Palm Beach-Boca Raton-Delray Beach, FL	54.5 30,663	45.5 25,562	100.0 56,225
904: Wichita, KS	57.9 17,659	42.1 12,852	100.0 30,511
908: Wichita Falls, TX	52.9 3,181	47.1 2,836	100.0 6,017
914: Williamsport, PA	52.5 4,266	47.5 3,853	100.0 8,119
916: Wilmington, DE/NJ/MD	55.6 16,523	44.4 13,200	100.0 29,723
920: Wilmington, NC	55.2 8,265	44.8 6,701	100.0 14,966
924: Worcester, MA	50.8 11,154	49.2 10,805	100.0 21,959
926: Yakima, WA	56.8 4,341	43.2 3,303	100.0 7,644
927: Yolo, CA	48.3 4,054	51.7 4,338	100.0 8,392
928: York, PA	56.7 13,802	43.3 10,527	100.0 24,329
932: Youngstown-Warren, OH-PA	55.2 20,352	44.8 16,541	100.0 36,893
934: Yuba City, CA	51.9 3,150	48.1 2,914	100.0 6,064
936: Yuma, AZ	55.3 2,047	44.7 1,656	100.0 3,703
COL TOTAL	55.1 8,503,079	44.9 6,930,217	100.0 15,433,296

Unmarried male/female ratio by specific geographic areas

Using the methodology described in my state post. For each area, I give the description, super-PUMA codes, the male/female ratio, and the person-weighted N. Data is from the

The Phoenix, AZ area and Buffalo, NY are very close to the nationwide ratio of 1.227.

Manhattan is pretty good for single men.

The San Francisco/Silicon Valley area is a horrible place for single men. Don’t move there if you are a single beta male and want to have any hope of finding a decent girlfriend.

Entire USA ratio=1.227 N=15,433,296
Manhattan (36101-36103) ratio=1.07 N=172,997
Buffalo (36052) ratio=1.23 N=35,721
Maricopa County (Phoenix metro area), AZ (4301-4306) ratio=1.24 N=189,246
San Francisco, city of (6130) ratio=1.39 N=101,269
San Mateo country (6140) ratio=1.19 N=35,832
Santa Clara county (6161-6163) ratio=1.44 N=85,207

Unmarried male/female ratio by state

A NEW METHODOLOGY

The 2000 data has the largest sample size. Allegedly 5% of the U.S. population was surveyed in detail. Each person in the survey has a "person weight" which is supposed to represent the total number of people in the population that they represent. I seem to get a lower male/female ratio when I don't use the person weight, which means that the actual responses are biased in favor of less males responding. I hope the Census people know what they are doing, being that they are government employees.

We are looking at non-Hispanic whites, age 25-40, who are unmarried.

BY STATE

It’s easy to prepare a chart of the male/female ratio by state. It’s not as informative as looking at smaller geographic divisions, but it still tells us some useful stuff.

For the nation as a whole, the unmarried male/female ratio is 1.227. But there are considerable variations by state.

States most favorable for single males:

New Mexico, Rhode Island

States least favorable for single males:

Hawaii, North Dakota, Nevada, Alaska

2000 5% PUMS and Person Weight
Cells contain: -Row percent -N of cases		sex
		1 Male	2 Female	ROW TOTAL
statefip	1: Alabama	56.4 112,964	43.6 87,183	100.0 200,147
	2: Alaska	57.0 20,664	43.0 15,585	100.0 36,249
	4: Arizona	54.7 151,281	45.3 125,128	100.0 276,409
	5: Arkansas	55.4 71,173	44.6 57,322	100.0 128,495
	6: California	55.3 858,576	44.7 695,322	100.0 1,553,898
	8: Colorado	56.6 171,107	43.4 130,971	100.0 302,078
	9: Connecticut	54.8 117,986	45.2 97,423	100.0 215,409
	10: Delaware	54.2 23,866	45.8 20,205	100.0 44,071
	11: District of Columbia	52.6 19,007	47.4 17,110	100.0 36,117
	12: Florida	55.8 459,691	44.2 363,649	100.0 823,340
	13: Georgia	56.0 225,264	44.0 177,114	100.0 402,378
	15: Hawaii	59.0 16,852	41.0 11,697	100.0 28,549
	16: Idaho	55.5 39,104	44.5 31,326	100.0 70,430
	17: Illinois	55.0 378,141	45.0 309,718	100.0 687,859
	18: Indiana	54.9 211,028	45.1 173,187	100.0 384,215
	19: Iowa	55.2 100,080	44.8 81,215	100.0 181,295
	20: Kansas	55.7 80,322	44.3 63,991	100.0 144,313
	21: Kentucky	53.6 137,650	46.4 119,047	100.0 256,697
	22: Louisiana	54.7 107,980	45.3 89,551	100.0 197,531
	23: Maine	53.2 51,605	46.8 45,449	100.0 97,054
	24: Maryland	54.6 141,391	45.4 117,651	100.0 259,042
	25: Massachusetts	52.5 270,296	47.5 244,710	100.0 515,006
	26: Michigan	55.5 341,278	44.5 273,719	100.0 614,997
	27: Minnesota	55.0 192,922	45.0 157,955	100.0 350,877
	28: Mississippi	54.9 58,773	45.1 48,353	100.0 107,126
	29: Missouri	55.2 188,245	44.8 152,656	100.0 340,901
	30: Montana	56.2 30,725	43.8 23,975	100.0 54,700
	31: Nebraska	56.8 58,938	43.2 44,808	100.0 103,746
	32: Nevada	57.3 71,386	42.7 53,277	100.0 124,663
	33: New Hampshire	54.8 51,144	45.2 42,213	100.0 93,357
	34: New Jersey	54.6 240,044	45.4 199,969	100.0 440,013
	35: New Mexico	51.9 30,834	48.1 28,576	100.0 59,410
	36: New York	54.3 573,452	45.7 481,817	100.0 1,055,269
	37: North Carolina	56.4 228,912	43.6 177,022	100.0 405,934
	38: North Dakota	59.1 23,932	40.9 16,548	100.0 40,480
	39: Ohio	54.9 400,509	45.1 329,067	100.0 729,576
	40: Oklahoma	55.0 91,521	45.0 74,956	100.0 166,477
	41: Oregon	54.8 129,037	45.2 106,637	100.0 235,674
	42: Pennsylvania	54.9 422,953	45.1 347,397	100.0 770,350
	44: Rhode island	51.5 40,492	48.5 38,104	100.0 78,596
	45: South Carolina	56.3 102,680	43.7 79,568	100.0 182,248
	46: South Dakota	56.2 23,196	43.8 18,083	100.0 41,279
	47: Tennessee	55.4 183,914	44.6 147,996	100.0 331,910
	48: Texas	55.0 444,228	45.0 364,178	100.0 808,406
	49: Utah	55.7 61,209	44.3 48,776	100.0 109,985
	50: Vermont	53.3 25,496	46.7 22,381	100.0 47,877
	51: Virginia	55.3 213,812	44.7 173,146	100.0 386,958
	53: Washington	55.4 224,070	44.6 180,517	100.0 404,587
	54: West Virginia	55.0 63,451	45.0 52,019	100.0 115,470
	55: Wisconsin	56.1 202,345	43.9 158,331	100.0 360,676
	56: Wyoming	56.3 17,553	43.7 13,619	100.0 31,172
	COL TOTAL	55.1 8,503,079	44.9 6,930,217	100.0 15,433,296

The unmarried male/female ratio project

The ratio of unmarried men to women is of interest to everyone who’s single and looking, and even those who are married but are interested in sociology and demographics, however the resources available on the web (such as the Richard Florida map) are very poor. People make the mistake of grouping everyone together, which results in useless data.

To do these calculations, I will use the American Community Survey 2006 data, available for free (thanks ot the University of Minnesota) at the IPUMS-USA website. I will then use the US Census PUMA maps to pull interesting geographic areas out of the data. The ACS only surveys 1% of the population, thus the results are subject to sample error.

I believe that a good demographic to examine is non-Hispanic white unmarried people between the ages of 25-40. Because interracial marriage is relatively rare, most single people are only interested in how many single people of the opposite sex there are from their own race.

The age range 25-40 captures the post-college years. People in this age range aren’t affected by the fact that there’s a big surplus of widowed female octogenarians.

“Unmarried” includes the following census categories: divorced, widowed, never married. The following categories are excluded: married spouse present, married spouse absent, separated.

Now, I introduced this topic with some USA-wide charts so that you can see the big picture. You will notice that even in the pre-marriage years, there is a surplus of males. This is because more boy babies are born than girl babies.

In this introductory post, I also include separate charts for blacks, Asians, and Hispanics.

Black men have a much more favorable male/female ratio than men of other races. I’m not sure why. Possibly became blacks have a more even birth ratio, because black men die early, because black men are marrying white women, or because black men are being undercounted by the census.

Hispanic men face the worst ratio. This is probably due to the disproportionate number of male illegal immigrants.

In future posts, I will examine the geographic data.

Non-Hispanic White
Cells contain: -Row percent -N of cases		sex
		1 Male	2 Female	ROW TOTAL
age	1: 0-17	51.4 21,705,175	48.6 20,493,062	100.0 42,198,237
	2: 18-20	52.1 4,048,871	47.9 3,719,306	100.0 7,768,177
	3: 21-24	54.1 4,412,950	45.9 3,747,934	100.0 8,160,884
	4: 25-28	55.4 3,073,705	44.6 2,472,222	100.0 5,545,927
	5: 29-32	56.1 2,014,546	43.9 1,574,294	100.0 3,588,840
	6: 33-36	55.0 1,836,492	45.0 1,504,618	100.0 3,341,110
	7: 37-40	53.7 1,789,844	46.3 1,544,026	100.0 3,333,870
	8: 41-45	51.9 2,476,961	48.1 2,296,258	100.0 4,773,219
	9: 45-50	50.4 2,423,458	49.6 2,389,582	100.0 4,813,040
	10: 51-60	45.3 3,627,512	54.7 4,374,329	100.0 8,001,841
	11: 61-70	35.2 1,878,822	64.8 3,451,610	100.0 5,330,432
	12: 71-80	25.7 1,316,544	74.3 3,810,573	100.0 5,127,117
	13: 81-90	21.0 848,826	79.0 3,194,044	100.0 4,042,870
	14: 91-99	17.3 210,036	82.7 1,001,393	100.0 1,211,429
	COL TOTAL	48.2 51,663,742	51.8 55,573,251	100.0 107,236,993

Non-Hispanic Black
Cells contain: -Row percent -N of cases		sex
		1 Male	2 Female	ROW TOTAL
age	1: 0-17	50.9 5,437,647	49.1 5,238,751	100.0 10,676,398
	2: 18-20	51.5 969,045	48.5 911,264	100.0 1,880,309
	3: 21-24	50.1 1,003,621	49.9 998,191	100.0 2,001,812
	4: 25-28	48.8 800,664	51.2 839,181	100.0 1,639,845
	5: 29-32	46.7 563,052	53.3 642,645	100.0 1,205,697
	6: 33-36	44.2 527,441	55.8 665,285	100.0 1,192,726
	7: 37-40	44.0 473,105	56.0 602,729	100.0 1,075,834
	8: 41-45	42.7 592,415	57.3 793,677	100.0 1,386,092
	9: 45-50	42.1 538,845	57.9 741,877	100.0 1,280,722
	10: 51-60	39.0 724,780	61.0 1,135,234	100.0 1,860,014
	11: 61-70	31.0 327,916	69.0 730,938	100.0 1,058,854
	12: 71-80	26.0 194,815	74.0 555,001	100.0 749,816
	13: 81-90	21.3 84,623	78.7 313,231	100.0 397,854
	14: 91-99	15.9 20,035	84.1 105,652	100.0 125,687
	COL TOTAL	46.2 12,258,004	53.8 14,273,656	100.0 26,531,660

Non-Hispanic Asian
Cells contain: -Row percent -N of cases		sex
		1 Male	2 Female	ROW TOTAL
age	1: 0-17	50.8 1,498,088	49.2 1,452,071	100.0 2,950,159
	2: 18-20	50.8 282,141	49.2 273,757	100.0 555,898
	3: 21-24	54.2 356,068	45.8 301,187	100.0 657,255
	4: 25-28	56.7 303,133	43.3 231,079	100.0 534,212
	5: 29-32	58.6 214,206	41.4 151,278	100.0 365,484
	6: 33-36	56.1 141,586	43.9 110,804	100.0 252,390
	7: 37-40	51.2 102,708	48.8 98,004	100.0 200,712
	8: 41-45	46.2 92,933	53.8 108,365	100.0 201,298
	9: 45-50	40.7 72,473	59.3 105,375	100.0 177,848
	10: 51-60	33.4 98,467	66.6 196,537	100.0 295,004
	11: 61-70	24.5 51,214	75.5 157,597	100.0 208,811
	12: 71-80	18.9 34,939	81.1 149,918	100.0 184,857
	13: 81-90	19.1 20,058	80.9 85,213	100.0 105,271
	14: 91-99	17.6 5,017	82.4 23,425	100.0 28,442
	COL TOTAL	48.7 3,273,031	51.3 3,444,610	100.0 6,717,641

Hispanic
Cells contain: -Row percent -N of cases		sex
		1 Male	2 Female	ROW TOTAL
age	1: 0-17	51.0 7,611,162	49.0 7,323,206	100.0 14,934,368
	2: 18-20	55.0 1,141,886	45.0 935,950	100.0 2,077,836
	3: 21-24	59.0 1,323,967	41.0 918,788	100.0 2,242,755
	4: 25-28	61.2 1,104,241	38.8 698,783	100.0 1,803,024
	5: 29-32	60.6 773,527	39.4 502,776	100.0 1,276,303
	6: 33-36	56.2 551,421	43.8 429,351	100.0 980,772
	7: 37-40	53.3 443,220	46.7 388,156	100.0 831,376
	8: 41-45	49.7 425,124	50.3 430,887	100.0 856,011
	9: 45-50	45.0 321,689	55.0 392,526	100.0 714,215
	10: 51-60	42.0 419,489	58.0 578,321	100.0 997,810
	11: 61-70	30.0 174,577	70.0 406,487	100.0 581,064
	12: 71-80	25.4 120,128	74.6 351,939	100.0 472,067
	13: 81-90	21.9 51,779	78.1 184,560	100.0 236,339
	14: 91-99	15.9 9,728	84.1 51,287	100.0 61,015
	COL TOTAL	51.6 14,471,938	48.4 13,593,017	100.0 28,064,955