Business Statistics Quiz: Sampling And Survey Bias

20 questions · exam conditions

0:00

Sampling And Survey BiasQuestion 1 of 20

A consumer goods company wants to assess brand loyalty. They obtain a list of all 1 million households that have purchased their product in the last year. They number the households from 1 to 1,000,000, randomly select a starting number between 1 and 200, and then select that household and every 200th household thereafter. What is this sampling method called, and what is its main advantage?

Simple Random Sampling; its main advantage is that it is the easiest to implement.

Stratified Sampling; its main advantage is ensuring representation of subgroups.

Cluster Sampling; its main advantage is reducing costs when the population is geographically dispersed.

Systematic Sampling; its main advantage is that it is often easier to implement than simple random sampling while still being a probability method.

← Back to quizzes

Business Statistics Quiz

Business Statistics Quiz: Sampling And Survey Bias

Practice Sampling And Survey Bias in Business Statistics with focused quiz questions that help you check what you know, review explanations, and build confidence with test-style prompts.

What this quiz covers

This quiz focuses on Sampling And Survey Bias, giving you a quick way to practice the rules, question types, and explanations that matter most for Business Statistics.

How to use this quiz

Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

All questions

Question 1

Simple Random Sampling; its main advantage is that it is the easiest to implement.
Stratified Sampling; its main advantage is ensuring representation of subgroups.
Cluster Sampling; its main advantage is reducing costs when the population is geographically dispersed.
Systematic Sampling; its main advantage is that it is often easier to implement than simple random sampling while still being a probability method. (correct answer)

Explanation: This method is systematic sampling. It involves selecting a random starting point and then picking every k-th element in the population. A key advantage is its simplicity and ease of implementation, especially with large, ordered lists. It can provide a good approximation of a simple random sample and is a valid probability sampling method, provided the list does not contain any hidden periodic patterns that align with the sampling interval.

Question 2

A business consulting firm wants to study employee productivity across different industries. They design a survey to be distributed through professional networking platforms, targeting users who list specific job titles (managers, analysts, specialists) in their profiles. The survey asks detailed questions about work hours, output metrics, and efficiency measures.

Based on the passage above, if this survey methodology produces results showing higher productivity levels than government labor statistics for the same industries, which sampling bias most likely explains this discrepancy?

Volunteer bias, where individuals who choose to participate in productivity surveys are inherently more motivated and productive employees than those who ignore such surveys
Self-reporting bias, where survey respondents systematically overestimate their productivity levels and work output when responding to professional surveys that might affect their reputation
Title bias, where targeting specific job titles excludes entry-level workers, administrative staff, and other roles that might have different productivity patterns than managers and specialists
Platform bias, where professional networking users represent more career-focused and ambitious workers compared to the general employee population across these industries (correct answer)

Explanation: When analyzing sampling bias in survey research, you need to consider how the sampling method systematically excludes certain groups, creating results that don't represent the broader population. The key insight here is that this survey uses professional networking platforms to recruit participants. These platforms attract a specific subset of workers: those who are career-focused, actively networking, and invested in their professional development. This creates a fundamental sampling bias because the platform itself pre-selects for more ambitious, engaged employees who likely have higher productivity levels than the general workforce. Answer D correctly identifies this platform bias. Professional networking users represent a more motivated segment of the workforce compared to all employees in these industries, naturally leading to higher reported productivity than government statistics that capture the entire worker population. Let's examine why the other options miss the mark. Answer A (volunteer bias) assumes participation is driven by high performers wanting to showcase productivity, but the passage doesn't suggest this self-selection pattern. Answer B (self-reporting bias) would affect how people report their productivity but wouldn't necessarily explain why this specific survey shows consistently higher results than government data. Answer C (title bias) focuses on excluding certain job roles, but managers, analysts, and specialists span various productivity levels—the bias isn't about job titles but about the type of people using networking platforms. Remember: When evaluating sampling bias, always trace back to who gets included versus excluded by the sampling method. The recruitment platform often determines your sample characteristics more than the survey content itself.

Question 3

A hotel chain wants to assess customer satisfaction by analyzing online reviews from the past six months. They collect 3,200 reviews from their website, travel booking sites, and social media platforms. The analysis shows that 78% of reviews are positive (4-5 stars), leading management to conclude that customer satisfaction is high. However, a parallel analysis of internal guest services records reveals that 23% of stays resulted in complaint calls or emails. Which statement best explains this contradiction and its implications for decision-making?

Sample size discrepancy explains the difference, since 3,200 online reviews may represent a smaller proportion of total stays than the guest services complaint rate suggests
Platform bias explains the discrepancy, since customers who use different review platforms have varying standards for satisfaction and different motivations for sharing feedback publicly
Temporal bias accounts for the contradiction, since online reviews reflect experiences over six months while guest services complaints represent more immediate reactions to problems
Voluntary response bias in online reviews creates systematic overrepresentation of extremely satisfied and extremely dissatisfied customers, while moderately dissatisfied customers contact guest services instead (correct answer)

Explanation: When you encounter contradictory data sources in business statistics, the key is identifying which type of sampling bias might explain the discrepancy. This question tests your understanding of how different data collection methods can yield conflicting results about the same phenomenon. The contradiction here stems from voluntary response bias in online reviews. Option D correctly identifies that customers who voluntarily post online reviews tend to represent the extremes—those who are either extremely satisfied (leading to glowing reviews) or extremely dissatisfied (leading to scathing critiques). Meanwhile, moderately dissatisfied customers—those annoyed enough to complain but not motivated to write public reviews—typically contact guest services directly. This creates two different samples: online reviews skewed toward positive experiences, and guest services records capturing the "middle ground" of dissatisfaction. Option A incorrectly focuses on sample size when the issue is sample composition, not quantity. Option B misses the mark by suggesting platform differences in standards rather than recognizing the fundamental bias in who chooses to review publicly. Option C assumes a timing difference, but both data sources cover similar periods—the bias is about response behavior, not timing. The 78% positive online reviews and 23% complaint rate actually align perfectly when you account for this bias pattern. The online reviews capture the extremes while missing the moderate dissatisfaction that drives guest services contacts. Remember: When analyzing conflicting data sources, always ask "who is motivated to respond to each method?" Voluntary response bias consistently skews toward extreme opinions, making it unreliable for measuring true population sentiment.

Question 4

A retail company wants to assess customer satisfaction across its 500 stores nationwide. They decide to survey customers at 25 stores located within 10 miles of corporate headquarters because these stores are easily accessible for follow-up interviews. After collecting responses, they find that 78% of customers rate their experience as 'excellent.' Which combination of sampling issues most significantly threatens the validity of generalizing this result to all 500 stores?

Convenience sampling bias and geographic clustering, since headquarters-proximate stores may have different management oversight and customer demographics than distant locations (correct answer)
Undercoverage bias and response bias, since only current customers are surveyed while potential customers and dissatisfied former customers are excluded from consideration
Selection bias and measurement error, since the 25 stores represent only 5% of total stores and customer satisfaction scales are inherently subjective measures
Voluntary response bias and social desirability bias, since customers choose whether to participate and may provide artificially positive ratings to avoid confrontation

Explanation: The primary threats are convenience sampling (selecting easily accessible stores rather than a representative sample) and geographic clustering (all selected stores are near headquarters, creating systematic differences in management attention, resource allocation, and likely customer demographics). Choice B incorrectly focuses on undercoverage of non-customers, but the goal is to survey current customers. Choice C mentions sample size being small, but 25 stores could be adequate if properly selected; subjectivity isn't a sampling bias. Choice D assumes voluntary response, but the stem doesn't indicate customers self-selected into the survey.

Question 5

An online retailer wants to estimate return rates for clothing purchases. They randomly sample 1,000 transactions from their database and plan to survey customers about their return behavior. However, they realize that 40% of the sampled transactions used guest checkout (no account required), making those customers difficult to contact. The retailer decides to replace these guest transactions with an equal number of randomly selected transactions from registered account holders. What bias does this substitution introduce, and why is it problematic?

Convenience bias, because the retailer chose the easier option of surveying account holders rather than investing effort to contact guest checkout customers through alternative methods
Selection bias, because registered account holders represent only 60% of the original sample, making the final sample size too small to generate statistically reliable estimates
Coverage bias, because the final sample systematically excludes guest checkout customers who may have fundamentally different return patterns due to reduced purchase commitment and anonymity (correct answer)
Replacement bias, because substituting transactions changes the temporal distribution of purchases, with newer transactions potentially having different return rates than older ones

Explanation: When analyzing sampling problems, focus on how changes to the original sample affect the representativeness of your target population. The key question is: does your final sample still accurately reflect the group you're trying to study? The correct answer is C because this substitution creates coverage bias. The retailer's original goal was to estimate return rates for all clothing purchases, which includes both guest checkout and registered account transactions. By systematically removing all guest checkout customers and replacing them with more registered users, they've fundamentally altered who their sample represents. Guest checkout customers likely behave differently—they may be more price-conscious, less loyal to the brand, or more willing to make impulse purchases they later return. The anonymity and reduced commitment of guest checkout could lead to significantly different return patterns that will now be completely missed. Option A incorrectly identifies this as convenience bias. While the retailer did choose an easier path, convenience bias refers to sampling whatever's most accessible rather than following a proper sampling plan. Here, they're still using random sampling—just from the wrong population. Option B misunderstands the issue. The sample size remains 1,000, so statistical reliability isn't the problem. The issue is sample composition, not size. Option D focuses on timing effects, but there's no indication that the replacement transactions come from different time periods than the originals. Remember: coverage bias occurs whenever your sampling frame systematically excludes important subgroups of your target population. Always ask whether your final sample truly represents everyone you're trying to study.

Question 6

A consulting firm surveys 200 employees from a Fortune 500 company about workplace satisfaction. They use a stratified sampling design with three strata: executives (n=20), middle management (n=80), and staff (n=100). However, during data collection, executives have a 95% response rate, middle management has 70% response rate, and staff have 45% response rate. What is the most concerning bias issue, and why does it threaten the study's conclusions?

Selection bias, because the original stratified design oversampled executives relative to their proportion in the company population, leading to unrepresentative demographic composition
Nonresponse bias, because higher response rates among executives and managers may reflect systematically different satisfaction levels compared to non-responding staff members (correct answer)
Measurement bias, because executives and staff likely interpret satisfaction questions differently due to varying job responsibilities, making comparisons across strata invalid
Coverage bias, because the sampling frame of current employees excludes recently departed workers whose satisfaction levels might provide critical insights about workplace issues

Explanation: Nonresponse bias is the primary concern because response rates vary dramatically by hierarchical level (95% vs 45%), and the reasons for non-participation likely correlate with satisfaction levels—dissatisfied staff may be more reluctant to respond than satisfied ones, while executives feel more comfortable participating. This creates systematic differences between respondents and non-respondents within each stratum. Choice A incorrectly assumes the stratification is wrong (stratified sampling often intentionally oversamples smaller groups). Choice C addresses measurement differences but not the sampling bias. Choice D mentions coverage bias, but studying current employees is appropriate for current workplace satisfaction.

Question 7

A pharmaceutical company conducts a post-market survey to assess side effects of their new medication. They contact patients through physician offices that prescribed the medication in the past year. However, they discover that 30% of originally prescribed patients are no longer reachable (moved, changed doctors, or phone numbers disconnected), and these patients are excluded from the study. Among reachable patients, 85% report the medication as 'well-tolerated.' What is the primary threat to the validity of concluding that the medication is well-tolerated by most patients?

Nonresponse bias, because the 15% of reachable patients who reported problems may not represent the experiences of the 85% who found the medication well-tolerated
Attrition bias, because the 30% of unreachable patients may have discontinued the medication due to side effects and changed providers specifically to avoid follow-up contact (correct answer)
Selection bias, because patients were recruited through physician offices that may have better prescribing practices and patient monitoring compared to other healthcare settings
Information bias, because patients reporting to their prescribing physicians may underreport side effects due to concerns about disappointing their healthcare providers or being switched to alternative treatments

Explanation: Attrition bias is the primary concern because 30% of patients became unreachable, and this group may systematically differ from those who remained reachable—specifically, patients who experienced severe side effects might have discontinued the medication and avoided follow-up by changing doctors or moving. The high 'well-tolerated' rate among reachable patients could reflect the systematic loss of patients with negative experiences. Choice A misinterprets the 85% figure (these are positive responses, not non-responses). Choice C addresses selection of physician offices but doesn't explain the unreachable patients. Choice D mentions underreporting, but the main issue is the missing 30% of patients.

Question 8

A national retail chain wants to estimate average customer satisfaction. They create a list of all 800 of their stores. They randomly select 50 stores and then survey every customer who makes a purchase in those 50 stores on a specific day. Which statement is the most accurate critique of this sampling methodology?

This is a simple random sample of customers, but it may be biased if the chosen day is not typical.
This is stratified sampling, with each store as a stratum, which is an inefficient method for this business problem.
This is cluster sampling; its primary risk is that the selected stores might not be representative of all stores. (correct answer)
This is convenience sampling because the chain surveyed customers who were already in their stores.

Explanation: The methodology described is cluster sampling, where the stores are the clusters. The population is divided into clusters (stores), a random sample of clusters is selected, and then all units (customers) within the selected clusters are surveyed. The primary risk of cluster sampling is that clusters themselves can be homogeneous in some way (e.g., stores in affluent areas, stores in urban vs. rural locations). If the selected clusters are not representative of the entire population of stores, the results will be biased.

Question 9

An investment firm wants to report the average 5-year performance of equity-based mutual funds. They compile data on all funds currently available on the market that have at least a 5-year history. Their calculation of the average return is likely to be an overestimate due to which type of bias?

Survivorship bias, as funds that performed poorly and were liquidated or merged are excluded from the analysis. (correct answer)
Nonresponse bias, as only fund managers with good performance would report their data to the firm.
Social desirability bias, because fund managers have an incentive to present their performance in the best possible light.
Selection bias, as the firm likely selected funds from a database that is not comprehensive of the entire market.

Explanation: This is a classic example of survivorship bias. The analysis is based only on the 'surviving' funds. Mutual funds with poor performance are often closed down or merged into other funds, removing them from the current database of available funds. By excluding these failures, the calculated average performance of the remaining funds is artificially inflated.

Question 10

A survey conducted by a company's HR department includes the question: 'Considering the substantial investment the company has made in our new training platform to support employee career growth, how would you rate its effectiveness?' What is the most significant source of bias this question introduces?

Nonresponse bias, as employees who have not used the platform will not be able to answer.
Undercoverage bias, as the survey may not reach employees on leave or new hires.
Social desirability bias, as employees will feel obligated to rate the company's initiatives positively.
Response bias from a leading question, as the framing encourages a positive rating. (correct answer)

Explanation: The question is a leading question. It uses emotionally charged and positive framing ('substantial investment', 'support employee career growth') before asking for an evaluation. This wording primes the respondent to view the platform favorably and encourages a positive response, thus introducing response bias. While social desirability (C) might also be present, the direct cause is the biased wording of the question itself.

Question 11

A restaurant chain leaves feedback cards on every table, inviting customers to share their experience. The compiled data consistently shows a large number of 'Excellent' ratings and a large number of 'Poor' ratings, with very few ratings in the middle categories. This bimodal distribution of responses is a classic symptom of what kind of bias?

Selection bias, because the cards are only available to dine-in customers.
Response bias, because the rating scale is not well-defined.
Voluntary response bias, because customers with strong opinions are the most likely to participate. (correct answer)
Survivorship bias, because only customers who completed their meal can provide feedback.

Explanation: This method relies on customers to self-select into the sample. This is known as voluntary response sampling. Such samples are notoriously biased because they tend to over-represent individuals who have strong opinions—either very positive or very negative—and are motivated to share them. Customers with an average, unremarkable experience are less likely to take the time to respond, leading to a polarized or bimodal distribution of results.

Question 12

A market researcher is tasked with understanding the experiences of 'gig economy' workers who use a specific food delivery app. As there is no public list of these workers, the researcher contacts five workers and asks each of them to refer other workers they know. This process is repeated with the new contacts. The primary limitation of this sampling method is that it...

is a form of probability sampling that is difficult to execute correctly.
is prone to selection bias, as referrals are likely to share similar characteristics with the people who referred them. (correct answer)
violates the privacy of the workers by asking for referrals without their consent.
is more costly and time-consuming than creating a complete sampling frame of all workers.

Explanation: This method is called snowball sampling. It is a non-probability technique used when the target population is hard to reach. Its main statistical limitation is selection bias. The sample tends to be homogeneous because people are socially connected to others like themselves. The final sample is therefore unlikely to be representative of the diversity within the entire population of gig workers for that app.

Question 13

A well-executed simple random sample of 400 employees finds that 70% are in favor of a new remote work policy. The actual proportion of all 5,000 employees who are in favor is known to be 68%. The 2% difference between the sample statistic and the population parameter is best described as:

nonresponse bias.
selection bias.
sampling error. (correct answer)
response bias.

Explanation: Sampling error is the natural, random variation that occurs because a sample, rather than the entire population, is surveyed. Even in a perfectly designed and executed random sample, the sample statistic (e.g., 70%) will almost never be exactly equal to the true population parameter (68%). This difference is due to chance and is known as sampling error. The other options refer to systematic errors (biases) that are not indicated by the problem description ('well-executed simple random sample').

Question 14

A cable company previously used online pop-up surveys to measure customer satisfaction, which yielded a 92% satisfaction rate. A new manager implements a costly but statistically rigorous simple random sample of all customers, which yields a 78% satisfaction rate. What is the most likely statistical explanation for the 14-point drop?

The original voluntary response survey was biased, likely over-representing customers with very positive feelings or those who were not having technical issues. (correct answer)
The simple random sample introduced selection bias by including dissatisfied customers who would not normally respond.
The larger sample size of the pop-up survey provided a more accurate estimate of the true satisfaction rate.
Customer satisfaction genuinely decreased in the time between the two surveys due to a recent price increase.

Explanation: When you encounter questions comparing different sampling methods, focus on the potential biases each method introduces and how they affect data quality. Answer A is correct because voluntary response surveys (like pop-up surveys) suffer from self-selection bias. Only customers motivated to respond participate, and these tend to be either extremely satisfied or extremely dissatisfied customers. However, customers experiencing technical problems are less likely to encounter pop-ups (since their service isn't working properly), so the extremely satisfied customers dominate the sample. This creates an upward bias, inflating the satisfaction rate to an unrealistic 92%. Answer B is wrong because simple random sampling doesn't introduce selection bias—it eliminates it. By definition, every customer has an equal chance of being selected, making dissatisfied customers just as likely to be included as satisfied ones. This isn't a flaw; it's the method working correctly. Answer C is wrong because it assumes the pop-up survey had a larger sample size, which isn't stated. More importantly, sample size alone doesn't overcome bias. A large biased sample is still less accurate than a smaller unbiased sample. Answer D is wrong because it suggests an external cause rather than a methodological explanation. While customer satisfaction could have genuinely changed, the question asks for the "statistical explanation," pointing you toward sampling methodology rather than business factors. Study tip: Remember that voluntary response methods almost always produce biased results. When comparing satisfaction rates from different sampling methods, the scientifically rigorous method (simple random sampling) typically provides the more accurate—and often less favorable—estimate.

Question 15

A consultant wants to interview 'exemplary' leaders within an organization to understand best practices. She asks senior executives to nominate managers who are widely considered to be the most effective and innovative. This sampling method is best described as:

Judgmental (or Purposive) sampling, because subjects are selected based on specific criteria and the judgment of experts. (correct answer)
Stratified sampling, where the strata are 'exemplary' and 'non-exemplary'.
Convenience sampling, because she is interviewing managers who were easily identified.
Snowball sampling, because she is starting with senior executives and branching out.

Explanation: When you encounter sampling method questions, focus on how the researcher is actually selecting participants and what drives those selection decisions. In this scenario, the consultant is deliberately choosing participants based on specific criteria (being "exemplary" leaders) and relying on expert judgment (senior executives' assessments) to identify them. This is the hallmark of judgmental or purposive sampling, where researchers intentionally select subjects who meet particular qualifications rather than using random selection. The consultant wants leaders with specific characteristics, so she's using informed judgment to find them. Option B misunderstands stratified sampling, which requires dividing the entire population into distinct groups (strata) and then randomly sampling from each stratum. Here, the consultant isn't creating population divisions or using random selection within groups. Option C confuses convenience with purposive sampling. While the nominated managers might be "easily identified" after nomination, the selection process itself is based on expertise and specific criteria, not mere convenience or accessibility. Option D misapplies snowball sampling, which involves current participants recruiting additional participants from their networks. The senior executives aren't being interviewed themselves, nor are the selected managers recruiting others—the executives are simply serving as expert nominators. The correct answer is A because this is textbook judgmental sampling: selection based on specific criteria using expert knowledge to identify the most suitable participants. Study tip: Remember that judgmental sampling is about purposeful selection using expertise, while convenience sampling is about easy access, and snowball sampling involves participant-driven recruitment chains.

Question 16

An e-commerce platform wants to estimate the average order value of their customers. They have 2 million registered users and decide to survey 1,000 of them. The research team considers four different sampling approaches:

Based on the passage above, which sampling method would most likely produce the least biased estimate of average order value, and what is the primary advantage of this approach over the alternatives?

Survey the first 1,000 users who log in on Monday morning, because these are the most active and engaged customers who represent typical purchasing behavior
Survey 1,000 users randomly selected from all registered users, because this approach ensures each customer has equal probability of selection regardless of activity level (correct answer)
Survey 1,000 users who made purchases in the last 30 days, because these customers have recent order values that reflect current market conditions and pricing
Survey 200 users each from the top 5 geographic regions by sales volume, because this stratified approach captures regional differences in purchasing power and preferences

Explanation: Random selection from all registered users provides the most unbiased estimate because it gives every user an equal chance of selection, avoiding systematic exclusions. Choice A introduces temporal and activity bias (Monday morning users may be atypical). Choice C creates recency bias by excluding inactive customers who still represent part of the user base. Choice D seems reasonable but focuses on high-volume regions only, missing potential users in other areas and introducing geographic bias toward higher-spending regions.

Question 17

A financial services company wants to study investment risk tolerance among their clients. They mail surveys to 5,000 randomly selected clients and receive 800 responses (16% response rate). The analysis reveals that 65% of respondents prefer low-risk investments, leading the company to shift their product offerings toward conservative options. Six months later, sales data shows this strategy failed. Which bias most likely explains the disconnect between survey results and actual client behavior?

Self-selection bias in survey response, where risk-averse clients were more motivated to complete and return the investment survey than risk-tolerant clients who may be less engaged with formal research (correct answer)
Social desirability bias in survey responses, where clients reported preferring conservative investments because they believed this was the financially responsible answer expected by their financial services provider
Temporal bias in data collection, where the survey captured client preferences at one point in time but market conditions and risk tolerance changed significantly during the six-month implementation period
Measurement bias in question design, where the survey instrument failed to accurately distinguish between theoretical investment preferences and actual investment behavior under real market conditions

Explanation: Self-selection bias best explains this outcome because risk-averse clients are naturally more likely to respond to financial surveys (they're more cautious and engaged with financial planning), while risk-tolerant clients may ignore such surveys. This creates a systematic overrepresentation of conservative preferences. The failed strategy confirms that non-respondents had different (more aggressive) preferences. Choice B assumes clients knew what answer the company wanted, which isn't indicated. Choice C suggests market changes, but six months isn't typically enough for fundamental risk tolerance shifts. Choice D implies measurement problems, but the issue is who responded, not how questions were asked.

Question 18

A startup wants to gather feedback on its new mobile app by surveying visitors to a local tech conference. They set up a booth and offer a free t-shirt to anyone who completes their 10-minute survey. The primary concern with generalizing the results of this survey to the broader target market of all potential app users is:

response bias, because the t-shirt incentive may cause people to give overly positive feedback.
nonresponse bias, because many people at the conference will choose not to take the survey.
selection bias, because tech conference attendees are not representative of the general population. (correct answer)
sampling error, because the sample size will likely be too small to be accurate.

Explanation: This is a form of convenience sampling, which leads to selection bias. The sample is drawn from a sub-population (tech conference attendees) that is convenient but not representative of the broader market. These individuals are likely more tech-savvy, have different needs, and may be early adopters compared to the general population. Therefore, their feedback cannot be reliably generalized. While other biases might exist, the fundamental flaw is in the selection of the sample itself.

Question 19

A city government wants to survey local business owners about a proposed tax increase. Their sampling frame is the official business license database from the beginning of the year. However, this database does not include new businesses started this year and still contains listings for businesses that have since closed. Which bias is the primary result of using this sampling frame?

Response bias, as business owners may not answer truthfully about a tax increase.
Nonresponse bias, as owners of closed businesses will not be able to respond.
Undercoverage bias for new businesses and inclusion of non-existent businesses. (correct answer)
Convenience sampling bias, because the database was the easiest one to access.

Explanation: A flawed sampling frame is a source of selection bias. In this case, the frame has two problems: it systematically excludes a part of the target population (new businesses), which is called undercoverage bias, and it includes units that are no longer in the population (closed businesses). While nonresponse bias (B) will occur when closed businesses don't respond, the root problem is that the frame itself is inaccurate, which is best described by (C).

Question 20

A factory's quality control plan involves inspecting every 50th unit produced. The machine that packages the units is known to slightly misalign after every 200 units, causing a minor packaging defect for a few units before it is auto-corrected. What is the most significant statistical problem with this inspection plan?

The sample size is too small to make any valid conclusions about overall quality.
The sampling interval has a periodic relationship with a recurring event in the production process, potentially creating a biased sample. (correct answer)
The plan is a form of convenience sampling and is not random, which invalidates statistical inference.
The plan suffers from undercoverage because it can never select units that are adjacent to each other on the production line.

Explanation: This scenario describes the primary pitfall of systematic sampling. If the sampling interval (k=50) aligns with a cyclical or periodic pattern in the population (a defect pattern every 200 units), the sample can be severely biased. In this case, since 200 is a multiple of 50, the inspections will always occur at the same points in the defect cycle, either consistently missing the defects or consistently observing them, but not capturing their true overall rate.