FAQs Pertaining to Sample Design Section, PBS, Islamabad

Define the term Population? #

Aggregate of all the individuals sharing some common characteristics is known as Population. For example, Population of all the students enrolled in Statistics department of a particular university, Population of all the employees working in Pakistan Bureau of Statistics #

Define the main types of Population? #

There are two types of Population #

     i.        Finite Population #

    ii.        Infinite Population #

Finite Population #

Finite population comprises of known and countable number of elements such as total employees in a company #

Infinite Population #

Infinite population characterized by an uncountable and potentially limitless number of elements for example the numbers between 1 and 2, stars in milky way galaxy. #

Define the term sample? #

Sample is a subset of population that possesses same characteristics as the population from which it is taken from. #

Define the term sampling unit? #

An eligible member for which the required information is collected is called the sampling unit. Whereas the aggregate of the sampling units comprises the sample size.

Define the term Target population #

 The population about which sample is drawn is known as target population. For example, if we want to draw a sample of university students then all university students will be our target population. #

Define the term Sampled Population? #

The subset of target population is known as sampled population. For example, if target population is students of university then sampled population will be specific group of university students you selected as a sample. #

Discuss the difference between Target Population and Sampled Population? #

Target Population is the whole group of interest, while Sampled Population is the subset of the target population that has at least some chance of being sampled.

Define the term sampling? #

The process of collection of sample from population is known as sampling. There are two types of sampling #

i-            Sampling with replacement        ii-  Sampling without replacement #

i.   Sampling with replacement #

It is method of sample selection in which individual elements of population are selected from population for inclusion in sample and after each selection the selected element is returned into population from which it was selected. Single individual can be selected more than once. #

ii.   Sampling without replacement #

It is method of sample selection in which individual elements of population are selected from population for inclusion in sample and after each selection the selected element is not returned into population from which it was selected making it impossible for single individual to be selected again in a sample

Name some common techniques used for sample selection? #

There are three most common techniques for the selection of sample #

i-            Random number table Sample selection #

ii-           Computer assisted Sample selection #

iii-          Lottery Method of Sample Selection #

i.   Random number table selection #

In this method each individual in the population is assigned a unique number, then Random Number Table is used for the selection of desired sample ensuring random and unbiased sample #

ii.   Computer Assisted Selection #

In this method computer programs or software based in random number table are used for the selection of desired sample #

iii.  Lottery Method of Sample Selection #

It is sometimes called as lottery method. Population Items are tagged with a unique number and then these tagged numbers are put into a bowl, then sample is selected by choosing these tagged number randomly.

Define the term sampling Frame? #

Sampling frame consists of all the individuals that make up the entire population. It serves as base to draw a sample from the population and ensures sample is representative of the population.

Define the term Census? #

The complete and comprehensive enumeration/count of all the individuals, units or element in the population is known as Census. #

Define the term sample Survey? #

Meaning of the survey is to gather information as per certain need. If this information is gathered by using sampling, then the process in known as sample survey.

Write down the main steps taken for the successful survey. #

Following are steps taken for a successful survey #

     i.        Clearly state the purpose/Scope of the survey #

    ii.        Define Target Population #

   iii.        Calculation of sample size and Allocation #

   iv.        Sample Selection by using suitable sampling technique #

    v.        Analyze the data and summarize the results #

Define the term sample design #

It is the process which starts from planning of selection of sample that is representative of population and ends on drawing and summarizing results from that selected sample is known as sample design.

Differentiate between Sampling Errors and Non Sampling Errors? #

Sampling errors #

The difference between sample statistics and Population parameter is known as sampling error. It can be negative or positive. Sampling error can be reduced by increase sample size. It cannot be completely eliminated. #

Non Sampling errors #

These errors occur it encompasses all the errors in a survey which are not related to process of collection of sample. For example, coverage error, non-response, haphazard selection, erroneous sampling frame. Increasing sample size has no effect on reduction of non-sampling error. #

Define the term relative error? #

It is percentage deviation of observed value from true value. In other words, it is percentage ratio of sampling error to true value of population parameter.

Define the term sampling Bias? #

It is related to sampling process. It is cumulative error which increase with increase in sample size. It can result from erroneous sampling methods or data collection procedures.

Define the term Probability or Random Sampling? #

If probability of selection of each and every unit of population is known prior to the selection of the sample, then the process of selection from such population is known as probability sampling or Random sampling #

Name the types of Probability sampling? #

There are four primary, random (probability) sampling methods. These methods are #

i.             Simple Random Sampling #

ii.            Systematic Random Sampling #

iii.          Stratified Random Sampling #

iv.          Cluster Random Sampling #

Define the term Simple Random Sampling (SRS) #

Simple random sampling is the randomized selection of a small segment of individuals or members from a whole population. It provides each individual or member of a population with an equal and fair probability of being chosen. The simple random sampling method is one of the most convenient and simple sample selection techniques. SRS is used when units of Population from which sample is intended to be selected are homogeneous

Define the term Systematic Random Sampling (SYS)? #

Systematic sampling is the selection of specific individuals or members from an entire population. The selection often follows a predetermined Sampling Interval (k=Total Population/Desired sample size = N/n). the first unit is selected from random number table and remaining units are selected as follows: #

First unit (Random number), Second unit (K+I^st Unit), Third unit ( k+ 2^nd Unit) +………… #

Define the term Stratified Random Sampling? #

Stratified Random sampling, which includes the partitioning of a population into Non overlapping subclasses with notable distinctions and variances. Each unit within each subclass are homogeneous, sample is selected from these sub groups/Subclasses. The stratified sampling method is useful, as it allows the researcher to make more reliable and informed conclusions by confirming that each respective subclass has been adequately represented in the selected sample.

Define the term Cluster Random Sampling? #

Cluster sampling, includes dividing a population into subclasses which are not overlapping but homogeneous. Each of the subclasses should portray comparable characteristics to the entire selected sample and within each subclass units are heterogeneous. This method entails the random selection of a whole subclass, as opposed to the sampling of members from each subclass. This method is ideal for studies that involve widely spread populations.

Define the meaning of Multistage sampling? #

In multistage sampling samples selected in different stages. The unit selected in this technique does not remains the same during the process of sampling. For example, if we select a sample of divisions (first stage) and then we select a sample n2 of Districts (Second stage) after selecting Districts we select a sample n3 of villages (Third stage) finally we select sample n4 of households then the process will be known as Multistage sampling.

Define the term Multiphase sampling? #

Multi-phase sampling is a type of sampling design in which a sample is selected in various phases. In this technique unit of selection remains the same throughout all the phases of sample selection. For example, if a company is looking to collect a sample of 6 feet tall people having master degree in Physics and living with 10Km radius of the location where company is situated. In first phase company collects sample of 6 feet tall people. In second phase sample of all six feet tall people having master degree in physics is collected. In third phase a sample of 6 feet tall people having master degree in Physics living within 10 Km radius of the location of the company. #

In Pakistan Demographic and Health Survey (PDHS) In first phase households are selected from each PSU in urban and rural domain. In second Phase from the selected sample of households, a systematic subsample of one in three households is chosen. #

Explain the difference between Multistage and Multiphase Sampling? #

In Multiphase sampling same units are used at each phase while in Multistage sampling different units are used in each stage. #

Define the term non Probability sampling #

Non-probability sampling is a sampling method where the selection of individuals from the population is not based on random chance. In this approach, not every element in the population has a known, non-zero chance of being included in the sample. The methods used for non-probability sampling often involve subjective judgment or convenience, and the resulting sample may not be representative of the entire population

Name the types are these in Non-Probability Sampling? #

Types of non-probability sampling methods include: #

i.             Purposive Sampling #

ii.            Quota Sampling #

iii.          Snowball Sampling #

iv.          Convenience Sampling #

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Define the term Purposive Sampling? #

purposive sampling, also called judgment sampling or authoritative sampling, is a non-probability sampling technique in which the sample members are chosen only on the basis of the researcher’s knowledge and judgment.

Define the term Quota Sampling? #

The quota sampling method is similar to stratified sampling, and it selects a sample from a population that has been divided into subgroups. However, unlike stratified sampling, which relies on the random selection of each subgroup, quota sampling uses a convenience method within each subgroup

Define the term Convenience Sampling? #

Convenience sampling is a non-probability sampling technique where researchers select participants based on their ease of access or availability. This method involves choosing individuals who are readily accessible, convenient, or easy to reach, rather than using a random or systematic approach. While convenience sampling is convenient for researchers, it may introduce biases because the sample may not accurately represent the entire population due to the lack of randomness in participant selection.

Define the term coefficient of Variation (C.V)? #

The coefficient of variation (CV) is a statistical measure used to express the relative variability of a set of data points compared to their mean. It is calculated by dividing the standard deviation of the data by the mean and then multiplying by 100 to express the result as a percentage. The coefficient of variation is particularly useful when comparing the variability of different datasets with varying units or scales, providing a standardized measure of dispersion relative to the mean. A lower CV indicates lower relative variability, while a higher CV suggests higher relative variability.

Discuss the role does the coefficient of variation play in assessing the precision of survey estimates at the Pakistan Bureau of Statistics? #

The coefficient of variation helps assess the relative variability of survey estimates, with a lower value indicating higher precision and a more reliable estimate

How you allocate sample size for the survey? #

Generally, Allocation of sample size for a particular sample survey among ultimate strata is made using Proportional allocation methodology.

How you determine the sample size for the survey? #

Generally, he different estimation formulas are used for computation of sample size at desired level of confidence with certain margin of errors. Consequently, sample size is fixed keeping in view the available resources and time constraints.

Which sampling technique is used by PBS for the ongoing sample surveys? #

Generally, two or three stage stratified random sampling technique is used.

Define the term Quick Count Technique? #

The “Quick Count” is the process of counting structures, households, dwellings, establishments, industries, within a demarcated block by going around without undertaking listing.

Define the term Listing Technique? #

The “Listing” is the process of (Getting started from North West corner of a block or some prominent point/landmark, moving clockwise, the closing point of the sector will coincide with starting point) listing structures, households, dwellings, establishments, industries, within a demarcated block by “asking” from the respondents on door to door.

When list of Enumeration Blocks was last updated? #

The Urban Area frame was updated in the year 2023 and the lists of villages/mouzas/dehs published by Population Census Organization as a result of Population & Housing Census (P&HC)-2023.

Define the term Enumeration Block (EB)? #

All the urban and rural areas comprising cities/towns/Mauzas/Dehshave been divided into small compact areas known as Enumeration blocks. EB usually have 200-250 houses on the average, with well-defined boundaries and maps.

Define the term Secondary Sampling Unit? #

The listed households of sample PSUs are considered Secondary Sampling Units (SSUs).

Define the term Primary Sampling Unit? #

Primary Sampling unit is a geographical urban/rural area containing 200-250 households on the average, which is generally called as Enumeration block.

All the Geographical areas notified by the respective provincial Government authorities as urban areas is called as on urban areas while rest is rural areas. The blocks formed in these two domains are called urban and rural PSUs. In both Rural and Urban domains, the enumeration blocks are taken as Primary Sampling Units (PSUs).

How does the one can determine the optimal sampling interval in systematic random sampling? #

Generally, the sampling interval in systematic random sampling is determined by dividing the total population by the desired sample size, ensuring an equal chance of selection for each unit

Explain the role of computer-assisted sampling in enhancing the efficiency and accuracy of sample selection #

Computer-assisted sampling utilizes software and algorithms for sample selection, enhancing efficiency and reducing human bias in the process

In the context of sample surveys, what considerations are taken into account when defining the scope and purpose of a survey? #

Defining the scope and purpose involves considerations such as the specific information needed, target population, and the practical constraints of resources and time #

How one can address the challenges related to non-response in its surveys? #

Non-response challenges are mitigated through effective communication strategies, follow-up procedures, and statistical adjustments to account for potential biases.

How one can manage the trade-off between a large sample size for increased precision and the associated resource constraints? #

The trade-off is managed by careful consideration of available resources, statistical techniques, and a balance between precision and practical limitations.

Point out the factors influence the decision to use stratified random sampling over other sampling methods in specific survey scenarios? #

Factors such as heterogeneity within the population and the need for precise estimates in subgroups influence the decision to use stratified random sampling.

Discuss the role that the sampling frame plays in the accuracy of sample selection, and how is it established for different populations? #

The sampling frame is crucial as it comprises all individuals in the population. It ensures representativeness, and for diverse populations, it is established through comprehensive lists, census data, or geographic mapping

Explain the concept of oversampling and its potential benefits or drawbacks in sample surveys? #

Oversampling involves intentionally selecting more individuals from certain subgroups. It can enhance precision in estimating characteristics of specific groups but may increase survey costs and complexity

How one can handle the issues related to coverage error in sample surveys, particularly in diverse and dynamic populations? #

Addressing coverage error involves updating sampling frames regularly, employing effective enumeration techniques, and adjusting estimates to account for underrepresented segments of the population

Discuss the importance of pilot studies in the sample design process and how they contribute to the overall success of a survey. #

Pilot studies allow for testing survey instruments, identifying potential issues, and refining procedures before the main survey. They contribute to the reliability and validity of the survey. #

Discuss the measures one can take to ensure the confidentiality and privacy of respondents’ information during sample surveys? #

By employing strict confidentiality protocols, anonymizing data, securing storage, and limiting access. Legal frameworks also protect respondents’ privacy.

Explain the concept of response bias and how one can minimizes its impact in survey results. #

Response bias occurs when respondents provide inaccurate information. It can be addressed through careful survey design, effective communication, and quality control measures.

In the case of non-probability sampling methods, discuss situations where purposive sampling might be more suitable than other non-probability techniques. #

Purposive sampling is appropriate when specific characteristics or expertise are essential for the study. It is useful in qualitative research or when studying rare phenomena.

How one can adjust the potential biases introduced by non-sampling errors in the analysis and interpretation of survey results? #

Statistical techniques, such as weighting and imputation, are applied to minimize biases introduced by non-sampling errors, ensuring the reliability of the survey results.

Explore the role of technology, such as mobile data collection and online surveys, in modernizing and improving the efficiency of sample surveys #

Technology enhances data collection speed, accuracy, and accessibility. Mobile data collection and online surveys streamline processes, reduce errors, and facilitate real-time data analysis.

How one can address challenges associated with stratification in stratified random sampling, especially when dealing with highly heterogeneous populations? #

Stratification challenges are managed by carefully defining strata based on relevant characteristics, ensuring each stratum is internally homogenous, and applying appropriate sampling techniques to capture the population diversity

Explain the concept of “weighting” in the context of survey sampling, and how does it contribute to adjusting for different probabilities of selection? #

Weighting assigns different values to sampled units based on their probability of selection. It helps compensate for underrepresented or overrepresented groups, ensuring the final results are reflective of the entire population.

In the context of sample surveys, discuss the impact of the mode of data collection (e.g., face-to-face interviews, telephone surveys, online surveys) on response rates and data quality. #

The mode of data collection influences response rates and data quality. Face-to-face interviews may have higher response rates but can introduce interviewer bias, while online surveys offer convenience but may face nonresponse challenges. #

Discuss the considerations that can be taken into account when determining the sampling design for longitudinal studies compared to cross-sectional studies? #

Longitudinal studies require careful consideration of sample retention, potential attrition, and changes in the population over time. Sampling designs must account for these dynamics to ensure accurate and meaningful results.

Define the role of sampling frame completeness in the research process. #

A complete sampling frame, encompasses all elements of the population of interest, ensures that the selected sample accurately represents the entire population.

How one can handle situations where certain subgroups in the population are difficult to reach or have low response rates in sample surveys? #

Specialized outreach strategies, targeted communication, and incentives may be employed to improve participation from hard-to-reach subgroups. Adjustments and weighting may also be applied to mitigate biases. #

Discuss the role of ethical considerations in the sample design process, particularly when dealing with vulnerable or sensitive populations. #

Ethical considerations involve obtaining informed consent, ensuring confidentiality, and safeguarding vulnerable populations. The sample design must prioritize participant well-being and adhere to ethical guidelines and standards.

Discuss the steps that can be taken to ensure the training and standardization of survey enumerators to maintain consistency and reliability in data collection? #

Rigorous training programs, detailed protocols, and ongoing supervision are implemented to ensure enumerators are well-prepared, standardized, and consistently apply survey procedures, enhancing the reliability of data collection.

In the context of Stratified random sampling, explain the challenges and benefits associated with the selection of clusters, especially when dealing with geographically dispersed populations. #

Challenges in Stratified sampling include potential clustering effects and increased variability. Benefits include cost-efficiency and practicality, particularly in geographically dispersed populations where Strata provide a more manageable unit of sampling.

Discuss the precautions that should be taken when using Stratified Random Sampling? #

Stratified Random Sampling involves selecting participants based on pre-defined quotas, such as age or gender. Researcher should ensure that the selected quotas accurately reflects the population’s diversity to maintain the sample representativeness.

In the case of non-probability sampling, such as snowball sampling, elaborate on the potential advantages and challenges it presents in obtaining diverse perspectives in research. #

Snowball sampling allows for reaching hidden populations but can introduce bias. Advantages include accessing hard-to-reach groups, while challenges involve the lack of randomness and potential for oversampling certain characteristics.

How do outliers or extreme values impact the survey research? #

Outliers in survey research can distort analysis, leading to skewed results and reduced generalization. These extreme values impact relationships between variables, potentially leading to misleading conclusions about the population.

Discuss the role of cognitive interviewing in the pre-testing phase of survey instrument development and its contribution to refining questions for cultural sensitivity. #

Cognitive interviewing involves testing questions with respondents to identify comprehension issues or cultural sensitivities. It ensures questions are clear, culturally appropriate, and yield reliable responses.

In the context of probability sampling, explore the considerations and challenges involved in implementing systematic random sampling in large and dynamic populations. #

Systematic random sampling requires a fixed sampling interval. Challenges in large and dynamic populations include maintaining randomness and adjusting to changes in population size or distribution.

Explain the concept of “nonresponse follow-up” in sample surveys and its importance in mitigating nonresponse biases for more accurate results. #

Nonresponse follow-up involves contacting no respondents to encourage participation. It’s crucial for reducing nonresponse bias, ensuring a more representative sample, and improving the accuracy of survey results.

Discuss the significant consequences of non-response in research? #

A non-response in research has significant consequences, including the introduction of bias, limitations in generalizability, potentially underestimation or overestimation of certain characteristics of population and risk of invalid conclusions.

How does the Pakistan Bureau of Statistics leverage geographic information systems (GIS) in sample design? #

GIS Lab plays a crucial role by providing maps and descriptions of Primary Sampling Units (PSUs) selected and allocated by the sample design Section.

Discuss the potential advantages and challenges associated with using probability proportional to size (PPS) sampling in surveys #

PPS sampling ensures proportionate representation of strata based on their size, offering efficiency. Challenges include accurate determination of stratum sizes and potential complexities in implementation.

Define the significance of a representative sample in the context of sample design for surveys? #

A representative sample ensures that survey results accurately reflect the characteristics of the entire population, enhancing the reliability and validity of the findings.

In the context of sample surveys, discuss the benefits of using a stratified random sampling. #

Stratified random sampling ensures that subgroups with distinct characteristics are adequately represented, leading to more precise estimates and reliable insights into the entire population. #

Explain the concept of “response rate” in sample surveys, and why is it an essential metric for assessing survey quality? #

Response rate is the proportion of completed surveys out of the total contacted. It is crucial for assessing the reliability and generalizability of survey results, indicating the level of nonresponse bias.

In the context of stratified random sampling, discuss the considerations involved in determining stratum boundaries and ensuring homogeneity within strata. #

Stratum boundaries are defined based on relevant characteristics, aiming for internal homogeneity. Careful consideration of population characteristics helps create meaningful and distinct strata.

How one can ensure the fairness and transparency of the sample selection process in its surveys? #

Fairness and transparency are maintained through randomization processes, clear documentation of sampling procedures, and adherence to predefined protocols, ensuring an unbiased selection process.

Elaborate characteristics of Sampling Frame? #

Following are characteristics of sampling Frame #

·       Sampling Frame must encompass the entire population of interest #

·       Accuracy and uniqueness in the information with sampling frame is crucial #

·       Sampling Frame must be regularly updated to address changes occur within the population #

In the context of sample surveys, discuss the trade-offs involved in choosing between a simple random sample and a systematic random sample. #

A simple random sample offers simplicity but may be impractical for large populations. Systematic random sampling provides efficiency but requires a well-defined sampling interval, influencing the choice based on survey objectives.

Define Rare Population Surveys #

In rare Population Surveys, uncommon groups with in population such as rare disease, drug users, endangered species etc. are studied. #

Biases related to interviewer characteristics are minimized through rigorous training, standardized protocols, and monitoring, ensuring consistent and unbiased data collection.

Explore the role of auxiliary information in improving the precision of survey estimates during the sample design process. #

Auxiliary information, such as demographic data, is utilized to inform the selection of an efficient sample, improving the precision and reliability of survey estimates.

Discuss the considerations involved in determining the appropriate level of stratification for surveys. #

The appropriate level of stratification is determined based on the heterogeneity within the population, aiming for strata that capture meaningful variations and ensure precise estimates.

Define the role which randomization plays in minimizing biases during the sample selection process, and how is it implemented in surveys #

Randomization ensures an equal chance of selection for each unit, minimizing biases. It is implemented through random number tables, computer algorithms, or other randomized methods during the sample selection process

Explain the concept of “probability proportional to size” (PPS) sampling and its application in surveys conducted by statistical agencies. #

PPS sampling involves allocating higher probabilities of selection to units with larger estimated sizes. It helps ensure proportionate representation of strata based on their estimated sizes.

Discuss the challenges might arise if the sampling frame is inaccurate? #

An inaccurate sampling frame can lead to selection bias; as certain population elements may be excluded or misrepresented.

How does stratified random sampling enhances representation #

Stratified Sampling divides the population into subgroups or strata based on certain characteristics. By ensuring representation from each stratum, it increases likely hood of capturing diverse characteristics in the sample

Discuss the considerations involved in determining the optimal sample size for a survey, balancing precision and resource constraints. #

Optimal sample size is determined by considering the desired level of precision, available resources, and the practical constraints of time and budget, ensuring a balance that meets survey objectives.

Define the role of the concept of “coverage error” in assessing the accuracy and completeness of a sampling frame for surveys? #

Coverage error reflects discrepancies between the sampling frame and the actual population, and addressing it is crucial for ensuring that the selected sample is representative and unbiased.

In the context of sample surveys, explore the potential advantages and challenges associated with using stratified random sampling in comparison to other sampling methods. #

Stratified random sampling provides more precise estimates for subgroups, but challenges include the need for accurate stratification and potential complexity. The method is chosen based on the survey’s objectives and population characteristics.

Discuss the role of a sampling fraction in sample design, and how does it influence the representativeness of survey results? #

The sampling fraction is the ratio of the sample size to the population size. It affects the precision of estimates; a smaller fraction may reduce costs but could lead to less representative results

How one can handle outliers in the determination of stratum boundaries during the stratified random sampling process? #

Outliers are carefully examined, and their impact on stratum characteristics is assessed. Stratum boundaries are adjusted if outliers significantly influence the homogeneity within strata. #

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How sampling plays vital role in research studies? #

Sampling plays vital role in research studies as it allows researchers to draw conclusions about a population by studying its subset, or sample by making the study more feasible and cost effective #

Discuss the steps one can take to minimize the impact of non-sampling errors on survey estimates during the data analysis phase? #

Non Sampling errors can be reduced by following ways #

·       Reliable data collection tools #

·       Ensuring through training of enumerators for data collection #

·       Implementing checks for accuracy throughout the data collection process. #

Define the term pilot study? #

pilot study is small scale research initiative conducted before the main study. its purpose is to test and refine research instruments, procedures and methods. it helps researchers in making necessary adjustments, ultimately enhancing the quality and validity of the main research.

Why is representative sample crucial for research validity? #

Representative sample mirrors the key characteristics of the entire population, enhancing the validity and generalization of research findings to broader context #

Why is Pilot Study important for full-scale research? #

A Pilot Study is crucial as it helps researchers test and refine their research methods, identify potential issues, and insure the feasibility of their study before conducting their full-scale research. It allows for adjustments, improves study design, and enhances the overall quality of the research, ultimately contributing to more reliable and valid results.