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18.8 Confidence Interval A measure that tells the possible range within which the true population characteristic lies with a certain level of confidence (usually at 95 percent level).

18.9 Design effect (Deff) A parameter measuring the efficiency of a used sampling plan compared to Simple Random Sampling Without Replacement (SRSWOR).

( ) ( ) , ( ) ( ) srswor srswor var y se y Deff Deft Deff var y se y

=

18.10 Sampling Frame Refers to a list of units from which a sample is to be selected. It must have characteristics to be studied.

18.11 Sampling Unit It is a smallest unit or element, which is the subject of sample selection or a unit of analysis, such as a person, household or an establishment. Sampling unit may be Primary, secondary, etc. depending on the stages of sampling.

18.12 Estimation Refers to the process of estimating population characteristics based on the sample statistics. The characteristics may be any variable associated with a member of the population, such as age, income, employment status and the quantity may be a total, proportion, average and standard deviation.

18.13 Statistical Error The difference between the true population parameters and the estimated statistics from a sample.

18.14 Sampling Error Refers to an inaccuracy in the estimates of the population characteristics which arise due to the sample on which the estimates are made from.

18.15 Non – Sampling Error Refers to inaccuracy which occurs when estimating population characteristics due to defective measurement techniques, mistakes during data collection, processing and interpreting, etc.

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18.16 Sampling Procedure Refers to the approach followed to select sampling units or elements from the population: It includes non – probability sampling or probability sampling.

18.16.1 Non – Probability Sampling Refers to the selection of sampling units without using probability mechanism. It covers a variety of procedures, including the use of volunteers and the purposive choice of elements for the sample on the grounds it is a “representative” of a population.

18.16.2 Probability Sampling Refers to the selection of sampling units by using probability mechanism. An essential requirement for any form of probability sampling is the existence of a sampling frame or population from which the sampled elements are selected from. Probability Techniques widely used are: Simple Random Sampling; Systematic Sampling; Stratified Sampling; Cluster Sampling; Multistage Sampling and Probability Proportional to Size Sampling.

18.17 Simple Random Sampling Refers to the selection of sampling units of size n from the population of size N. In Simple Random Sampling, each element has an equal chance of being selected.

18.18 Stratified Random Sampling (or Stratified sampling) Refers to the method of selecting a sample from a population of size N where the population is firstly sub – divided into k sub – populations called strata; • First, stratify your sampling frame (e.g. divide it into the low, medium, high-income households or males, females depending on your stratification variable). • Second, take a random sample from each stratum (i.e. take random samples from a low- income household, medium income households, high income households, or males, females. The selected random samples will constitute the final sample. (Note: you could also take Systematic samples from respective strata).

18.19 Systematic Random Sampling (or Systematic Sampling) In this sampling method the N units in the sampling frame are arranged in a particular order Suppose N = nk, where n is the sample size and k is an integer, a random number less than or equal to k is selected and thereafter every kth element is selected.

207 18.20 Cluster Sampling Refers to the process of firstly selecting a number of clusters from a sampling frame consisting of all clusters. A study is then carried out to all units in the entire selected clusters. For example, select geographical areas first and within the selected geographical areas, all households are interviewed.

18.21 Multistage Sampling Refers to the process where selection of the sample is carried out in stages. For example, select geographical areas first and within the selected geographical areas, select households to be interviewed.

18.22 Quota Sampling Refers to a method of selecting a sample in which investigator collects information from individuals until the sample size (the quota) is attained.

18.23 Sample Allocation Refers to the process of distributing or allocating a total sample size to different strata, so that a separate sample is selected from each stratum.

18.24 Probability Proportional to Size Sampling Refers to the selection of (both primary and secondary) sampling units based on the sizes of the sampling frames. The process of selecting sampling units follows the principal of Multistage Sampling.

18.25 Primary sampling unit (PSU) Geographical area comprising one or more enumeration areas of the same type (and therefore not necessarily contiguous) that together have at least one hundred dwelling units.

18.26 Sampling Weight Refers to the process of improving survey results by making adjustments for total non- response, to conform to the known population distribution in order to improve precision of sample estimates and analysis of data obtained from a complex sample survey.

18.27 Adjustment for Statistical Purposes A set of procedures employed to improve coverage, classification, timing or valuation of the data, conform to an accounting or recording basis, or address data quality differences in compiling specific datasets.

208 18.28 Administered Item Registry item for which administrative information is recorded in an administration record.

18.29 Administration Record Collection of administrative information for an administered item.

18.30 Administrative Data The set of information collected primarily for administrative purposes, usually by government departments and other organizations. This data is gathered as part of routine record-keeping, management, and operational activities.

18.31 Administrative Source A data holding containing information collected and maintained for the purpose of implementing one or more administrative regulations.

18.32 Bias An effect which deprives a statistical result of representativeness by systematically distorting it, as distinct from a random error which may distort on any one occasion but balances out on the average.

18.33 Code A language-independent set of letters, numbers or symbols that represent a concept whose meaning is described in a natural language.

18.34 Coding The process of converting verbal or textual information into codes representing classes within a classification scheme, to facilitate data processing, storage or dissemination.

18.35 Cold Deck The imputation technique used during data editing where missing or inconsistent values are calculated or derived from other information about the household or person. Synonym logical imputation. See hot deck.

18.36 Coverage The definition of the population that statistics aim to cover.

18.37 Coverage Error Error caused by a failure to adequately cover all components of the population being studied, which results in differences between the target population and the sampling frame.

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18.38 Data A representation of facts, concepts, or instructions in a formal manner, suitable for communication, interpretation, or processing by humans or by automatic means.

18.39 Data Confidentiality A property of data, usually resulting from legislative measures, which prevents it from unauthorized disclosure.

18.40 Data Editing Activity aimed at detecting and correcting errors, logical inconsistencies and suspicious data.

18.41 Data Imputation The procedure of entering a value for a specific data item, where the response is missing or unusable.

18.42 Data Processing The operation performed on data in order to derive new information according to a given set of rules.

18.43 Hot deck The imputation technique used in data editing where the source for imputed values is constantly updated from valid response combinations encountered during processing, thus reflecting the reality of the households and persons most recently processed. Synonym: dynamic imputation. See cold deck.

18.44 Item response rate The ratio of the number of eligible units responding to an item to the number of responding units eligible to have responded to the item.

18.45 Macro data Observation data gained by a purposeful aggregation of statistical micro data.

18.46 Matching An operation whereby households and individuals enumerated during a census and a post- enumeration survey are compared for similarities and differences.

210 18.47 Metadata Data about data, that refers to the definitions, descriptions of procedures, system parameters, and operational results which characterize and summaries statistical programs.

18.48 Micro data Observation data collected on an individual object or statistical unit.

18.49 Probing The technique that is used to obtain a complete and relevant response by asking further questions.

18.50 Questionnaire A group or sequence of questions designed to elicit information upon a subject, or a sequence of subjects, from an informant.

18.51 Random Number A number allocated to a statistical unit that is mainly used for sampling purposes.

18.52 Reference Period The period of time (day, week, month, or year) for which information is relevant.

18.53 Refusal Situation when a household or individual refuses to answer the questions or complete the questionnaire.

18.54 Respondent The person or organization that answers the questions or completes the questionnaire.

18.55 Statistics
Is a process that involves scientific methods of collecting, organizing, processing, analysing, presenting, and interpreting data.

18.56 Official statistics Is the statistics produced, validated, compiled and disseminated by or under the authority of the National Statistics Offices.

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21. National Accounts Statistics: Main Aggregates and Detailed Tables, 2014 Part V, United Nations New York, 2015. 22. United Nations: System of National Accounts 2008, New York, 2009. 23. United Nations Development Programme (UNDP). Gender and Indicators Overview Report July, (2007): www.undp.org.

212 24. United Nations. International Classification for Time Use Statistics, 2016. 25. United Nations, Department of Economic and Social Affairs, Statistics Division, International Recommendations for Industrial Statistics 2008, New York, 2009 26. United Nations, Department of Economic and Social Affairs, Statistics Division, International Series M No. 4/Rev.4 Standard Industrial Classification of All Economic Activities Revision 4, New York, 2008. 27. United Nations Industrial Development Organization, Industrial Statistics Guidelines and Methodology, Vienna 2010. 28. JMP Indicators for monitoring WASH in Households, Health Care Facilities, Schools, UNICEF/WHO 29. Tanzania Demographic and Health Survey and Malaria Indicators Survey (TDHS-MIS) Report, 2022 30. Tanzania Household Budget Survey (HBS) Reports, 2017/18

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