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Population and Housing Census 2006 - Nigeria

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Abstract --------------------------- The primary mission of the 2006 Population and Housing Census (PHC) of Nigeria was to provide data for policy-making, evidence-based planning and good governance. The Government at all tiers, researchers, the academia, civil society organizations and the international agencies will find the sets of socio-demographic data useful in formulating developmental policies and planning. The 2006 data will certainly provide benchmarks for monitoring the Millennium Development Goals (MDGs). Enumeration in the 2006 PHC was conducted between March 21st and 27th 2006. It was designed to collect information on the quality of the population and housing, under the following broad categories: demographic and social, education, disability, household composition, economic activity, migration, housing and amenities, mortality and fertility. The results of the exercise are being released as per the Commission's Tabulation Plan which began with the release of the total enumerated persons by administrative areas in the country in the Official Gazette of the Federal Republic of Nigeria No.2, Vol 96 of February 2,2009 and followed with the release of Priority Tables that provide some detailed characteristics of the population of Nigeria by State and LGA. Geographic coverage --------------------------- National Analysis unit --------------------------- Individuals Households Kind of data --------------------------- Census/enumeration data [cen] Mode of data collection --------------------------- Face-to-face [f2f] Cleaning operations --------------------------- Census 2006 Processing: The Technology and Methodology:- Unlike the data capture method used for the country’s previous censuses, where information from the census forms are typed into the computer system, data capture for census 2006 was carried out by OMR/OCR/ICR systems where questionnaires are scanned through high speed optical scanners. The choice of the scanning system was because it is faster and more accurate than the data keying method. OMR/OCR/ICR Technology Definition of terms - OMR (Optical Mark Recognition) - This means the ability of the scanning machine to detect pencil marks made on the questionnaires by the Enumerators in accordance with the responses given by the respondents. - OCR (Optical Character Recognition) - This means the ability of the scanning machine to recognize machine printed characters on the questionnaires. - ICR (Intelligent Character Recognition) - This means the ability of the scanner to recognize characters hand written by the Enumerators in accordance with the responses given by the respondents. Processing Procedures of Census 2006 at the DPCs:- Data processing took place in the Commission’s seven (7) Data Processing Centres located in different geographical zones in the country. There was absolute uniformity in the processing procedures in the seven DPCs. (a) Questionnaire Retrieval/Archiving Questionnaires from the fields were taken directly from the Local Government Areas to designated DPCs. The forms on arrival at the DPCs were counted, archived and labeled. Retrieval of the questionnaires at the DPCs were carried out based on the EA frame received from the Cartography Department. Necessary Transmittal Forms are completed on receipt of the Forms at the DPCs. The Transmittal Forms are also used to keep track of questionnaires movement within the DPC. (b) Forms Preparation The scanning machine has been designed to handle A4 size paper. And the Census form being twice that size has to be split into two through the dotted lines at the middle of the form. This forms preparation procedure is to get the questionnaires, for each Enumeration Areas (EAs), ready for scanning. There is a Batch Header to identify each batch. (c) Scanning Each Batch on getting to the Scanning Room was placed on joggers (a vibrating machine)to properly align the forms, and get rid of dust or particles that might be on the forms. The forms are thereafter fed into the scanner. There were security codes in form of bar codes on each questionnaire to identify its genuineness. There was electronic editing and coding for badly coded or poorly shaded questionnaires by the Data Editors. Torn, stained or mutilated forms are rejected by the scanner. These categories of forms were later manually keyed into the system. Re-archiving of Scanned Forms:- Scanned forms were placed in their appropriate marked envelopes in batches, and thereafter returned to the Archiving Section for re-archiving. Data Output from the Scanning Machine:- The OMR/OCR Software interprets the output from the scanner and translates it into an XML file from where it is further translated into the desired ASCII output that is compatible for use by the CSPro Package for further processing and tabulation. Data back-up and transfer:- After being sure that the data are edited for each EA batch in an LGA, data then was exported to the SAN (Storage Area Network) of the Server. Two copies of images of the questionnaires for each EA copied to the LTO tapes as backup and then transferred to the Headquarters. The ASCII data files for each LGA are zipped and encrypted, and thereafter transfer to the Data Validation Unit (DVU) at the Headquarters in Abuja. Data appraisal --------------------------- Data collation and validation:- The Data Validation Unit at the Headquarters was responsible for collating these data into EAs, LGAs, States and National levels. The data are edited/validated for consistency errors and invalid entries. The Census and Survey Processing (CSPro) software is used for this process. The edited, and error free data are thereafter processed into desired tables. Activities of the Data Validation unit (DVU):- Decryption of each LGA Data File Concatenation/merging of Data Files Check each EA batch file for EA completeness within an LGA and State Check for File/Data Structure Check for Range and Invalid Data items Check for Blank and empty questionnaire Check for inter and intra record consistency Check for Skip Patterns Perform Data Validation and Imputation Generate Statistics Report of each function/activity Generate Statistical Tables on LGA, State and National levels.

摘要 --------------------------- 2006年尼日利亚人口与住房普查(PHC)的主要使命是为政策制定、基于证据的规划和良好治理提供数据。各级政府、研究人员、学术界、民间社会组织和国际机构将发现这些社会人口数据集在制定发展政策和规划方面非常有用。2006年的数据无疑将为监测千年发展目标(MDGs)提供基准。2006年PHC的普查于2006年3月21日至27日进行。其设计旨在收集以下广泛类别下的人口和住房质量信息:人口和社会、教育、残疾、家庭构成、经济活动、移民、住房和便利设施、死亡率和生育率。该活动的结果将按照委员会的汇总计划发布,该计划始于2009年2月2日联邦共和国官方公报第2号,第96卷中发布的按行政区域统计的总普查人口数,随后发布了优先表格,这些表格提供了按州和地方政府区域划分的尼日利亚人口的一些详细特征。 地理覆盖范围 --------------------------- 全国 分析单位 --------------------------- 个人 家庭 数据类型 --------------------------- 普查/人口普查数据 [cen] 数据收集方式 --------------------------- 面对面 [f2f] 数据清洗操作 --------------------------- 2006年普查处理:技术和方法 - 与该国以前普查中使用的数据采集方法不同,即从普查表格中键入计算机系统中的信息,2006年普查的数据采集是通过OMR/OCR/ICR系统进行的,其中问卷通过高速光学扫描仪进行扫描。选择扫描系统是因为它比数据键入方法更快、更准确。 OMR/OCR/ICR技术 术语定义 - OMR(光标识别)- 这意味着扫描机能够检测调查员根据受访者的回答在问卷上所做的铅笔标记的能力。 - OCR(光学字符识别)- 这意味着扫描机能够识别问卷上的机器打印字符的能力。 - ICR(智能字符识别)- 这意味着扫描机能够根据受访者的回答识别调查员手写的字符的能力。 2006年普查在数据处理中心(DPC)的处理程序: - 数据处理发生在委员会位于该国不同地理区域的七个(7)数据处理中心。在七个DPC中,处理程序绝对一致。 (a)问卷检索/存档 从现场收集的问卷直接从地方政府区域运送到指定的DPC。到达DPC的表格被计数、存档并贴上标签。 根据从制图部门收到的EA框架检索DPC中的问卷。在收到表格时完成必要的传递表格。传递表格还用于跟踪问卷在DPC内的移动。 (b)表格准备 扫描机被设计成可以处理A4大小的纸张。普查表格的大小是A4的两倍,因此必须通过表格中间的虚线将其分成两部分。这种表格准备程序是为了为每个普查区域(EA)的问卷准备扫描。每个批次都有一个批头以识别每个批次。 (c)扫描 每个批次到达扫描室后,都会放在摇摆机(一种振动机器)上,以正确对齐表格,去除表格上可能存在的灰尘或颗粒。 然后,表格被送入扫描仪。每个问卷上都有安全码形式的条形码,以识别其真实性。对于编码不良或填涂不佳的问卷,数据编辑员进行了电子编辑和编码。扫描仪拒绝了撕破、污染或破损的表格。这些类别的表格后来手动输入到系统中。 扫描后表格的再存档:扫描后的表格被放入适当标记的信封中,然后返回存档部门进行再存档。 扫描机的数据输出:OMR/OCR软件解释扫描仪的输出并将其转换为XML文件,然后进一步转换为与CSPro软件兼容的所需ASCII输出,以便进行进一步处理和汇总。 数据备份和传输:在确保每个地方政府区域(LGA)的每个EA批次的数据都已编辑后,数据随后被导出到服务器的SAN(存储区域网络)。每个EA的问卷图像的副本复制到LTO磁带上作为备份,然后转移到总部。每个LGA的ASCII数据文件被压缩和加密,然后转移到位于阿布贾总部的大数据验证单位(DVU)。 数据评估 --------------------------- 数据汇编和验证:总部的大数据验证单位负责将这些数据汇编到EA、LGA、州和国家层面。数据经过编辑/验证,以消除一致性错误和无效条目。使用普查和调查处理(CSPro)软件进行此过程。编辑无误的数据随后被处理成所需表格。 大数据验证单位(DVU)的活动: 解密每个LGA数据文件 合并/合并数据文件 检查每个EA批次文件在LGA和国家内的EA完整性 检查文件/数据结构 检查范围和无效数据项 检查空白和空问卷 检查记录间和记录内一致性 检查跳过模式 执行数据验证和插补 生成每个功能/活动的统计报告 生成LGA、州和国家层面的统计表格。
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