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NOTES ON THIS PAGE 1996 CRIME STATISTICS MAIN PAGE THUNDER & LIGHTNING NEWS SERVICE HOME PAGE FBI HOME PAGE

CRIME IN THE NINETIES BIG CITY PROPERTY CRIME RATES 1990 – 1996

Rank	City & State	1996 Population (est)	1996 Number of Property Crimes	1996 Property Crime Rate (per 100,000 residents)	Percent Change, Property Crime Rate, 1995 – 1996	Percent Change, Property Crime Rate, 1992 – 1996	Percent Change, Property Crime Rate, 1990 – 1996
1	ORANGE, CA	118,445	3,523	2,974.4	-19.8%	-46.5%	-51.3%
2	ANN ARBOR, MI	109,939	4,287	3,899.4	-13.7%	-24.0%	-50.5%
3	MESQUITE, TX	117,795	6,014	5,105.5	-11.7%	-28.9%	-48.5%
4	NEW YORK, NY	7,339,594	284,746	3,879.6	-13.3%	-38.7%	-47.0%
5	FORT WORTH, TX	470,254	33,918	7,212.7	-3.3%	-40.5%	-45.5%
6	SAN DIEGO, CA	1,168,364	51,425	4,401.5	-4.1%	-34.6%	-45.4%
7	WICHITA FALLS, TX	101,755	5,826	5,725.5	-7.3%	-26.4%	-44.4%
8	FONTANA, CA	105,211	4,083	3,880.8	-14.8%	-42.3%	-44.4%
9	SANTA ANA, CA	294,963	10,982	3,723.2	-14.2%	-36.4%	-44.3%
10	GARDEN GROVE, CA	150,062	5,632	3,753.1	-18.1%	-38.4%	-42.8%
11	PASADENA, TX	134,568	6,375	4,737.4	8.2%	-30.8%	-40.3%
12	IRVING, TX	170,960	8,679	5,076.6	-4.8%	-26.1%	-40.1%
13	PITTSBURGH, PA	354,308	15,916	4,492.1	-12.8%	-35.9%	-39.6%
14	DALLAS, TX	1,060,585	84,121	7,931.6	0.0%	-23.4%	-39.4%
15	FULLERTON, CA	118,524	4,761	4,016.9	-21.4%	-40.2%	-38.9%
16	EL MONTE, CA	106,149	3,315	3,123.0	-12.9%	-33.2%	-37.0%
17	GRAND PRAIRIE, TX	112,930	5,726	5,070.4	-2.2%	-23.9%	-36.9%
18	WEST COVINA, CA	104,766	4,400	4,199.8	-10.2%	-28.1%	-36.9%
19	LONG BEACH, CA	440,023	21,239	4,826.8	-15.8%	-24.3%	-36.6%
20	BRIDGEPORT, CT	133,015	8,934	6,716.5	1.5%	-28.7%	-36.1%
21	HOUSTON, TX	1,772,143	112,873	6,369.3	1.0%	-12.5%	-36.0%
22	EL PASO, TX	602,951	39,996	6,633.4	6.6%	-16.6%	-35.3%
23	AUSTIN, TX	537,484	38,457	7,155.0	-2.8%	-30.9%	-35.0%
24	MADISON, WI	197,572	8,324	4,213.1	-4.7%	-23.6%	-33.0%
25	ESCONDIDO, CA	118,003	6,038	5,116.8	-15.9%	-24.0%	-32.8%
26	RIVERSIDE, CA	245,081	12,324	5,028.5	-23.1%	-28.8%	-32.6%
27	IRVINE, CA	127,410	3,816	2,995.1	-15.9%	-28.6%	-32.2%
28	ANAHEIM, CA	286,146	12,599	4,403.0	-16.3%	-28.4%	-32.2%
29	BOSTON, MA	552,519	35,557	6,435.4	-17.0%	-17.6%	-32.1%
30	OCEANSIDE, CA	148,308	5,958	4,017.3	-2.3%	-30.8%	-32.0%
31	SAN ANTONIO, TX	1,021,477	82,969	8,122.5	8.6%	-22.5%	-31.5%
32	PATERSON, NJ	139,759	6,814	4,875.5	-11.8%	-16.8%	-31.4%
33	CAMBRIDGE, MA	100,725	4,319	4,287.9	-10.5%	-19.5%	-31.3%
34	INGLEWOOD, CA	111,650	4,298	3,849.5	-11.9%	-36.6%	-30.5%
35	STOCKTON, CA	225,799	16,286	7,212.6	-8.3%	-22.7%	-29.7%
36	HARTFORD, CT	124,223	11,056	8,900.1	-20.9%	-31.0%	-28.6%
37	SIMI VALLEY, CA	108,469	2,245	2,069.7	-18.0%	-33.6%	-27.9%
38	GARLAND, TX	201,336	8,785	4,363.4	-17.4%	-29.7%	-27.8%
39	LOS ANGELES, CA	3,498,139	172,420	4,928.9	-12.7%	-28.6%	-27.7%
40	MIAMI, FL	384,976	40,928	10,631.3	-12.9%	-22.7%	-27.5%
41	NORFOLK, VA	245,956	16,522	6,717.5	-10.0%	-9.2%	-26.7%
42	SANTA CLARITA, CA	125,435	2,659	2,119.8	-19.0%	-18.1%	-26.4%
43	TULSA, OK	379,798	22,945	6,041.4	-2.9%	-12.1%	-26.3%
44	HUNTINGTON BEACH, CA	191,911	6,694	3,488.1	-11.9%	-14.2%	-24.8%
45	AMHERST TOWN, NY	107,331	2,651	2,469.9	-4.1%	-14.6%	-23.8%
46	CHATTANOOGA, TN	156,524	12,543	8,013.5	0.6%	0.4%	-23.7%
47	PASADENA, CA	136,077	6,245	4,589.3	-22.4%	-23.1%	-23.6%
48	BEAUMONT, TX	119,715	9,057	7,565.5	-10.9%	-23.1%	-23.2%
49	GLENDALE, CA	181,019	6,245	3,449.9	-14.0%	-14.9%	-22.6%
50	JERSEY CITY, NJ	228,424	12,913	5,653.1	-6.4%	-18.3%	-22.5%
51	STERLING HEIGHTS, MI	120,737	4,339	3,593.8	5.5%	1.3%	-22.5%
52	YONKERS, NY	183,650	7,106	3,869.3	-1.9%	-7.4%	-22.4%
53	LIVONIA, MI	101,450	3,183	3,137.5	-7.3%	-23.8%	-22.4%
54	RENO, NV	159,559	9,731	6,098.7	-5.7%	-16.0%	-22.2%
55	LITTLE ROCK, AR	182,799	18,259	9,988.6	-2.4%	-17.9%	-22.1%
56	PROVIDENCE, RI	149,805	12,081	8,064.5	-5.4%	-8.0%	-22.0%
57	ST. PETERSBURG, FL	246,229	19,115	7,763.1	6.1%	-3.5%	-21.9%
58	CHARLOTTE-MECKLENBURG, NC	554,070	44,603	8,050.1	2.2%	-21.7%	-21.8%
59	CHULA VISTA, CA	151,377	7,728	5,105.1	-4.1%	-21.6%	-21.7%
60	KNOXVILLE, TN	174,054	9,240	5,308.7	-13.0%	-25.5%	-21.3%
61	SAN FRANCISCO, CA	745,127	46,706	6,268.2	-6.6%	-25.1%	-21.2%
62	LAREDO, TX	156,032	10,200	6,537.1	10.4%	-8.2%	-21.1%
63	GLENDALE, AZ	183,029	12,259	6,697.8	-17.0%	-9.0%	-20.9%
64	NEWARK, NJ	261,909	25,676	9,803.4	-15.0%	-11.9%	-20.8%
65	SALINAS, CA	121,517	6,195	5,098.1	-10.0%	-21.1%	-20.6%
66	POMONA, CA	145,916	6,252	4,284.7	-8.2%	-25.4%	-20.6%
67	SAN JOSE, CA	830,374	28,212	3,397.5	-5.1%	-19.8%	-20.4%
68	NEW HAVEN, CT	119,566	12,420	10,387.6	-4.0%	-5.1%	-20.4%
69	TUCSON, AZ	472,385	41,667	8,820.6	-19.5%	-6.1%	-19.6%
70	ARLINGTON, TX	298,632	18,834	6,306.8	3.4%	-18.4%	-19.2%
71	VIRGINIA BEACH, VA	439,851	19,744	4,488.8	1.3%	-9.0%	-19.1%
72	MIDLAND, TX	100,087	4,589	4,585.0	2.9%	-17.2%	-19.1%
73	COLORADO SPRINGS, CO	331,020	18,928	5,718.1	-9.0%	-9.2%	-18.9%
74	FORT WAYNE, IN	186,196	12,897	6,926.6	8.3%	-17.6%	-18.6%
75	ONTARIO, CA	136,742	7,482	5,471.6	-16.1%	-13.9%	-18.5%
76	STAMFORD, CT	107,165	4,514	4,212.2	-18.5%	-17.1%	-18.5%
77	WATERBURY, CT	103,490	7,295	7,049.0	-11.8%	-8.9%	-18.4%
78	RICHMOND, VA	204,881	16,388	7,998.8	-7.1%	-12.5%	-18.0%
79	HAMPTON, VA	142,248	6,575	4,622.2	0.4%	-14.1%	-17.9%
80	CLEVELAND, OH	496,049	29,778	6,003.0	-2.6%	-9.3%	-17.7%
81	ROCHESTER, NY	231,373	18,658	8,064.0	-7.7%	-24.6%	-17.7%
82	SPRINGFIELD, MO	152,024	10,710	7,044.9	-5.5%	-2.2%	-17.4%
83	AURORA, CO	262,188	14,353	5,474.3	-5.9%	-19.7%	-17.0%
84	GARY, IN	116,024	7,349	6,334.0		-24.0%	-16.8%
85	FLINT, MI	139,588	12,729	9,119.0	-5.8%	-13.0%	-16.8%
86	BAKERSFIELD, CA	193,777	11,462	5,915.0	-9.2%	-16.4%	-16.6%
87	JACKSONVILLE, FL	690,367	49,769	7,209.1	-5.0%	-17.8%	-16.5%
88	AURORA, IL	113,220	5,562	4,912.6	2.9%	-12.7%	-16.4%
89	MILWAUKEE, WI	627,139	43,649	6,960.0	-5.7%	-9.4%	-16.1%
90	TAMPA, FL	294,670	34,184	11,600.8	3.9%	-6.6%	-15.9%
91	BERKELEY, CA	101,250	9,246	9,131.9	-9.8%	-17.9%	-15.6%
92	CHANDLER, AZ	129,554	8,122	6,269.2	0.8%	-0.4%	-15.5%
93	LAKEWOOD, CO	131,786	6,965	5,285.1	0.4%	-10.4%	-15.3%
94	PORTSMOUTH, VA	105,404	7,516	7,130.7	-0.2%	-5.9%	-14.9%
95	SUNNYVALE, CA	121,284	3,257	2,685.4	-8.4%	-28.5%	-14.8%
96	SEATTLE, WA	539,591	51,093	9,468.8	-0.9%	-11.1%	-14.6%
97	CHICAGO, IL	2,754,118	194,058	7,046.1	-2.1%	-6.6%	-14.3%
98	LEXINGTON, KY	241,150	13,330	5,527.7	-4.2%	-0.9%	-13.9%
99	DENVER, CO	516,224	30,482	5,904.8	-1.8%	-16.6%	-13.9%
100	NEW ORLEANS, LA	488,300	42,898	8,785.2	0.7%	9.7%	-13.7%
101	DES MOINES, IA	195,455	14,231	7,281.0	-6.2%	-8.2%	-13.6%
102	OXNARD, CA	147,937	6,528	4,412.7	2.2%	-22.4%	-13.5%
103	NORWALK, CA	102,176	3,212	3,143.6	-14.7%	-16.1%	-12.9%
104	ELIZABETH, NJ	107,427	8,022	7,467.4	-3.8%	1.0%	-12.6%
105	BROWNSVILLE, TX	117,511	8,717	7,418.0	12.4%	-23.1%	-12.5%
106	WICHITA, KS	312,706	22,509	7,198.1	-4.3%	-12.6%	-12.3%
107	FORT LAUDERDALE, FL	168,059	22,903	13,628.0	-0.9%	-6.8%	-12.0%
108	NEWPORT NEWS, VA	182,487	8,653	4,741.7	-9.6%	-21.4%	-11.5%
109	TORRANCE, CA	140,185	6,422	4,581.1	-8.4%	-9.4%	-11.2%
110	PHOENIX, AZ	1,139,793	98,220	8,617.4	-12.2%	6.0%	-10.9%
111	OAKLAND, CA	372,145	31,006	8,331.7		-15.2%	-10.8%
112	GRAND RAPIDS, MI	192,358	12,157	6,320.0	0.1%	-13.2%	-10.6%
113	LUBBOCK, TX	202,403	10,882	5,376.4	-7.4%	-14.3%	-10.5%
114	TOLEDO, OH	324,610	24,853	7,656.3	2.0%	-1.6%	-10.4%
115	DAYTON, OH	179,680	15,815	8,801.8	-4.5%	-5.1%	-10.0%
116	COLUMBIA, SC	105,316	10,338	9,816.2	-4.1%	4.9%	-9.9%
117	ATLANTA, GA	413,123	56,841	13,758.9	2.5%	2.0%	-9.2%
118	ROCKFORD, IL	144,421	13,210	9,146.9	-3.0%	-4.9%	-9.1%
119	MORENO VALLEY, CA	141,292	7,541	5,337.2	-5.2%	-17.2%	-8.9%
120	GREEN BAY, WI	104,283	4,289	4,112.8	-2.3%	-4.8%	-8.9%
121	JACKSON, MS	196,619	18,100	9,205.6	-11.9%	-21.9%	-8.9%
122	LAS VEGAS, NV	831,303	48,534	5,838.3	-8.6%	-9.7%	-8.8%
123	EVANSVILLE, IN	131,455	6,625	5,039.7	-2.5%	10.6%	-8.7%
124	AMARILLO, TX	171,779	12,660	7,369.9	4.0%	-4.3%	-8.7%
125	TACOMA, WA	189,568	17,358	9,156.6	-8.1%	3.1%	-8.7%
126	AKRON, OH	223,303	13,662	6,118.1	0.0%	-5.0%	-8.5%
127	LANCASTER, CA	120,881	4,564	3,775.6	-8.6%	-20.6%	-8.4%
128	HOLLYWOOD, FL	128,996	11,377	8,819.7	1.5%	7.9%	-8.1%
129	DOWNEY, CA	101,309	4,195	4,140.8	-1.4%	-2.4%	-8.0%
130	ORLANDO, FL	182,616	20,053	10,981.0	16.2%	9.6%	-7.9%
131	PHILADELPHIA, PA	1,528,403	82,399	5,391.2	-4.4%	10.4%	-7.7%
132	ERIE, PA	108,432	4,863	4,484.8	-3.3%	6.3%	-7.6%
133	PUEBLO, CO	105,059	5,985	5,696.8	-9.1%	2.5%	-7.3%
134	HUNTSVILLE, AL	162,376	12,991	8,000.6	9.3%	-8.7%	-7.1%
135	KANSAS CITY, MO	448,474	43,415	9,680.6	0.7%	0.6%	-6.9%
136	PLANO, TX	163,817	7,749	4,730.3	8.3%	-6.2%	-6.5%
137	ALEXANDRIA, VA	114,996	6,507	5,658.5	-4.6%	-4.6%	-6.4%
138	BURBANK, CA	101,082	3,705	3,665.3	-1.6%	-12.8%	-6.3%
139	TEMPE, AZ	156,788	13,160	8,393.5	-9.7%	16.5%	-6.3%
140	SPOKANE, WA	199,636	14,978	7,502.7	-1.3%	-1.1%	-6.3%
141	BIRMINGHAM, AL	272,169	24,867	9,136.6	-6.3%	-5.8%	-5.7%
142	SAVANNAH, GA	146,534	11,770	8,032.3	8.5%	-4.0%	-5.5%
143	CHESAPEAKE, VA	183,965	7,659	4,163.3	-1.6%	-18.7%	-4.4%
144	COLUMBUS, GA	194,345	11,404	5,867.9	-2.3%	4.1%	-4.2%
145	HIALEAH, FL	200,339	16,197	8,084.8	15.5%		-4.1%
146	ST. PAUL, MN	267,292	18,267	6,834.1	2.0%	1.4%	-4.0%
147	RANCHO CUCAMONGA, CA	116,431	4,458	3,828.9	-1.3%	-16.5%	-3.8%
148	FORT COLLINS, CO	103,472	5,029	4,860.3	-3.6%		-3.4%
149	BUFFALO, NY	313,238	22,112	7,059.2	-1.7%	-12.9%	-3.1%
150	COLUMBUS, OH	640,297	54,867	8,569.0	5.1%	7.6%	-2.6%
151	WACO, TX	110,213	10,201	9,255.7	16.7%	8.2%	-2.5%
152	PORTLAND, OR	467,906	42,471	9,076.8	-10.5%	-3.8%	-2.5%
153	LINCOLN, NB	206,704	13,138	6,355.9	-0.6%	-8.6%	-2.1%
154	SCOTTSDALE, AZ	165,644	9,292	5,609.6	-14.5%	1.1%	-2.0%
155	LANSING, MI	120,821	8,095	6,700.0	-1.0%	15.9%	-1.9%
156	MONTGOMERY, AL	197,972	11,613	5,866.0	-1.8%	2.4%	-1.9%
157	SACRAMENTO, CA	379,283	30,073	7,928.9	-13.7%	-9.9%	-1.5%
158	LAFAYETTE, LA	103,134	7,638	7,405.9	-15.2%	-8.7%	-1.2%
159	CORPUS CHRISTI, TX	286,660	27,447	9,574.8	1.3%	2.3%	-1.1%
160	SALT LAKE CITY, UT	180,180	20,782	11,534.0	-2.3%	2.0%	-1.1%
161	SANTA ROSA, CA	118,625	6,242	5,262.0	-6.9%	-5.1%	-0.9%
162	SYRACUSE, NY	160,033	9,601	5,999.4	-3.0%	-4.1%	-0.8%
163	BATON ROUGE, LA	229,501	23,963	10,441.3	-1.4%	-10.5%	-0.8%
164	NAPERVILLE, IL	101,980	2,748	2,694.6	6.8%	-2.0%	-0.7%
165	FRESNO, CA	392,049	36,226	9,240.2	-11.6%	-13.3%	-0.5%
166	MOBILE, AL	207,106	17,327	8,366.2	0.7%	-12.0%	-0.4%
167	RALEIGH, NC	245,176	14,971	6,106.2	-5.0%	-6.8%	0.3%
168	CONCORD, CA	113,479	6,656	5,865.4	-6.2%	2.1%	1.9%
169	DETROIT, MI	1,002,299	96,949	9,672.7	1.5%	11.2%	1.9%
170	VALLEJO, CA	113,069	7,432	6,573.0	-0.6%	-4.3%	2.3%
171	GREENSBORO, NC	203,186	14,466	7,119.6	-10.9%	-3.4%	2.8%
172	CINCINNATI, OH	360,457	23,534	6,528.9	5.4%	-10.2%	3.2%
173	BOISE, ID	153,258	8,194	5,346.5	-2.6%	3.4%	3.2%
174	OMAHA, NB	350,607	22,197	6,331.0	-7.2%		3.5%
175	ABILENE, TX	114,523	5,373	4,691.6	-1.7%	14.3%	3.7%
176	MESA, AZ	340,818	23,276	6,829.5	-15.5%	7.6%	5.3%
177	WINSTON-SALEM, NC	160,678	16,706	10,397.2	-4.8%	4.8%	5.5%
178	HAYWARD, CA	117,233	7,058	6,020.5	-1.9%	0.0%	6.2%
179	SIOUX FALLS, SD	110,891	4,881	4,401.6	-7.7%	8.9%	6.6%
180	ANCHORAGE, AK	254,774	14,100	5,534.3	-11.2%	-11.3%	7.3%
181	MODESTO, CA	178,865	11,573	6,470.2	-18.4%	4.2%	8.5%
182	MEMPHIS, TN	631,626	57,746	9,142.4	4.5%	10.2%	9.0%
183	ALLENTOWN, PA	105,372	6,791	6,444.8	8.7%	15.4%	9.6%
184	ST. LOUIS, MO	374,041	46,385	12,401.0	-2.6%	7.8%	10.5%
185	PEORIA, IL	113,790	9,530	8,375.1		-2.9%	10.9%
186	MACON, GA	113,802	13,040	11,458.5	25.2%	27.2%	11.2%
187	SALEM, OR	119,822	10,338	8,627.8	-14.9%	4.6%	11.4%
188	SHREVEPORT, LA	199,418	21,168	10,614.9	7.0%	13.8%	12.1%
189	HONOLULU, HI	878,044	57,311	6,527.1	-10.6%	11.6%	12.3%
190	SPRINGFIELD, IL	106,794	8,419	7,883.4	-8.5%	-1.0%	12.5%
191	ALBUQUERQUE, NM	426,736	41,986	9,838.9	12.2%	24.1%	12.7%
192	WASHINGTON, DC	543,000	51,146	9,419.2	-0.9%	10.0%	13.3%
193	BALTIMORE, MD	716,446	66,475	9,278.4	-9.9%	2.6%	13.7%
194	LOUISVILLE, KY	274,506	17,642	6,426.8	8.0%	12.5%	15.3%
195	FREMONT, CA	186,186	6,957	3,736.6	-6.7%	7.6%	15.3%
196	OKLAHOMA CITY, OK	469,632	51,722	11,013.3	7.9%	12.6%	15.6%
197	DURHAM, NC	148,571	15,147	10,195.1	6.1%	7.1%	19.6%
198	ALBANY, NY	104,919	6,998	6,669.9	-1.7%	2.2%	20.8%
199	INDEPENDENCE, MO	113,382	8,184	7,218.1	-2.6%	24.0%	21.5%
200	EUGENE, OR	122,637	11,442	9,330.0	0.6%	23.5%	22.8%
201	TOPEKA, KS	121,495	13,892	11,434.2	-3.9%	31.7%	33.7%
202	NASHVILLE, TN	530,059	49,446	9,328.4	4.6%	15.8%	43.5%
203	INDIANAPOLIS, IN	376,531	30,499	8,100.0		37.8%	48.3%

NOTES

A number of cities with populations greater than 100,000 are not included on this list.. These cities either do not participate in the FBI's voluntary Uniform Crime Reporting problem, or have not reported crimes completely for the years in question.

Cities not included in this report:

City & State

BABYLON TOWN, NY

BROOKHAVEN, NY

CEDAR RAPIDS, IA

CLEARWATER, FL

HENDERSON, NV

HUNTINGTON, NY

ISLIP, NY

KANSAS CITY, KS

MINNEAPOLIS, MN

OVERLAND PARK, KS

PALMDALE, CA

SAN BERNARDINO, CA

SOUTH BEND, IN

SPRINGFIELD, MA

TALLAHASSEE, FL

THOUSAND OAKS, CA

WARREN, MI

WORCESTER, MA

METHODOLOGY

Statistics were drawn from FBI Uniform Crime Reports, specifically 9-track computer tape versions of the FBI's Return A Master for 1990, 1992, and 1995; and from the 1996 Uniform Crime Reports Preliminary Annual Report (June 1, 1997), and in additions made to the Preliminary Annual Report through June 5, 1997.

Population statistics are estimates from the U. S. Census Bureau, as provided to the FBI and included on Return-A master. In the case of the 1996 Preliminary Annual Report, populations are 1996 estimates provided to the FBI by the U. S. Census Bureau.

Calculations and rankings were performed by Number Crunchers Precision Journalism®.

Over that period of time, some law-enforcement agencies have substantially changed jurisdictions, which means that figures and rates for successive years may not be comparable.

THE INDEX

There are seven crimes included in the FBI's Crime Index. Four are crimes against persons, also known as violent crimes. Three are crimes against property. A fourth category of property crime – arson – was added to the FBI Crime Index in the late 1970s. However, not all agencies report the category. Thus, seven crimes are included in these statistics. They are:

VIOLENT CRIME	PROPERTY CRIME
Murder and non-negligent manslaughter	Burglary
Forcible Rape	Larceny-Theft
Robbery	Motor Vehicle Theft
Aggravated Assault

STRENGTHS AND WEAKNESSES

The FBI Crime Index has several substantial strengths and weaknesses as a measure of crime. Primary among its strengths is how widespread it is. The overwhelming majority of law-enforcement agencies across the country voluntarily contribute data to the FBI Uniform Crime Reporting program each year.

Among the weaknesses is that the FBI Crime Index counts only those incidents in selected categories known to police. Crimes – such as rape, for instance – in categories where reporting is known to be less than complete may not be accurately represented. Also, crimes within certain communities which may not cooperate fully with and trust their law-enforcement agencies may be skewed.