2022 May/June · Paper 22 · Q51 markPopulations and samples
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Practice questions
Original questions written by HomiLabs in the style of the exam, with answers and mark schemes. They are not
Cambridge past paper questions and have not been reviewed by Cambridge. Try each one before opening the answer.
Q1Sampling techniques · Core · Paper 2 style · 4 marks
(a)Describe what is meant by an opportunity sample.[2]
(b)Give one strength and one weakness of opportunity sampling.[2]
Show answer
(a) Participants are selected because they are available and willing at the time the researcher is collecting data, e.g. asking people who are in a college canteen at lunchtime.
1 mark: people who are available/convenient at the time. 1 mark: elaboration or example (researcher approaches them).
(b) Strength: quick, cheap and easy to obtain participants. Weakness: likely to be unrepresentative because only people in one place at one time are sampled (and the researcher may choose people who look approachable), so findings may not generalise.
1 mark: strength. 1 mark: weakness with reason.
Q2Sampling techniques · Core · Paper 2 style · 4 marks
(a)Describe how a researcher could obtain a volunteer (self-selected) sample for a study of online gaming habits among young adults in Lahore.[2]
(b)Explain one weakness of using a volunteer sample in this study.[2]
Show answer
(a) Place an advertisement (e.g. on a university notice board or a gaming forum) describing the study and asking young adults aged 18 to 25 who play online games to contact the researcher if they would like to take part.
1 mark: advertisement/request for participants. 1 mark: participants choose to respond/sign up, linked to context.
(b) People who reply may be especially keen gamers, or more confident and helpful, so the sample may over-represent heavy gaming and not reflect typical young adults (volunteer bias).
1 mark: volunteer bias. 1 mark: linked to the gaming study.
Q3Sampling techniques · Core · Paper 2 style · 3 marks
(a)Describe how a random sample of 25 pupils could be selected from a school of 250 pupils in Hyderabad.[2]
(b)State the probability that any one pupil is selected.[1]
Show answer
(a) Obtain a list of all 250 pupils, give each a number, then use a random number generator (or put all names in a container and draw out 25) to choose 25 pupils.
1 mark: list of the whole target population. 1 mark: random selection method (lottery/random number generator) giving each pupil an equal chance.
(b) 0.1 (1 in 10).
B1: 25 ÷ 250 = 0.1.
Q4Sampling techniques · Core · Paper 2 style · 4 marks
(a)Describe what is meant by a snowball sample.[2]
(b)Suggest why snowball sampling would be useful for a study of people recovering from gambling problems.[2]
Show answer
(a) The researcher finds a few participants from the target population, then asks them to recommend or recruit other people they know who fit the criteria; those people recruit others, so the sample grows.
1 mark: initial small group found. 1 mark: they recruit/refer further participants.
(b) People with gambling problems are hard to identify and may hide it; existing participants know others in a similar situation (e.g. from support groups) and can approach them with trust, so the researcher can reach a hidden population.
1 mark: hard-to-reach / hidden population. 1 mark: participants know and trust others like them.
Q5Sampling techniques · Core · Paper 2 style · 3 marks
(a)Explain why a truly random sample is often difficult to obtain in psychology.[3]
Show answer
(a) The researcher needs a complete list of everyone in the target population, which is often unavailable. Even if names are drawn randomly, some selected people may refuse or not be contactable, so the final sample becomes partly self-selected. It can also be time-consuming and costly to reach people who are spread over a wide area.
1 mark each for any three of: need full list; refusals/non-response make it partly volunteer; time/cost; selected people may be hard to reach.
Q6Sampling techniques · Core · Paper 2 style · 2 marks
(a)Explain one ethical advantage of using a volunteer sample compared with an opportunity sample.[2]
Show answer
(a) Volunteers have actively chosen to take part after reading about the study, so they are more likely to have given genuine informed consent and feel free to refuse, whereas people approached face-to-face may feel pressured to agree.
1 mark: volunteers choose freely / informed. 1 mark: comparison – less pressure than being approached directly.
Q7Sampling techniques · Core · Paper 2 style · 3 marks
(a)Identify the sampling technique in each of the following hypothetical studies:(i) A researcher posts on a social-media page asking for parents of toddlers to complete a survey.(ii) A researcher asks the people sitting in a hospital waiting room to rate their anxiety.(iii) A researcher draws 20 names from a box containing the names of every employee in a bank.[3]
Show answer
(a) (i) Volunteer (self-selected) sample. (ii) Opportunity sample. (iii) Random sample.
1 mark each.
Q8Sampling techniques · Standard · Paper 2 style · 4 marks
(a)In a hypothetical snowball sample for a study of home-based tailors in Faisalabad, the researcher starts with 3 tailors. In each round of recruitment, every tailor recruited in the previous round (starting with the first 3) recruits exactly 2 new tailors. There are three rounds of recruitment. Calculate the total number of participants.[2]
(b)Explain one reason why this sample may be biased.[2]
Show answer
(a) 45 participants.
M1: 3 + 6 + 12 + 24. A1: 45.
(b) Tailors recruit people they know, so the sample will consist of connected friendship or family networks, possibly from the same area and with similar working conditions, and tailors outside these networks will be missed.
1 mark: participants recruit similar people / from own network. 1 mark: so sample unrepresentative of all home-based tailors.
Q9Sampling techniques · Standard · Paper 2 style · 4 marks
(a)A researcher placed an advertisement for a study about sleep in a newspaper read by about 4500 people in Rawalpindi. 300 people replied. Calculate the percentage of readers who replied. Give your answer to 1 decimal place.[1]
(b)Name the sampling technique and explain why the researcher should be cautious about generalising the results.[3]
Show answer
(a) 6.7 %
B1: 300 ÷ 4500 × 100 = 6.666… = 6.7 %.
(b) Volunteer (self-selected) sampling. Only a small proportion (6.7 %) replied, and those who reply may be different from other readers – e.g. people with sleep problems who are more interested in the topic, or people with more free time – and newspaper readers themselves may not represent the general population.
1 mark: volunteer sampling. 1 mark: respondents are a small, self-selected group with particular characteristics. 1 mark: readers of one newspaper not typical of whole population.
Q10Sampling techniques · Standard · Paper 2 style · 6 marks
(a)Describe 'random sampling' and 'opportunity sampling', using any examples.[6]
Show answer
(a) Random sampling: every member of the target population has an equal chance of being selected; the researcher needs a complete list of the population and uses a lottery or random number generator, e.g. picking 30 staff numbers at random from a hospital's list of 600 nurses. It avoids researcher bias in selection but may still produce an unrepresentative sample by chance and can be time-consuming. Opportunity sampling: the researcher uses whoever is available and willing at the time, e.g. asking passengers waiting at a bus terminal; it is quick and convenient but likely to be biased towards certain types of people (e.g. those who use that terminal at that time).
3 marks each: 1 mark definition, 1 mark elaboration (how done / strength or weakness), 1 mark example.
Q11Sampling techniques · Standard · Paper 2 style · 3 marks
(a)A psychologist wants to study the experiences of refugees from one region who have settled in a city. Explain which sampling technique would be most appropriate and why.[3]
Show answer
(a) Snowball sampling: there is no complete list of refugees, so random sampling is not possible; refugees may be wary of strangers, but if a few trusted participants are found (e.g. through a community centre) they can introduce others, allowing the researcher to reach enough participants.
1 mark: snowball. 1 mark: no list / hard to reach. 1 mark: trust and referral explanation.
Q12Sampling techniques · Standard · Paper 2 style · 5 marks
(a)In a hypothetical study, a researcher stood outside a gym in Dubai at 7 a.m. and asked people leaving whether they would complete a questionnaire about healthy eating. Identify the sampling technique and explain two reasons why the results may be biased.[5]
Show answer
(a) Opportunity sampling. 1. People leaving a gym early in the morning are probably more health-conscious than average, so they may report healthier eating than the general population. 2. Only people present at that time and place could be chosen (e.g. not shift workers or people who cannot afford gym fees), and the researcher may approach people who seem friendly, so the sample is not representative.
1 mark: opportunity sample. For each reason: 1 mark identification, 1 mark explanation linked to the gym context.
Q13Sampling techniques · Standard · Paper 2 style · 2 marks
(a)Explain why a researcher might choose an opportunity sample even though it is likely to be unrepresentative.[2]
Show answer
(a) It is the quickest and cheapest way of obtaining participants, and in some studies (e.g. a laboratory experiment on a basic process such as visual perception) the researcher assumes the process works the same in most people, so representativeness matters less.
1 mark: practicality (time, cost, ease). 1 mark: elaboration, e.g. universal processes or pilot studies.
Q14Sampling techniques · Standard · Paper 2 style · 6 marks
(a)Describe 'volunteer sampling' and 'snowball sampling', using any examples.[6]
Show answer
(a) Volunteer sampling: participants select themselves, usually by responding to an advertisement, e.g. a poster in a library asking students to take part in a memory study; it gives willing and often committed participants but may be biased towards people who are more motivated or have more time. Snowball sampling: the researcher begins with a few participants who meet the criteria and asks them to recruit others they know, e.g. finding a few people who have recovered from a phobia, who then introduce others; it allows access to hard-to-reach groups, but the sample may contain people with similar characteristics because they come from the same networks.
3 marks each: 1 mark definition, 1 mark elaboration (strength/weakness or procedure), 1 mark example.
Q15Sampling techniques · Challenge · Paper 2 style · 4 marks
(a)A college in Karachi has 800 students. A researcher randomly selects 40 students for a study of exam stress, but 14 of the selected students refuse to take part. Calculate the percentage of selected students who refused.[1]
(b)Explain how this refusal rate affects the representativeness of the sample.[3]
Show answer
(a) 35 %
B1: 14 ÷ 40 × 100 = 35 %.
(b) The final sample of 26 is no longer truly random because the people who agreed are, in effect, volunteers. Students who refused may be different – e.g. the most stressed students might avoid a study about stress – so the sample may underestimate exam stress, and the smaller sample is also more affected by individual differences.
Q16Sampling techniques · Challenge · Paper 2 style · 4 marks
(a)Compare random sampling and snowball sampling in terms of representativeness and practicality.[4]
Show answer
(a) Representativeness: random sampling gives every member of the population an equal chance and avoids researcher bias, so it is more likely to be representative; snowball samples consist of linked social networks, so they are likely to be biased towards similar people. Practicality: random sampling needs a full list of the population and may be impossible for hidden groups (e.g. people with an addiction), whereas snowball sampling is practical for hard-to-reach populations because participants recruit others they know.
2 marks representativeness comparison (1 each side), 2 marks practicality comparison (1 each side).
Q17Sampling techniques · Challenge · Paper 2 style · 10 marks
(a)Describe how a researcher could conduct a study using a questionnaire to investigate attitudes towards mental-health help-seeking among university students in Islamabad. Your plan must include the sampling technique, and you must explain how it would be carried out.[10]
Show answer
(a) Sampling: random sample – obtain the list of all registered undergraduates from the university, number them, use a random number generator to select 100; contact by university email with information sheet and consent form; replace non-responders by drawing more names and record the response rate. Questionnaire: closed questions with a 5-point Likert scale (strongly agree to strongly disagree), e.g. 'I would see a counsellor if I felt low for two weeks'; some open questions, e.g. 'What would stop you seeking help?'; demographic questions (age, gender, course). Procedure: online or paper in a quiet room, standardised instructions, about 15 minutes, anonymous with ID codes, right to withdraw, debrief with details of the counselling service. Analysis: total attitude score (quantitative) compared between groups; themes from open answers. Pilot the questionnaire with a few students.
Level 4 (9–10): sampling technique named and fully described (how selected, from what population, size, recruitment); questionnaire details with example items; procedure replicable; ethics. Level 3 (6–8): most features with some detail. Level 2 (3–5): basic plan, sampling vague. Level 1 (1–2): very limited.
Q18Sampling techniques · Challenge · Paper 2 style · 4 marks
(a)A hypothetical study needs a sample of 60 shoppers at a large market in Peshawar. Ali suggests asking the first 60 people who walk past a stall. Fatima suggests putting up a poster asking shoppers to sign up. Evaluate each suggestion and recommend which is better for reducing bias.[4]
Show answer
(a) Ali (opportunity): quick and gives a sample of people actually shopping, but only those passing one stall at one time are included, and passers-by in a hurry may refuse. Fatima (volunteer): participants choose freely, but only shoppers who notice the poster and have time or interest will sign up, creating volunteer bias and possibly a slow, small sample. Recommendation: e.g. Ali's method adapted – approach every 5th shopper at different stalls and times of day – reduces both selection by the researcher and self-selection bias; credit any justified recommendation.
1 mark: evaluation of Ali's suggestion. 1 mark: evaluation of Fatima's suggestion. 1 mark: clear recommendation. 1 mark: justification about bias.
Q19Sampling techniques · Challenge · Paper 2 style · 4 marks
(a)A researcher wants a random sample from all 1500 adults registered at a health clinic in Lahore. He chooses 90 adults using random numbers, and 54 of them complete his questionnaire. Calculate (i) the percentage of registered adults who were selected, and (ii) the percentage of selected adults who completed the questionnaire.[2]
(b)Suggest one way the researcher could increase the response rate without making the sample less random.[2]
(b) Send reminders to the selected adults who have not responded (or make the questionnaire shorter/available by phone or online), rather than replacing them with whoever is available, so that the original randomly chosen people are more likely to take part.
1 mark: suitable method (reminders, convenience of format, short questionnaire, explanation of importance). 1 mark: keeps the originally selected random sample.
Q20Populations and samples · Core · Paper 2 style · 4 marks
(a)Define the terms 'target population' and 'sample'.[2]
(b)A researcher studies 30 nurses from one hospital in Multan to learn about stress among nurses in Pakistan. Identify the target population and the sample.[2]
Show answer
(a) Target population: the whole group of people the researcher is interested in and wants the findings to apply to. Sample: the smaller group of people selected from the target population who actually take part in the study.
1 mark each.
(b) Target population: nurses in Pakistan. Sample: the 30 nurses from the hospital in Multan.
1 mark each.
Q21Populations and samples · Core · Paper 2 style · 2 marks
(a)Explain what is meant by a representative sample and why it is important.[2]
Show answer
(a) A representative sample has the same important characteristics as the target population (e.g. similar proportions of ages, genders and backgrounds), so findings from it can be generalised to the population.
1 mark: sample reflects the characteristics of the population. 1 mark: allows generalisation.
Q22Populations and samples · Standard · Paper 2 style · 5 marks
(a)A hypothetical study wanted to investigate the reading habits of teenagers in Pakistan. The researcher's sample was 120 students from private English-medium schools in Islamabad, of whom 36 were girls. Calculate the percentage of the sample who were girls.[1]
(b)Explain two ways in which this sample may not represent the target population.[4]
Show answer
(a) 30 %
B1: 36 ÷ 120 × 100 = 30 %.
(b) 1. Only 30 % were girls, whereas girls make up about half of teenagers, so girls' reading habits are under-represented. 2. All students came from private English-medium schools in one city; teenagers in government or Urdu-medium schools, in rural areas or not in school may have very different access to books and reading habits.
For each: 1 mark identification, 1 mark explanation linked to reading habits.
Q23Populations and samples · Standard · Paper 2 style · 3 marks
(a)A hypothetical experiment on the effect of caffeine on concentration used 20 psychology undergraduates from one university in the UK. Explain why the target population may be narrower than the researchers claim.[3]
Show answer
(a) The researchers may claim the results apply to 'adults', but psychology undergraduates are mostly young, educated and from one country, and many may know about research aims. People who are older, from other cultures, or who rarely drink caffeine may react differently, so the findings really only generalise to similar students.
1 mark: identifies the narrow sample characteristics. 1 mark: explains how other groups may differ in caffeine response or concentration. 1 mark: conclusion that the population the results apply to is limited.
Q24Populations and samples · Challenge · Paper 2 style · 3 marks
(a)Explain the difference between a target population and a sampling frame (the list from which a sample is actually drawn), using an example.[3]
Show answer
(a) The target population is everyone the researcher wants to generalise to, e.g. all adults with diabetes in Karachi. The sampling frame is the actual list available, e.g. patients registered at three diabetes clinics. The two may differ: people with undiagnosed diabetes or who do not attend these clinics are in the population but not on the list, so even a random sample from the list may be biased.
1 mark: target population definition with example. 1 mark: sampling frame / list definition with example. 1 mark: explains how the difference may cause bias.
Q25Populations and samples · Challenge · Paper 2 style · 6 marks
(a)A researcher wants to investigate the experiences of women who run small home businesses in rural Punjab. Discuss how the definition of the target population affects the choice of sampling technique and the generalisability of findings.[6]
Show answer
(a) Definition: the population must be defined precisely – e.g. women aged 18+ living in villages in Punjab who earn money from a business run from home – so it is clear who is included. Because there is no list of such women, random sampling is impractical; snowball sampling through community contacts or an opportunity sample at village markets may be used. These techniques are likely to produce samples biased towards connected women in accessible villages, so findings generalise best to similar women. A broad definition (e.g. 'women entrepreneurs in Pakistan') would make generalisation from such a sample inappropriate, whereas a narrow definition makes the sample more representative but the findings apply to fewer people.
1 mark: need to define population precisely (with example). 2 marks: link from definition/availability of a list to sampling technique choice. 2 marks: effect on representativeness/generalisability. 1 mark: trade-off between broad and narrow definitions.
Q26Populations and samples · Challenge · Paper 2 style · 4 marks
(a)A hypothetical study of 60 commuters at a Lahore metro station found that 18 felt anxious in crowds. A newspaper reported: '30 % of people in Lahore suffer from crowd anxiety.' Calculate the percentage of the sample who felt anxious, and explain why the newspaper's claim is not justified.[4]
Show answer
(a) 18 ÷ 60 × 100 = 30 %. The claim is not justified because the sample was 60 metro commuters at one station – not representative of all people in Lahore (e.g. people who avoid crowds may not use the metro at all, so anxiety may be underestimated, or the time of day may have affected results). The sample is also small, and 'felt anxious' is not the same as 'suffering' from an anxiety problem.
B1: 30 %. 1 mark: sample not representative of the population of Lahore. 1 mark: specific reason (only metro users/one station/self-selection out of the metro). 1 mark: small sample or measurement issue (felt anxious ≠ disorder).
Q27Sample size · Core · Paper 2 style · 4 marks
(a)Explain one advantage of using a large sample in a psychological study.[2]
(b)Explain one disadvantage of using a large sample.[2]
Show answer
(a) Individual differences and unusual participants have less effect on the overall results, so the findings are more likely to be representative and generalisable to the target population.
1 mark: reduces effect of individual differences/anomalies. 1 mark: more representative / generalisable / reliable.
(b) It takes more time and money to recruit and test many participants, and it may be impractical, e.g. if each participant needs a one-hour interview.
1 mark: time/cost. 1 mark: elaboration.
Q28Sample size · Core · Paper 2 style · 3 marks
(a)Explain why case studies often use a sample size of one, and one consequence of this for the research.[3]
Show answer
(a) Case studies investigate a single person (or small group) in great depth, often because the condition is rare or unusual (e.g. a person with a specific brain injury), so it may only be possible to study one. Consequence: detailed qualitative data are obtained, but the findings may not be generalisable because that individual may be unique.
1 mark: in-depth study of one person. 1 mark: rare/unusual cases. 1 mark: consequence – low generalisability (or rich detail).
Q29Sample size · Standard · Paper 2 style · 4 marks
(a)A hypothetical study compared the mean reaction times of two groups, each containing only 5 participants. In Group A the reaction times (in milliseconds) were 312, 298, 305, 640 and 301. Calculate the mean reaction time for Group A, and explain how the small sample size affects the conclusions that can be drawn.[4]
Show answer
(a) Mean = 1856 ÷ 5 = 371.2 ms. One unusual score (640 ms) has a large effect on the mean of such a small group; without it the mean would be about 304 ms. With only 5 people, a single anomaly or individual difference can distort the comparison between groups, so the conclusion may not be reliable or generalisable.
M1: sum 1856. A1: 371.2 ms. 1 mark: outlier 640 strongly affects a small sample. 1 mark: results less reliable/representative.
Q30Sample size · Challenge · Paper 2 style · 4 marks
(a)A researcher plans a questionnaire study about smartphone use among 9000 secondary-school pupils in a district. She can afford to survey either 30 pupils chosen at random or 300 pupils from the two schools nearest her office. Evaluate both options and recommend which she should choose.[4]
Show answer
(a) 30 random pupils: every pupil has an equal chance, so there is no systematic selection bias, but the sample is small, so chance variation and individual differences may make it unrepresentative. 300 pupils from two nearby schools: the larger sample reduces the effect of individual differences, but it is biased – pupils from two schools in one area may share similar backgrounds, school phone rules and internet access. Recommendation: e.g. the random sample, because bias cannot be removed by increasing size, whereas the random sample's error is due to chance only; or a justified compromise (random selection of schools, then pupils). Credit any justified decision.
1 mark: evaluation of small random sample. 1 mark: evaluation of large biased sample. 1 mark: recommendation. 1 mark: justification (size does not cure bias).
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