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From page 73... ... The Census Bureau's American FactFinder website provides quick and easy on-line access to data tables and thematic maps. On their website, the Census Bureau provides ready-made demographic proﬁle tables at the state, county, and place level of geography (places with more 73 C H A P T E R 5 Policy Planning and Other Descriptive Analyses Using ACS Data Read the entire page →
From page 74... ... 5.1.2 ACS for Descriptive Analyses As for the products based on the census 2000 Long Form, the ACS data releases described in Section 3 of this guidebook provide most data users with very efﬁcient means of obtaining the 74 A Guidebook for Using American Community Survey Data for Transportation Planning 43 These ﬁgures are obtained from the Missouri Department of Transportation Socio-Economic Indicator Resource web page at http://oseda.missouri.edu/modot/planning/northcentral_transportation.shtml. Figure 5.1. Read the entire page →
From page 75... ... Therefore, the general ability of users to perform descriptive analyses of the types most commonly performed will remain as the Census Bureau completes the migration to ACS. Policy Planning and Other Descriptive Analyses Using ACS Data 75 Adair Carroll Chariton Grundy Howard Linn Livingston Macon Mercer Putnam Randolph Saline Schuyter Sullivan 14.7 26.5 23.4 19.6 25.3 20.8 18.2 21.3 24.8 26.7 21.1 17.1 25 21.2 0 5 10 15 20 25 30 Mean Travel Time to Work (in Minutes) Read the entire page →
From page 76... ... The ACS's smaller sample sizes and the Census Bureau's stricter rules on avoiding publication of estimates where there is a possibility that an individual can be identiﬁed, will make descriptive analyses of many small areas more difﬁcult. 5.3 Descriptive Analysis Case Studies The following case studies illustrate how a data user might compile descriptive analyses using ACS data, and provide a step-by-step description of how to obtain the data, do the computations, and present the results. Read the entire page →
From page 77... ... . Policy Planning and Other Descriptive Analyses Using ACS Data 77 44 The data used for the ﬁrst two example case studies are from ACS estimates for Lake County, Illinois, for 2002 and 2003, and on ﬁctitious hypothetical estimates for the same county. Read the entire page →
From page 78... ... Table 5.1 shows selected commuting-to-work characteristics for Lake County for years 2002 and 2003. The data ﬁles and estimates included in the Census Bureau detailed tabulations are released with a lower bound and an upper bound corresponding to the 90 percent conﬁdence interval. Read the entire page →
From page 79... ... * Total Households 222,841 221,092 224,590 226,074 224,274 227,874 Mode to Work: Total Workers 16+ 314,647 309,478 319,816 316,525 312,408 320,642 Car, Truck, or Van: 282,426 276,882 287,970 282,407 277,642 287,172 Drove Alone 252,516 247,114 257,918 249,687 244,713 254,661 Carpooled 29,910 27,176 32,644 32,720 29,361 36,079 All Public Transportation: 13,829 12,087 15,571 13,299 11,567 15,031 Bus or Trolley Bus 1,860 1,114 2,606 2,527 1,686 3,368 Streetcar or Trolley Car 117 0 307 138 6 270 Subway or Elevated 541 241 841 776 401 1,151 Railroad 11,110 9,508 12,712 9,557 8,121 10,993 Ferryboat 39 0 103 43 0 115 Taxicab 162 0 330 258 48 468 Motorcycle 249 72 426 72 0 155 Bicycle 728 314 1,142 916 360 1,472 Walked 3,459 2,390 4,528 5,459 4,167 6,751 Other Means 1,315 804 1,827 2,176 1,567 2,785 Worked at Home 12,641 10,994 14,288 12,196 10,652 13,740 Departure Time to Work Total Workers 16+ 314,647 309,478 319,816 316,525 312,408 320,642 Did Not Work at Home: 302,006 296,960 307,052 304,329 300,014 308,644 12:00 a.m. Read the entire page →
From page 80... ... To know whether this difference in percentages of workers who used a certain mode to work is statistically signiﬁcant, the steps described below should be applied. These steps are based on the documents released by the Census Bureau on the accuracy of the data and the change proﬁles, and are summarized in Section 4 of this guidebook.45 Step 1 -- Compute the standard errors of the numerator Xˆ and denominator Yˆ of the proportion Pˆ, given their lower and upper bounds. Read the entire page →
From page 81... ... ⎡⎣ ⎤⎦ − ( ) ⎡⎣ ⎤⎦1 2 22 2 Policy Planning and Other Descriptive Analyses Using ACS Data 81 Read the entire page →
From page 82... ... Speciﬁcally, it shows the 2002 and 2003 percentages, difference in percentages, standard error of the difference, margin of error of the difference, lower and upper bounds of the 90 percent conﬁdence interval, and whether the difference is statistically signiﬁcant at the 90 percent level of conﬁdence. 5.3.2 Analysis 2: Ranking Profile You have been asked to produce a proﬁle of Hypothetical Lake County showing the percentage of zero-vehicle households in year 2010 by county subdivision and how the different subdivisions compare to the county average.46 Understanding how vehicle availability varies across the county is important, for example, for determining whether transit service is adequate in areas with higher concentrations of zero-vehicle households. Read the entire page →
From page 83... ... , and 7 county subdivisions where the percentage of zerovehicle households is larger than the county average. Policy Planning and Other Descriptive Analyses Using ACS Data 83 Given Data Calculations Estimate Lower Bound Upper Bound Standard Error of Estimate Proportion Standard Error of Proportion Total Population 654,067 * Read the entire page →
From page 84... ... 84 A Guidebook for Using American Community Survey Data for Transportation Planning Given Data Calculations Estimate Lower Bound Upper Bound Standard Error of Estimate Proportion Standard Error of Proportion Total population 663,721 * Read the entire page →
From page 85... ... Policy Planning and Other Descriptive Analyses Using ACS Data 85 Given Data Calculations 2002 Estimate 2003 Estimate 2002 % 2003 % Diff: 2003 % -2002 % SE (Diff) Read the entire page →
From page 86... ... Figure 5.7. Percentage of zero-vehicle households by county subdivision as compared to the county average based on the point estimates for Hypothetical Lake County. Read the entire page →
From page 87... ... Percentage of zero-vehicle households by county subdivision: estimate, lower bound, and upper bound for Hypothetical Lake County. Read the entire page →
From page 88... ... Five-Year Data (2005-2009) Antioch Township 23,450 23,906 24,363 24,820 25,276 No Yes Yes Avon Township 58,903 60,049 61,196 62,343 63,490 No Yes Yes Benton Township 18,463 18,827 19,190 19,553 19,917 No No Yes Cuba Township 16,880 17,208 17,537 17,866 18,194 No No Yes Ela Township 42,537 43,366 44,194 45,022 45,850 No Yes Yes Fremont Township 25,675 26,175 26,675 27,175 27,675 No Yes Yes Grant Township 18,446 18,809 19,172 19,535 19,898 No No Yes Lake Villa Township 36,142 36,846 37,549 38,253 38,957 No Yes Yes Libertyville Township 52,415 53,436 54,456 55,477 56,497 No Yes Yes Moraine Township 37,018 37,738 38,459 39,180 39,901 No Yes Yes Newport Township 4,439 4,526 4,612 4,699 4,785 No No Yes Shields Township 46,497 47,402 48,307 49,213 50,118 No Yes Yes Vernon Township 70,047 71,411 72,775 74,139 75,503 Yes Yes Yes Warren Township 63,690 64,930 66,171 67,411 68,651 Yes Yes Yes Wauconda Township 17,563 17,905 18,247 18,589 18,931 No No Yes Waukegan Township 99,468 101,405 103,341 105,278 107,215 Yes Yes Yes West Deerfield Township 34,077 34,740 35,404 36,067 36,731 No Yes Yes Zion Township 24,508 24,985 25,462 25,939 26,416 No Yes Yes County Total 690,218 703,664 717,110 730,559 744,005 Yes Yes Yes Table 5.5. Read the entire page →
From page 89... ... County Subdivision Total Occupied Households Lower Bound Upper Bound ZeroVehicle Households Lower Bound Upper Bound Antioch Township Avon Township Benton Township Cuba Township Ela Township Fremont Township Grant Township Lake Villa Township Libertyville Township Moraine Township Newport Township Shields Township Vernon Township 26,124 23,867 28,381 248 177 319 Warren Township 25,383 23,159 27,607 570 426 714 Wauconda Township Waukegan Township 32,139 29,651 34,627 2,337 1,891 2,783 West Deerfield Township Zion Township County Total 249,685 248,264 251,106 6,817 5,832 7,802 Table 5.6. Annual 2009 acs data for Hypothetical Lake County. Read the entire page →
From page 90... ... , ACS data for Hypothetical Lake County. County Subdivision Total Occupied Households Lower Bound Upper Bound ZeroVehicle Households Lower Bound Upper Bound Antioch Township 9,613 9,056 10,170 304 266 342 Avon Township 19,487 18,624 20,350 507 449 565 Benton Township 7,036 6,586 7,486 192 166 218 Cuba Township 6,709 6,273 7,145 87 74 100 Ela Township 14,388 13,666 15,110 121 104 138 Fremont Township 9,064 8,528 9,600 98 84 112 Grant Township 7,614 7,138 8,090 284 248 320 Lake Villa Township 12,969 12,292 13,646 187 162 212 Libertyville Township 19,475 18,612 20,338 515 456 574 Moraine Township 13,996 13,286 14,706 490 433 547 Newport Township 1,706 1,550 1,862 16 13 19 Shields Township 11,549 10,920 12,178 358 314 402 Vernon Township 25,265 24,273 26,257 270 236 304 Warren Township 24,586 23,607 25,565 622 553 691 Wauconda Township 6,729 6,292 7,166 230 200 260 Waukegan Township 31,314 30,214 32,414 2,551 2,337 2,765 West Deerfield Township 12,025 11,380 12,670 96 82 110 Zion Township 8,285 7,781 8,789 512 453 571 County Total 241,810 241,147 242,473 7,440 6,972 7,908 Table 5.8. Read the entire page →
From page 91... ... UB (%) Antioch Township 9,613 304 339 23 3.2 0.2 2.8 3.5 Avon Township 19,487 507 523 35 2.6 0.2 2.3 2.9 Benton Township 7,036 192 273 16 2.7 0.2 2.4 3.1 Cuba Township 6,709 87 264 8 .3 0.1 1.1 1.5 Ela Township 14,388 121 438 10 0.8 0.1 0.7 0.9 Fremont Township 9,064 98 325 8 .1 0.1 1.0 1.2 Grant Township 7,614 284 288 22 3.7 0.2 3.3 4.1 Lake Villa Township 12,969 187 410 15 1.4 0.1 1.3 1.6 Libertyville Township 19,475 515 523 36 2.6 0.2 2.4 2.9 Moraine Township 13,996 490 430 35 3.5 0.2 3.1 3.9 Newport Township 1,706 16 95 2 .9 0.1 0.8 1.1 Shields Township 11,549 358 381 27 3.1 0.2 2.8 3.4 Vernon Township 25,265 270 601 21 1.1 0.1 0.9 1.2 Warren Township 24,586 622 593 42 2.5 0.2 2.3 2.8 Wauconda Township 6,729 230 265 18 3.4 0.2 3.0 3.8 Waukegan Township 31,314 2,551 667 130 8.1 0.4 7.5 8.8 West Deerfield Township 12,025 96 391 8 1 1 0 0.8 0.1 0.7 0.9 Zion Township 8,285 512 305 36 6.2 0.4 5.6 6.8 County Total 241,810 7,440 402 284 3.1 0.1 2.9 3.3 Table 5.9. Read the entire page →
From page 92... ... For each county subdivision, the 90 percent conﬁdence interval means that 90 times out of 100 the true value of the percentage of zero-vehicle households for that area falls between the lower and upper bounds of an estimate derived from a sample like the one taken. Once the percentages and standard errors of the percentages are calculated, the differences between individual subdivisions and the county as a whole can be calculated and compared using the procedures previously described. Read the entire page →
From page 93... ... Antioch Township 0.1% 0.24% 0.40% -0.3% 0.5% No Avon Township -0.5% 0.20% 0.33% -0.8% -0.1% Yes Benton Township -0.3% 0.23% 0.38% -0.7% 0.0% No Cuba Township -1.8% 0.16% 0.26% -2.0% -1.5% Yes Ela Township -2.2% 0.13% 0.22% -2.5% -2.0% Yes Fremont Township -2.0% 0.14% 0.23% -2.2% -1.8% Yes Grant Township 0.7% 0.27% 0.46% 0.2% 1.1% Yes Lake Villa Township -1.6% 0.16% 0.26% -1.9% -1.4% Yes Libertyville Township -0.4% 0.20% 0.34% -0.8% -0.1% Yes Moraine Township 0.4% 0.25% 0.42% 0.0% 0.8% No Newport Township -2.1% 0.16% 0.26% -2.4% -1.9% Yes Shields Township 0.0% 0.24% 0.40% -0.4% 0.4% No Vernon Township -2.0% 0.14% 0.23% -2.2% -1.8% Yes Warren Township -0.5% 0.20% 0.33% -0.9% -0.2% Yes Wauconda Township 0.3% 0.26% 0.43% -0.1% 0.8% No Waukegan Township 5.1% 0.40% 0.65% 4.4% 5.7% Yes West Deerfield Township -2.3% 0.13% 0.22% -2.5% -2.1% Yes Zion Township 3.1% 0.39% 0.64% 2.5% 3.7% Yes Table 5.10. Statistical difference computation results. Read the entire page →
From page 94... ... Table 5.12 shows the distribution of number of workers by means of transportation to work using Census 2000 data and 2000-2003 annual ACS data. 94 A Guidebook for Using American Community Survey Data for Transportation Planning Survey Year 0 50 100 150 200 250 300 350 400 450 Census 2000 ACS 2000 ACS 2001 ACS 2002 ACS 2003 Commuters (in Thousands) Read the entire page →
From page 95... ... Policy Planning and Other Descriptive Analyses Using ACS Data 95 Employed Civilians (in Millions) BLS, % Change, 2000-2003 = -4.7% ACS, % Change, 2000-2003 = -7.4% 3.20 3.25 3.30 3.35 3.40 3.45 3.50 3.55 3.60 3.65 2000 2001 2002 2003 Year 145,700 70,800 Census 2000 ACS BLS-LAUS 175,300 266,000 Figure 5.11 Employed civilians, Census 2000, ACS, and BLS-LAUS. Read the entire page →
From page 96... ... Calculate standard errors for the component geography estimates, 3. Calculate the standard errors of the estimates for the combined geography, and 96 A Guidebook for Using American Community Survey Data for Transportation Planning Census American Community Survey 2000 2000 2001 2002 2003 Total: 3,306,100 3,337,500 3,236,400 3,203,700 3,186,900 Car, Truck, or Van: 2,674,600 2,683,800 2,604,100 2,596,300 2,571,300 Drove Alone 2,248,100 2,252,300 2,239,900 2,240,700 2,205,800 Carpooled 426,500 431,500 364,200 355,600 365,500 Public Transportation: 321,100 357,700 324,300 306,100 300,800 Bus or Trolley Bus 178,900 199,400 180,000 178,400 176,900 Streetcar or Trolley Car 14,300 14,300 15,100 12,800 10,400 Subway or Elevated 98,700 107,500 94,800 88,100 85,300 Railroad 20,100 24,600 21,900 19,000 20,400 Ferryboat 5,800 6,700 7,900 4,100 6,100 Taxicab 3,300 5,100 4,500 3,600 1,900 Motorcycle 11,900 13,700 13,800 9,400 9,400 Bicycle 36,000 36,800 31,300 33,000 31,000 Walked 106,100 92,200 92,900 100,800 100,100 Other Means 23,700 19,000 27,600 15,800 23,900 Worked at Home 132,700 134,400 142,500 142,300 150,300 Table 5.12. Read the entire page →
From page 97... ... Hence, the standard errors for the carpool estimates are those shown in Table 5.14. Policy Planning and Other Descriptive Analyses Using ACS Data 97 Carpool Commuters Bay Area Bicycle Commuters Geographic Area Estimate Lower Bound Upper Bound Estimate Lower Bound Upper Bound San Francisco CMSA 373,018 353,631 392,405 34,561 28,350 40,772 Oakland PMSA 148,912 134,587 163,237 11,635 7,980 15,290 San Francisco PMSA 75,418 67,238 83,598 10,149 8,007 12,291 San Jose PMSA 79,052 68,397 89,707 6,743 2,826 10,660 Santa Rosa PMSA 24,377 18,945 29,809 1,795 372 3,218 Vallejo PMSA 37,723 31,846 43,600 723 29 1,417 Santa Cruz PMSA (outside MTC area) Read the entire page →
From page 98... ... For the ﬁrst approach, in which the non-MTC PMSA estimate is subtracted from the CMSA estimate, the combined standard error is For the second approach, in which the ﬁve MTC PMSAs are summed, the combined standard error is: Step 4 -- Calculate the margins of error. The margin of error for the 90 percent conﬁdence level is Therefore, for the ﬁrst approach, in which the non-MTC PMSA estimate is subtracted from the CMSA estimate, the combined estimate is: Carpool CommutersMTC Area = 365,482 ± 19,544 For the second approach, in which the ﬁve MTC PMSAs are summed, the combined estimate is Carpool CommutersMTC Area = 365,482 ± 21,206 Although the two approaches have the same central point estimate, the ﬁrst approach that combines only two ACS estimates provides a more precise estimate than the second approach where ﬁve separate estimates are combined. Read the entire page →
From page 99... ... 90% Confidence Interval 31,045 + 6,635 31,045 + 5,983 Method for Deriving MPO Data from Census Geography San Francisco CMSA less Santa Cruz PMSA Sum of 5 PMSAs 0 5 10 15 20 25 30 35 40 Figure 5.14. Bay Area bicycle commuters, with confidence intervals, ACS 2003. Read the entire page →
From page 100... ... 5.3.4 Conclusions from these Analysis Case Studies Just as with the decennial census Long Form dataset, there are many different types of descriptive analyses that analysts can produce using ACS data. These case studies demonstrate how to produce change proﬁles and ranking proﬁles for a county and its subdivisions, create descriptive statistics for compiling a state-of-the-system report for a multicounty area, and interpret the results in light of the lower and upper bounds of the 90 percent conﬁdence interval that are released with the data. Read the entire page →
From page 101... ... Huntley et al., 2003.49 • A census book, containing information and proﬁles for each of the communities, produced every 10 years at Tulare County Association of Governments.50 • The use of PUMS data at MTC to produce demographic proﬁles of telecommuters in Marin County. Policy Planning and Other Descriptive Analyses Using ACS Data 101 47 See www.scag.ca.gov/economy/socioecondata.html, November 2003. Read the entire page →

From page 73...

... The Census Bureau's American FactFinder website provides quick and easy on-line access to data tables and thematic maps. On their website, the Census Bureau provides ready-made demographic proﬁle tables at the state, county, and place level of geography (places with more 73 C H A P T E R 5 Policy Planning and Other Descriptive Analyses Using ACS Data