📚 Year 12 Cambridge Psychology: Key Points for Experimental/Practical Exams | 剑桥12年级心理学：实验/实践考核要点
Cambridge AS Psychology (9990) places strong emphasis on practical skills through Paper 2: Research Methods. This paper challenges you to design investigations, analyse data, interpret statistical findings and evaluate psychological research. Mastering these aspects is not only vital for your exam performance but also builds the foundation of scientific thinking required at A Level. This guide distills the must‑know assessment points, from hypotheses to report‑writing, so you can approach your practical work and examination with clarity and confidence.
剑桥AS心理学（9990）通过试卷2《研究方法》对实践技能提出了很高要求。这份试卷考查你设计研究、分析数据、解读统计结果以及评估心理学研究的能力。掌握这些要点不仅对考试成绩至关重要，更能奠定A Level所需的科学思维基础。本指南提炼出从假设到报告撰写的必知考核要点，帮助你清晰地、自信地面对实践任务与考试。
1. Understanding the AS Practical Assessment | 理解AS实践评估要求
Paper 2 lasts 1 hour 30 minutes and carries 60 marks. Questions typically fall into three categories: designing a new study, working with given data (e.g. drawing graphs, calculating descriptive statistics), and evaluating an existing piece of research. You need to be equally comfortable with experiments, questionnaires, observations, interviews and correlational studies, and you must know the strengths and limitations of each method.
试卷2时长1小时30分钟，总分60分。题目通常分为三类：设计新研究、处理所给数据（如绘制图表、计算描述统计量）以及评估一项已有研究。你需要同样熟练地驾驭实验、问卷、观察、访谈和相关性研究，还必须了解每种方法的优势与局限。
The exam expects you to use precise psychological terminology. Words like ‘operationalisation’, ‘extraneous variable’, ‘counterbalancing’ and ‘standard deviation’ must become part of your active vocabulary. Mark schemes reward accuracy in describing procedures and justifying choices, so avoid vague language and always link your answers back to the study’s aim.
考试要求你使用准确的心理学术语。像“操作化”“额外变量”“平衡法”和“标准差”这类词汇必须成为你的主动词汇。评分方案看重对研究程序的准确描述和选择理由的论证，因此请避免模棱两可的语言，始终将答案与研究的核心目的联系起来。
2. Formulating Research Aims and Hypotheses | 制定研究目标与假设
Every good study starts with a clear aim — a statement explaining what the researcher intends to investigate. Once the aim is set, you formulate a hypothesis that predicts the relationship between the variables. At AS level, you must distinguish between directional (one‑tailed) hypotheses, which state the expected effect (e.g. ‘participants who sleep 8 hours will recall more words’), and non‑directional (two‑tailed) hypotheses, which simply predict a difference without specifying its direction (e.g. ‘there will be a difference in word recall between participants who sleep 8 hours and those who sleep 4 hours’).
每项好的研究都始于一个清晰的目标——说明研究者打算探究什么。目标确立后，你需要提出一个假设，对变量间的关系作出预测。在AS阶段，你必须区分方向性（单尾）假设，即陈述预期的效应（如“睡眠8小时的参与者能回忆更多单词”），和非方向性（双尾）假设，即仅仅预测存在差异但不指明方向（如“睡眠8小时与睡眠4小时的参与者在单词回忆上存在差异”）。
Always decide on the hypothesis type before looking too closely at the data. Use a directional hypothesis only when previous research strongly suggests a particular outcome; otherwise, a non‑directional hypothesis is the safer choice. Examiners frequently test your ability to write an operationalised hypothesis, so practice turning abstract ideas into measurable predictions.
要始终在仔细查看数据之前就确定假设类型。只有在以往研究强烈提示某一特定结果时才使用方向性假设，否则非方向性假设是更稳妥的选择。考官经常考查你撰写可操作化假设的能力，因此要多练习将抽象想法转化为可测量的预测。
3. Identifying and Operationalising Variables | 识别与操作化变量
The independent variable (IV) is the factor you manipulate or compare, while the dependent variable (DV) is the outcome you measure. Operationalisation means defining exactly how the IV and DV will be manipulated or measured. For instance, instead of saying ‘we will test memory’, write ‘the number of correctly recalled words from a list of 20 neutral nouns’. The more precise your operational definitions, the easier it is to replicate the research and the more credible your conclusions become.
自变量（IV）是你操作或比较的因素，因变量（DV）则是你测量的结果。操作化意味着准确定义如何操纵或测量自变量和因变量。例如，不要说“我们将测试记忆力”，而应写“从20个中性名词列表中正确回忆的单词数量”。你的操作性定义越精确，研究就越容易重复，结论也越可信。
You must also consider extraneous variables (EVs) and confounding variables. EVs are any factors other than the IV that could affect the DV; if they are not controlled they can become confounding variables, undermining internal validity. Common EVs include participant mood, time of day, noise, and experimenter effects. A strong answer always names relevant EVs and suggests concrete ways to control them, such as using standardised instructions or a double‑blind procedure.
你还必须考虑额外变量和混淆变量。额外变量是除了自变量之外可能影响因变量的任何因素；如果不加控制，它们就可能变成混淆变量，损害内部效度。常见的额外变量包括参与者的情绪、一天中的时段、噪音和实验者效应。一个有力的答案总要指出相关的额外变量，并提出具体的控制方法，比如使用标准化指导语或双盲程序。
4. Choosing the Right Experimental Design | 选择合适的实验设计
There are three main experimental designs: independent groups, repeated measures, and matched pairs. Each has distinct advantages and pitfalls; knowing these is essential because exam questions often ask you to justify your choice or evaluate a given design.
主要有三种实验设计：独立组设计、重复测量设计和匹配对设计。每种设计都有其独特的优势和隐患；熟悉这些至关重要，因为试题常要求你论证所选设计或评估给出的设计。
| Design | Key Features and Typical Controls | 主要特点与典型控制 |
|---|---|---|
| Independent groups | Different participants in each condition; random allocation helps minimise participant variables. | 不同参与者进入不同条件；随机分配有助于最小化参与者变量。 |
| Repeated measures | Same participants take part in all conditions; order effects (e.g. fatigue, practice) are controlled with counterbalancing. | 同一群参与者接受所有条件；顺序效应（如疲劳、练习）通过平衡法控制。 |
| Matched pairs | Participants are paired on a relevant characteristic (e.g. IQ) and then split; reduces participant variables without order effects, but matching is time‑consuming. | 参与者按某个相关特征（如IQ）配对后再分派；既减少了参与者变量又避免了顺序效应，但配对耗时。 |
When choosing a design, weigh up the nature of your task. If practice could inflate performance, repeated measures may be risky unless properly counterbalanced. If individual differences are likely to mask the effect of the IV, an independent groups design with a large sample might be preferable. Always link your explanation to the scenario given in the question.
选择设计时要权衡任务的性质。如果练习效应可能推高表现，那么重复测量可能风险较大，除非进行恰当的平衡。如果个体差异容易掩盖自变量效应，那么使用大样本的独立组设计可能更好。一定要将你的解释与题目给出的情境联系起来。
5. Sampling Techniques and Ethical Considerations | 抽样技术与伦理考量
Your sample should be as representative as possible. Opportunity sampling uses readily available people, which is quick but often biased. Random sampling gives every member of the target population an equal chance, reducing bias but rarely fully achievable. Stratified sampling involves selecting participants in proportion to population subgroups, and self‑selected (volunteer) sampling attracts highly motivated individuals but can introduce volunteer bias.
你的样本应尽可能具有代表性。机会抽样使用方便获取的人，快捷但常有偏差。随机抽样让目标人群中的每个成员都有均等被选中的机会，减少偏差，但很少能完全实现。分层抽样涉及按人群子群比例选择参与者，而自选（志愿者）抽样吸引高度积极的个体，但可能引入志愿者偏差。
Ethics lie at the heart of all psychological research. The four main principles you must be able to discuss are: informed consent (participants should know what the study involves and agree to take part), avoidance of deception (unless essential and justified), right to withdraw (participants must be free to leave at any time without penalty), and protection from harm (both psychological and physical). Confidentiality and debriefing are equally important. When designing a study, always explain how you will uphold each ethical safeguard.
伦理学始终是心理学研究的核心。你必须能够论述的四项主要原则是：知情同意（参与者应知晓研究内容并同意参与）、避免欺骗（除非至关重要且有理由）、退出权（参与者必须能够随时自由离开而不受惩罚）以及保护免受伤害（包括心理伤害和身体伤害）。保密和事后解释同样重要。在设计研究时，始终要说明你将如何维护每项伦理保障。
6. Data Collection: Methods and Controls | 数据收集：方法与控制
Research methods can be experimental (laboratory, field, natural and quasi) or non‑experimental (observations, self‑report, correlations). In an experimental design you actively manipulate the IV; in a quasi‑experiment the IV is a naturally occurring difference (e.g. gender), so causation is harder to establish. Knowledge of these distinctions helps you correctly identify the method being used and evaluate its validity.
研究方法可以是实验法（实验室、现场、自然和准实验）或非实验法（观察、自陈报告、相关性研究）。在实验设计中你要主动操纵自变量；而在准实验中，自变量是自然存在的差异（如性别），因此更难以建立因果关系。了解这些区别有助于你准确识别所使用的方法并评估其效度。
Controls are the tactics you use to keep EVs constant. Standardised instructions ensure every participant receives exactly the same treatment. Random allocation spreads participant variables evenly across conditions. Counterbalancing (e.g. ABBA method) balances order effects in repeated measures designs. Single‑blind and double‑blind procedures reduce demand characteristics and experimenter bias respectively. Always state the purpose of a control — never just name it.
控制是指你用来保持额外变量恒定的策略。标准化指导语确保每位参与者得到完全一致的处理。随机分配将参与者变量均匀分散到各个条件中。平衡法（如ABBA法）平衡了重复测量设计中的顺序效应。单盲和双盲程序分别降低需求特征和实验者偏差。始终要说明控制的目的是什么——切勿仅仅说出名称。
7. Presenting Data: Graphs and Tables | 呈现数据：图表与表格
Graphs and tables are not just decorative; they are tools that help you spot patterns and communicate results. Bar charts compare categories, histograms display frequency distributions of continuous data, and scatter graphs reveal relationships between two co‑variables. Label both axes clearly, include units where relevant, and give the figure a descriptive title.
图表和表格不只是装饰，它们是你发现规律和传达结果的工具。条形图用于比较类别，直方图展示连续数据的频数分布，散点图揭示两个协变量之间的关系。要清晰标注两个坐标轴，在相关处加上单位，并为图配上描述性的标题。
Examiners often deduct marks for small mistakes: forgetting to label the axes, using unequal class intervals on a histogram, or starting an axis at a value other than zero when it distorts the visual effect. A well‑drawn graph can make your results instantly understandable, so practise constructing them under timed conditions and always refer back to your graph in the written evaluation.
考官常常会因为一些小错误而扣分：忘记标注坐标轴、在直方图上使用不相等的组距，或者将坐标轴起点设为非零值而扭曲了视觉效果。一张绘制精良的图表能让你的结果一目了然，所以要在限时条件下练习绘制，并在文字评估中回头引用你的图表。
8. Descriptive Statistics: Central Tendency and Dispersion | 描述统计：集中趋势与离散度
Descriptive statistics summarise the ‘what’ of your data. Measures of central tendency — mean, median and mode — tell you about the typical score. The mean is most informative for normally distributed interval/ratio data, but it is easily distorted by outliers. The median is the middle value and is robust to extreme scores, making it more suitable for ordinal data or skewed distributions. The mode simply indicates the most frequent value and is the only measure suitable for nominal data.
描述统计概括的是数据的“是什么”。集中趋势量数——平均值、中位数和众数——告诉你数据的典型分数。平均值对于正态分布的等距/等比数据信息最丰富，但易受异常值扭曲。中位数是中间值，对极端分数稳健，因此更适合顺序数据或偏态分布。众数仅指出现最频繁的值，也是名义数据唯一适用的量数。
Measures of dispersion, such as the range and standard deviation, reveal how spread out the scores are. The range (highest minus lowest) is quick to calculate but affected by outliers. Standard deviation indicates how much, on average, scores deviate from the mean; a small standard deviation suggests data are tightly clustered around the mean, while a large one signals wide variability. Whenever you quote a mean, also report a measure of dispersion — never present a summary statistic in isolation.
离散量数，如全距和标准差，揭示的是分数的分散程度。全距（最大值减最小值）计算快捷但受异常值影响。标准差衡量的是分数平均而言偏离平均值的程度；标准差小表明数据紧密围绕平均值，大则表明变异很大。无论何时引用平均值，都要同时报告离散量数——切忌孤立地呈现一个概括统计量。
9. Inferential Statistics: Choosing and Interpreting Tests | 推断统计：选择与解释检验
Inferential statistics help you decide whether the results are likely to reflect a genuine effect or just chance. At AS level, the two tests you need are the sign test and the chi‑squared (χ2) test. The sign test is used when you have a repeated measures design (or matched pairs) and ordinal or better data — it compares the direction of differences between pairs. The chi‑squared test is for nominal (category) data and tests whether observed frequencies differ from expected frequencies, making it ideal for questionnaires and observational tallies.
推断统计帮助你判断结果很可能反映了真实效应还是仅仅出于偶然。在AS阶段，你需要掌握两种检验：符号检验和卡方（χ2）检验。符号检验用于重复测量（或匹配对）设计且数据为顺序或更高级别——它比较配对间的差异方向。卡方检验用于名义（类别）数据，检验观察频数是否与期望频数存在差异，因此非常适合问卷和观察计数表。
| Test | When to Use | 何时使用 |
|---|---|---|
| Sign test | Repeated measures or matched pairs design; ordinal/interval data; comparing a difference in pairs. | 重复测量或匹配对设计；顺序/等距数据；比较配对间的差异。 |
| Chi‑squared | Independent groups design; | 独立组设计；名义数据；检验分类变量间的关联或拟合度。 |
After calculating your test statistic, compare it to the critical value in the given table, using the correct degrees of freedom or N value. Your result is statistically significant if the observed value is greater than or equal to the critical value for all tests except the sign test, where the observed value must be less than or equal to the critical value. Always state whether you reject the null hypothesis and refer back to the level of significance (commonly p ≤ 0.05). Do not claim your results ‘prove’ anything — use phrasing such as ‘the results suggest a significant effect’.
计算出检验统计量后，查阅给定表格中的临界值，使用正确的自由度或N值。对于除符号检验之外的所有检验，若观察值大于等于临界值，结果就具有统计显著性；而符号检验中，观察值必须小于等于临界值才显著。一定要说明你是否拒绝虚无假设，并回头提及显著水平（常用 p ≤ 0.05）。不要宣称结果“证明”了什么——使用“结果表明具有显著效应”这样的措辞。
10. Evaluating Research: Strengths, Weaknesses and Improvements | 评估研究：优势、不足与改进
Evaluation is where you earn high marks by demonstrating critical thinking. Cover four key areas: validity (internal and external), reliability, ethical issues, and generalisation. Internal validity asks whether the study truly measures what it claims — uncontrolled EVs may lower it. External validity concerns whether findings can be generalised beyond the specific setting, especially ecological validity and population validity.
评估部分正是你展示批判性思维、赢得高分的地方。请覆盖四大关键领域：效度（内部和外部）、信度、伦理问题和推广性。内部效度考察研究是否真正测量了它声称要测量的内容——未控制的额外变量可能降低内部效度。外部效度涉及研究结果能否推广到特定情境之外，特别是生态效度和人群效度。
Always suggest realistic and concrete improvements. Instead of writing ‘use a larger sample’, specify ‘recruit 100 participants from three different schools to improve representativeness’. Similarly, ‘control extraneous variables’ becomes ‘use a double‑blind procedure so that neither the participant nor the experimenter knows the condition, minimising demand characteristics and experimenter effects’. The tighter your suggestions, the better your evaluation score.
始终要提出切实可行的具体改进意见。不要写“使用更大的样本”，而要具体写成“从三所不同学校招募100名参与者以提高代表性”。类似地，将“控制额外变量”变为“使用双盲程序，这样参与者和实验者都不知道条件分配，从而最小化需求特征和实验者
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