Sheep and Goats - Quality Measures

Sheep and Goats Methodology and
Quality Measures
ISSN: 2167-1338

Released March 10, 2023, by the National Agricultural Statistics Service (NASS), Agricultural Statistics Board, United States Department of
Agriculture (USDA).

Scope and Purpose: The January Sheep and Goats Survey is conducted annually and targets sheep and goat producers in
the United States, excluding Alaska. The survey collects data for total sheep and goat inventories and components of that
total, including breeding animals, market inventory, market lambs by weight group, goat inventory by type, lamb and kid
crops, and wool and mohair production and value. In addition, data are collected for death loss from previous year, onfarm slaughter, and breeding and market animal values. Every five years a Sheep and Lamb Predator and Non-Predator
Loss Survey is conducted nationally and incorporated as part of the January Sheep and Goats Survey. Sheep estimates are
published for 32 states and New England and goat estimates are published for 34 states and New England.
Survey Timeline: The reference date for the January Sheep and Goats Survey is January 1, with a data collection period
of approximately 15 calendar days. Regional Field Offices (RFOs) may begin data collection one day prior to the
reference date. Data collection continues until a scheduled ending date and RFOs have about 4 or 5 business days to
complete editing and analysis, execute the summary, and interpret survey results. The Agricultural Statistics Board must
perform the national review, reconcile state estimates to the national estimates, and prepare official estimates for release in
5 or 6 business days. The estimates are released to the public on the last business day in January.
Sampling: The target population for the Sheep and Goats Survey is all agricultural establishments with one or more sheep
or goats owned by the operation. NASS uses a dual frame approach, consisting of list frame and area frame components,
to provide complete coverage of this target population. The Sheep and Goats Survey is conducted in every state except
Alaska.
The list frame includes all known agricultural establishments. Livestock inventory numbers of each establishment are
maintained on the list frame to allow NASS to define list frame sampling populations for specific surveys and to employ
efficient sampling designs. Only list frame records with positive sheep or goat inventory data are included in the list frame
population. The list frame for sheep and goat population covers approximately 83 percent of sheep inventory and 72
percent of goat inventory in the United States.
The area frame contains all land in the state and, as such, is complete. The land is stratified according to intensity of
agriculture using satellite imagery. The land in each stratum is divided into segments of roughly one square mile.
Segments are optimally allocated and sampled to effectively measure crops and livestock. The sampled segments are fully
enumerated in June. All farms and ranches found operating tracts in these segments are checked to see if they are included
in the list frame sheep and goat population. The farms and ranches that are not included in the list frame sheep and goat
population, called nonoverlap tracts, are sampled for the January Sheep and Goats Survey so that the target population is
completely represented. The area frame for sheep and goat population covers approximately 17 percent of sheep inventory
and 28 percent of goat inventory in the United States.
The Sheep and Goats Survey list frame sample is selected using a hierarchical stratified sampling design with strata
defined by total sheep and goats. The sample is designed to achieve a National standard error of 2 percent of the point
estimate for total sheep and 4 percent for total goats and kids. The Sheep and Goats Survey nonoverlap sample uses a
stratified sample design based on data collected in the June Area Frame Survey. Each sampling unit from the list and area
frames is assigned a sampling weight which is used to create the survey estimates.
Data Collection and Editing: For consistency across modes, the paper version is considered the master questionnaire and
the Computer Assisted Telephone Interview (CATI), Computed Assisted Self Interview (CASI), and Mobile Computer
Assisted Personal Interview (mCAPI) instruments are built to model the paper instrument. Questionnaire content and

format are evaluated annually through a specifications process where requests for changes are evaluated and approved or
disapproved. Input may vary from question wording or formatting to a program change involving the deletion or
modification of current questions or addition of new ones. If there are significant changes to either the content or format
proposed, a NASS survey methodologist will pre-test the changes for usability. Prior to the start of data collection, all
modes of instruments are reviewed and the paper, mCAPI, CASI and CATI instruments are thoroughly tested.
All federal data collections require approval by the Office of Management and Budget (OMB). NASS must document the
public need for the data, apply sound statistical practice, prove the data do not already exist elsewhere, and ensure the
public is not excessively burdened. The questionnaire must display an active OMB number that gives NASS the authority
to conduct the survey, a statement of the purpose of the survey and the use of the data being collected, a response burden
statement that gives an estimate of the time required to complete the form, a confidentiality statement that the respondent's
information will only be used for statistical purposes in combination with other producers, and a statement saying that
response to the survey is voluntary and not required by law.
In addition to asking the specific sheep and goat items, all instruments collect information to verify the sampled unit,
determine any changes in the name or address, identify any partners to detect possible duplication, verify the farm still
qualifies for the target population, and identify any additional operations operated by the sampled operator.
Sampled farms and ranches receive a pre-survey letter explaining the survey and informing them that they will be
contacted for survey purposes only. The letter provides the questions to be asked to allow respondents to prepare in
advance and also provides a pass code they can use to complete the survey on the internet. All modes of data collection
are utilized for sheep and goat surveys. RFOs are given the option of conducting a mail out/mail back phase. While mail is
the least costly mode of collection, the short data collection period and the uncertainty of postal delivery times limit its
effectiveness. Most of the data are collected by computer-assisted telephone interviews (CATI) by individual RFOs and
Data Collection Centers. Limited personal interviewing is done, generally for large operations or those with special
handling arrangements. A program is run to determine if any sampled farms are in multiple on-going surveys, so data
collection can be coordinated.
Survey Edit: As survey data are collected and captured, they are edited for consistency and reasonableness using
automated systems. The edit logic ensures the coding of administrative data follows the methodological rules associated
with the survey design. Relationships between data items on the current survey are verified and, in certain situations, those
items may be compared to data from earlier surveys to ensure relationships are logical. The edit will determine the status
of each record to be either "dirty" or "clean." Dirty records must be updated and reedited or certified by an analyst to be
clean. If updates are needed, they are reedited interactively. Only clean records are eligible for analysis and summary.
Analysis Tools: Edited data are processed through an interactive analysis tool which displays data for all reports by item.
The tool provides scatter plots, tables, charts, and special tabulations that allow the analyst to compare an individual
record to other similar records within their state. Outliers and unusual data relationships become evident and RFO staff
will review them to determine if they are correct. The tool also allows comparison to a farm's previously reported data to
detect large changes in the operation. Suspect data found to be in error are corrected, while data found to be correct are
kept.
Nonsampling Errors: Nonsampling errors are present in any survey process. These errors include reporting, recording,
editing, and imputation errors. Steps are taken to minimize the impact of these errors, such as questionnaire testing,
comprehensive interviewer training, validation and verification of processing systems, detailed computer edits, and the
analysis tool.
Estimators: Each farm and ranch in the sample has an initial sampling weight. This is the inverse of the sampling
fraction. For example, if a stratum has 1,000 farms in the population and 200 are sampled for this survey, each sampled
farm has a weight of 5. In other words, each sampled farm represents 5 farms. The nonoverlap tracts sampled to measure
the sheep and goats not accounted for by the list have a weight determined by adjusting their original area frame weight
by any second stage sampling weight.

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Sheep and Goats Methodology and Quality Measures (March 2023)
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Response to the January Sheep and Goats Survey is voluntary. Some producers refuse to participate in the survey. Others
cannot be located during the data collection period, and some submit incomplete reports. These nonrespondents must be
accounted for if accurate estimates of sheep and goats are to be made. For the Sheep and Goats Survey, nonrespondents
are accounted for by adjusting the weights of the respondents. The adjustment occurs by stratum as the bounded strata
represent homogeneous groupings of similar sized farms. The adjustment is also performed by individual item on the
questionnaire (total sheep, total goats, sheep death loss, etc.) so adjustments for item nonresponse (partial reports) and unit
nonresponse (refusals and inaccessibles) are done in a single calculation. Using the previous example, if 180 of the
original 200 respond, the weights of the 180 will be adjusted to 1,000 divided by 180, or 5.56. The largest stratum is
unbounded and consists of large and, often unique, farms. Nonrespondents in this stratum and the nonoverlap tracts must
be manually imputed by RFO statisticians, and their weights are not adjusted.
Two estimators are used to compute direct measures of the sheep and goat items. The "reweighted" estimator and the
"adjusted" estimator are computationally identical except in how the nonresponse adjustments are made. The reweighted
estimator uses a global weight adjustment across all usable reports. The nonresponse weight adjustment for the adjusted
estimator uses an additional piece of information. When a sampled farm refuses to cooperate, interviewers will probe to
determine the presence of sheep and/or goats even though the number is not known. This presence/absence indicator is
used in the weight adjustment.
Point estimates, called direct expansions, for both estimators are calculated by multiplying the reported value by the
nonresponse adjusted weight and summing to a stratum total. A variance estimate is also computed at the stratum level.
The nonoverlap tracts are treated as an additional stratum. Totals and variances are additive across strata to form a state
estimate and states are additive to a national estimate.
Ratio estimates are also computed for many items. For example, market lambs can be estimated as a percent of total
market sheep and lamb inventory. Ratio estimates use the reweighted estimator described above for the numerator and
denominator. Both the numerator and denominator must be complete for that record to be included in the ratio estimator.
Estimation: When all samples are accounted for, all responses fully edited, and the analysis material is reviewed, each
RFO executes the summary for their state. When all RFOs have run summaries, Headquarters executes the National
summary. Since all states conduct identical surveys, the samples can be pooled, and National survey results computed.
The summary results provide multiple point estimates and their standard errors for each data series being estimated. It also
provides information used to assess the performance of the current survey and evaluate the quality of the survey estimates,
such as strata level expansions, response rates, and percent of the expansion from usable reports.
RFOs are responsible for performing a detailed review of their survey results. Any irregularities revealed by the summary
must be investigated and, if necessary, resolved. Using the historical relationship of the survey estimates to the official
estimate, RFOs must interpret the survey results and submit a recommended estimate to Headquarters. The data are
viewed in tabular and graphical form and a consensus estimate is established. RFOs see their survey results only and do
not have access to other states' results. For some data series, information from other sources is also utilized in the process
of establishing estimates.
For the National estimates, NASS assembles a panel of statisticians to serve as the Agricultural Statistics Board (ASB)
which reviews the National results and establishes the National estimates. Since larger sample sizes yield more precise
results, NASS employs the "top-down" approach by determining the National estimates first and reconciling the state
estimates to the National number for sheep and goat inventories, lamb and kid crops, and wool and mohair production.
The ASB also enjoys an advantage in being able to examine results across states, compare the state recommendations, and
utilize administrative data available only at the National level. The same estimators used in the state summaries are
produced by the National summary. The ASB follows the same approach the states do in determining the National
estimate. The historical relationship of the survey estimates to the official estimate is evaluated over time to determine
accuracy and bias using tables and graphs. Every five years NASS conducts the Census of Agriculture, which is an
exhaustive data collection effort for all known farm operations across the United States. The information gathered from
the Census of Agriculture is used to establish benchmark levels by which the survey estimators can be compared, and bias
determined. Survey based estimators can also be impacted by "outliers" - individual reports that have "excessive
influence" on the results due to either improper classification or extremely unusual data for a given operation (i.e.,
Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

3

operation is not representative of other operations). NASS thoroughly reviews the survey data to identify these situations
and consider their impact on the survey results when establishing the official estimates.
External information (administrative data) is also utilized in the process of setting estimates. To be considered, these data
must be deemed to be reliable and come from unbiased sources. The most common administrative data is commercial
slaughter. NASS employs a balance sheet approach whenever possible to ensure that estimates are as accurate as possible.
This approach typically is limited to National-level estimates. A balance sheet and its components are reviewed when the
inventory numbers are established. Commercial slaughter is an important element of the balance sheet at the National
level since its high degree of reliability is based on a near-actual count of animals slaughtered. National level live animal
imports from other countries and exports to other countries are also considered.
Subtracting the disposition components of the balance sheet from supply components should, theoretically, give the
current inventory. However, each component of the balance sheet has varying degrees of possible estimation error. To be
most useful as an indication of inventory, therefore, each component should be estimated based on all available
information. The supply components of the National balance sheet are the beginning inventory, births, and imports
(inshipments for State balance sheets). From this supply, the disposition components - commercial slaughter (marketings
at State level), farm slaughter, deaths, and exports - are subtracted. The result is the indicated number on hand at the end
of the period or year.

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Sheep and Goats Methodology and Quality Measures (March 2023)
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Quality Metrics for Sheep and Goats
Purpose and Definitions: Under the guidance of the Statistical Policy Office of the Office of Management and Budget,
the United States Department of Agriculture’s National Agricultural Statistics Service provides data users with quality
metrics for its published data series. The metrics tables below describe the performance data for all surveys contributing to
the publication. The accuracy of data products may be evaluated through sampling and non-sampling error. The
measurement of error due to sampling in the current period is evaluated by the coefficient of variation for each estimated
item. Nonsampling error is evaluated by response rates and the weighted item response rates.
Sample size is the number of observations selected from the population to represent a characteristic of the
population. Operations that did not have the item of interest or were out of business at the time of data collection
have been excluded.
Response rate is the proportion of the above sample that completed the survey.
Weighted item response rate is a ratio of reported survey data expanded by the original sampling weight
compared to final nonresponse adjusted summary totals.
Coefficient of variation provides a measure of the size for the standard error relative to the point estimate and is
used to measure the precision of the results of a survey estimator.
Sheep and Goats Survey Sample Size and Response Rates: To assist in evaluating the performance of the estimates in
the sheep and goats report, the sample size and response rates are displayed.
Sheep and Goats Survey Sample Size and Response Rate – United States: January 1, 2022-2023
Sample size

Response rate

2022

2023

(number)
United States .......................................................................

2022

(number)

19,805

2023

(percent)

20,504

(percent)
56.2

54.0

Sheep and Goats Survey Quality Metrics – United States: January 1, 2022-2023
Weighted item
response rate
2022

Coefficient
of variation
2023

(percent)

2022

(percent)

2023

(percent)

(percent)

All sheep and lambs ............................................................
Breeding sheep and lambs ..............................................
Market sheep and lambs ..................................................
Lamb crop ...........................................................................
Wool production ...................................................................

60.6
59.5
63.9
60.6
64.6

57.5
57.0
58.8
57.6
62.0

4.1
4.4
4.5
4.1
5.3

3.9
3.6
7.3
4.3
6.0

All goats and kids ................................................................
Angora goats and kids .....................................................
Milk goats and kids ..........................................................
Meat and other goats and kids .........................................
Kid crop ...............................................................................
Mohair Production ...............................................................

62.0
64.6
67.5
60.5
62.5
72.2

58.5
65.4
58.0
58.3
57.2
61.9

6.3
21.6
20.4
5.9
7.1
11.7

4.8
18.1
7.5
5.7
4.9
16.7

Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

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Sheep and Goats Survey Sample Size and Response Rates – States and United States:
January 1, 2022-2023
Sample size
2022

Response rate
2023

(number)

2022

(number)

2023

(percent)

(percent)

Alabama .............................................................................
Arizona ...............................................................................
Arkansas .............................................................................
California ............................................................................
Colorado .............................................................................
Florida .................................................................................
Georgia ...............................................................................
Hawaii .................................................................................
Idaho ...................................................................................
Illinois ..................................................................................

373
181
282
827
752
344
418
144
339
365

406
166
301
858
700
350
415
156
370
389

51.2
50.3
52.1
42.0
52.3
45.1
48.6
51.4
61.1
62.7

50.5
53.0
49.8
39.6
50.4
38.3
47.5
52.6
57.6
54.5

Indiana ................................................................................
Iowa ....................................................................................
Kansas ................................................................................
Kentucky .............................................................................
Louisiana ............................................................................
Maryland .............................................................................
Michigan .............................................................................
Minnesota ...........................................................................
Mississippi ..........................................................................
Missouri ..............................................................................

427
726
410
394
200
279
399
554
302
488

458
720
416
468
230
271
445
578
313
502

50.6
54.3
55.1
59.9
60.5
52.3
51.4
59.7
65.6
55.5

48.5
58.2
49.0
56.6
43.0
48.7
52.1
56.7
49.5
57.2

Montana ..............................................................................
Nebraska ............................................................................
Nevada ...............................................................................
New England 1 ....................................................................
New Jersey .........................................................................
New Mexico ........................................................................
New York ............................................................................
North Carolina .....................................................................
North Dakota .......................................................................
Ohio ....................................................................................

546
398
127
595
169
285
365
392
227
588

520
415
139
631
180
296
375
442
227
616

60.4
51.0
44.9
64.4
45.0
53.3
44.4
66.6
64.3
48.3

62.9
49.4
45.3
52.6
42.2
50.7
56.8
59.3
59.9
44.5

Oklahoma ...........................................................................
Oregon ................................................................................
Pennsylvania ......................................................................
South Carolina ....................................................................
South Dakota ......................................................................
Tennessee ..........................................................................
Texas ..................................................................................
Utah ....................................................................................
Virginia ................................................................................
Washington .........................................................................

502
555
518
345
711
535
1,723
543
460
277

550
608
541
324
717
537
1,720
645
470
297

60.0
56.0
49.8
50.7
56.4
57.0
62.9
66.9
60.4
62.1

57.5
62.8
58.8
44.1
50.8
58.3
57.9
66.4
46.6
56.2

West Virginia .......................................................................
Wisconsin ...........................................................................
Wyoming .............................................................................

288
504
819

282
522
801

76.7
54.8
60.4

71.6
54.6
64.8

Other States 2 .....................................................................

129

137

49.6

48.2

United States ......................................................................

19,805

20,504

56.2

54.0

1

New England includes Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.
2
Individual state estimates not available for states not shown but are included in Other States.

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Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

Quality Metrics for All Sheep and Lambs – States and United States: January 1, 2022-2023
Weighted item
response rate
2022

Coefficient
of variation
2023

(percent)

2022

(percent)

2023

(percent)

(percent)

Arizona ................................................................................
California .............................................................................
Colorado ..............................................................................
Idaho ...................................................................................
Illinois ..................................................................................
Indiana ................................................................................
Iowa .....................................................................................
Kansas ................................................................................
Kentucky ..............................................................................
Michigan ..............................................................................

52.5
58.2
74.4
66.7
67.8
81.1
50.5
71.4
76.8
53.1

58.0
34.0
74.6
73.4
65.4
35.9
63.4
52.0
66.7
54.6

17.3
17.4
2.5
2.9
14.1
44.8
13.1
10.0
12.2
18.9

13.4
14.2
3.9
3.8
21.1
42.1
6.6
15.6
9.0
11.4

Minnesota ............................................................................
Missouri ...............................................................................
Montana ..............................................................................
Nebraska .............................................................................
Nevada ................................................................................
New England 1 .....................................................................
New Mexico .........................................................................
New York .............................................................................
North Carolina .....................................................................
North Dakota .......................................................................

84.6
37.9
73.0
48.9
28.4
29.1
59.5
45.9
63.2
41.4

60.1
49.5
64.9
74.1
13.8
54.9
39.2
57.7
72.8
42.5

47.8
32.5
3.5
9.0
8.6
40.6
19.3
15.6
13.3
33.7

14.8
33.8
4.8
40.5
5.0
37.5
10.5
8.3
14.3
32.0

Ohio .....................................................................................
Oklahoma ............................................................................
Oregon ................................................................................
Pennsylvania .......................................................................
South Dakota .......................................................................
Tennessee ...........................................................................
Texas ..................................................................................
Utah .....................................................................................
Virginia ................................................................................
Washington .........................................................................

57.6
67.2
76.8
46.0
51.5
72.6
67.5
70.0
61.8
40.0

47.1
61.5
84.6
50.2
45.0
64.4
62.4
70.0
58.9
65.0

11.8
10.0
44.3
20.5
4.5
14.1
7.7
3.2
10.1
33.3

11.4
10.6
47.9
12.5
6.4
15.0
5.5
6.7
19.6
38.2

West Virginia .......................................................................
Wisconsin ............................................................................
Wyoming .............................................................................

83.9
45.3
46.5

83.1
65.4
58.5

21.6
20.0
16.5

17.3
21.8
8.7

Other States 2 ......................................................................

46.2

51.8

8.4

8.6

United States .......................................................................

60.6

57.5

4.1

3.9

1

New England includes Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.
2
Individual state estimates not available for states not shown but are included in Other States.

Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

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Quality Metrics for Angora Goats – States and United States: January 1, 2022-2023
Weighted item
response rate
2022

Coefficient
of variation
2023

(percent)

2022

(percent)

2023

(percent)

(percent)

Arizona ...............................................................................
New Mexico ........................................................................
Texas ..................................................................................

92.1
65.3
56.0

81.2
60.8
61.5

81.8
39.2
24.1

60.1
35.9
17.6

Other States1 ......................................................................

75.5

61.0

25.3

14.2

United States ......................................................................

64.6

65.4

21.6

18.1

1

8

Individual state estimates not available for states not shown but are included in Other States.

Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

Quality Metrics for Milk Goats – States and United States: January 1, 2022-2023
Weighted item
response rate
2022

Coefficient
of variation
2023

(percent)

2022

(percent)

2023

(percent)

(percent)

Alabama ..............................................................................
Arkansas .............................................................................
California .............................................................................
Colorado ..............................................................................
Florida .................................................................................
Georgia ...............................................................................
Idaho ...................................................................................
Illinois ..................................................................................
Indiana ................................................................................
Iowa .....................................................................................

48.9
53.1
27.6
43.0
57.4
44.2
61.3
68.6
56.2
57.7

50.0
51.9
64.0
80.5
71.8
56.4
48.4
57.9
41.1
68.2

31.7
40.7
14.0
24.8
29.1
31.5
27.2
13.7
19.8
25.2

33.4
34.5
5.4
48.4
49.8
31.5
24.8
21.8
18.5
25.2

Kansas ................................................................................
Kentucky ..............................................................................
Michigan ..............................................................................
Minnesota ............................................................................
Missouri ...............................................................................
Nebraska .............................................................................
New England1 ......................................................................
New York .............................................................................
North Carolina .....................................................................
Ohio .....................................................................................

51.4
77.3
37.2
71.5
58.4
56.1
73.7
64.9
69.4
50.0

52.6
61.1
58.6
70.0
56.5
51.7
18.4
60.2
48.8
55.4

33.4
30.0
31.2
21.4
28.8
30.4
67.7
14.4
15.4
26.2

33.3
28.9
13.6
30.7
26.5
33.9
70.3
15.4
24.3
43.1

Oklahoma ............................................................................
Oregon ................................................................................
Pennsylvania .......................................................................
South Carolina .....................................................................
Tennessee ...........................................................................
Texas ..................................................................................
Virginia ................................................................................
Washington .........................................................................
Wisconsin ............................................................................

64.0
47.2
43.6
51.8
78.9
94.3
93.1
70.6
71.9

57.8
65.0
59.5
51.9
34.5
69.7
66.4
73.0
65.7

23.6
15.5
20.7
27.5
47.5
85.0
25.4
22.3
6.8

38.5
14.3
18.7
26.8
49.8
22.4
37.1
40.8
10.3

Other States2 .......................................................................

65.9

55.4

26.6

25.3

United States .......................................................................

67.5

58.0

20.4

7.5

1
2

New England includes Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.
Individual state estimates not available for states not shown but are included in Other States.

Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

9

Quality Metrics for Meat and Other Goats – States and United States: January 1, 2022-2023
Weighted item
response rate
2022

Coefficient
of variation
2023

(percent)

2022

(percent)

2023

(percent)

(percent)

Alabama .............................................................................
Arizona ...............................................................................
Arkansas .............................................................................
California ............................................................................
Colorado .............................................................................
Florida .................................................................................
Georgia ...............................................................................
Illinois ..................................................................................
Indiana ................................................................................
Iowa ....................................................................................

72.7
64.1
64.8
15.0
55.9
49.2
54.2
54.8
46.8
46.2

68.3
42.7
57.1
36.2
50.4
45.5
44.6
56.5
42.1
51.1

30.3
47.7
21.7
30.2
24.1
13.1
13.5
22.5
23.9
18.1

26.7
34.7
21.5
25.2
22.0
16.7
23.6
22.1
24.8
19.6

Kansas ................................................................................
Kentucky .............................................................................
Louisiana ............................................................................
Minnesota ...........................................................................
Mississippi ..........................................................................
Missouri ..............................................................................
New York ............................................................................
North Carolina .....................................................................
Ohio ....................................................................................
Oklahoma ...........................................................................

66.8
77.9
21.6
78.4
78.8
61.1
42.0
62.9
56.2
81.2

56.9
63.5
78.7
43.2
71.7
75.6
63.1
65.2
53.3
75.0

11.1
19.2
61.1
29.7
26.0
24.0
24.7
15.0
12.2
25.8

17.7
15.4
48.1
37.0
33.4
37.6
20.3
14.3
14.9
23.4

Oregon ................................................................................
Pennsylvania ......................................................................
South Carolina ....................................................................
Tennessee ..........................................................................
Texas ..................................................................................
Virginia ................................................................................
Washington .........................................................................
West Virginia .......................................................................

46.4
61.3
48.7
68.9
65.9
52.4
69.4
77.2

66.4
60.0
55.2
68.1
55.8
59.6
75.6
80.9

10.4
26.7
21.7
17.2
12.7
26.7
37.5
16.1

21.1
21.6
17.1
11.0
10.7
23.8
34.7
23.5

Other States1 ......................................................................

55.4

52.6

10.6

9.9

United States ......................................................................

60.5

58.3

5.9

5.7

1

Individual state estimates not available for states not shown but are included in Other States.

10

Sheep and Goats Methodology and Quality Measures (March 2023)
USDA, National Agricultural Statistics Service

Information Contacts
Process
Estimation ....................................
Data Collection ............................
Questionnaires ............................
Sampling and Editing ...................
Summary and Estimators .............
Dissemination ..............................
Media Contact and Webmaster ....

Unit
Livestock Branch
Survey Administration Branch
Data Collection Branch
Sampling Editing and Imputation Methodology Branch
Summary Estimation and Disclosure Methodology Branch
Data Dissemination Office
Public Affairs Office

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(202) 720-3570
(202) 720-3895
(202) 720-6201
(202) 690-8141
(202) 690-8141
(202) 720-3869
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Email
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]

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