📚 AS AQA Science: Vocabulary & Terminology Quick Memorisation Guide | AS AQA 科学：词汇术语速记指南
Mastering the precise language of science is essential for success in AS AQA Science. This guide breaks down the most frequently tested vocabulary and terminology, offering clear definitions, paired explanations, and memory aids to help you learn efficiently and avoid common confusion.
掌握科学的精确语言对于在 AS AQA 科学考试中取得成功至关重要。本指南分解了最常考到的词汇和术语，提供清晰的定义、双语解释和记忆辅助，帮助你高效学习并避免常见的混淆。
1. The Scientific Method: Key Terms | 科学方法核心术语
The scientific method is a logical process of investigation. An observation leads to a question, which is then turned into a hypothesis – a testable statement that suggests an explanation. A prediction is a specific outcome expected if the hypothesis is correct, often written as ‘If… then…’ A well-tested hypothesis may become a theory, which is a broad explanation supported by a large body of evidence, while a law describes a concise relationship in nature, usually expressed mathematically.
科学方法是一套逻辑探究过程。观察引发问题，然后形成假设——一个可验证的、提出某种解释的陈述。预测是在假设正确的前提下期望出现的具体结果，常写成”如果……那么……”的形式。经过充分检验的假设可能成为理论，即由大量证据支持的广泛解释；而定律则描述自然界中简洁的关系，通常以数学形式表达。
- Hypothesis: A testable statement (e.g., ‘Light is needed for photosynthesis.’)
- 假设：一个可验证的陈述（例如”光合作用需要光”）。
- Prediction: A forecast of results (e.g., ‘If light intensity increases, then the rate of photosynthesis will increase.’)
- 预测：对结果的预报（例如”如果光照强度增加，那么光合作用速率将增加”）。
2. Variables and Controls | 变量与控制
In any experiment, we change and measure variables. The independent variable (IV) is the one you deliberately change or select. The dependent variable (DV) is what you measure or observe; its value depends on the IV. Control variables are all other factors that must be kept constant to ensure a fair test, so that any change in the DV can be attributed solely to the IV.
在任何实验中，我们都会改变和测量变量。自变量 (IV) 是你有意改变或选择的量。因变量 (DV) 是你测量或观察的量，它的值依赖于自变量。控制变量 是必须保持不变的所有其他因素，以确保公平测试，这样因变量的任何变化才能仅仅归因于自变量的变化。
- Independent variable: ‘I change’
- 自变量：”我改变的量”
- Dependent variable: ‘the Data collected’
- 因变量：”收集到的数据”
- Control variable: kept the ‘Same’
- 控制变量：保持”相同”
3. Accuracy, Precision, and Errors | 准确度、精密度与误差
Accuracy is how close a measured value is to the true value. Precision refers to how close repeated measurements are to each other, regardless of whether they are near the true value. A measurement can be precise but not accurate (all readings clustered away from the true value). Systematic errors cause all readings to shift in the same direction (e.g., a zero error on a balance), affecting accuracy. Random errors cause unpredictable scatter and affect precision; they can be reduced by taking multiple readings and calculating a mean.
准确度 是指测量值与真实值的接近程度。精密度 是指多次测量结果之间的相互接近程度，无论它们是否靠近真实值。一个测量可以精密但不准确（所有读数聚集在偏离真值的地方）。系统误差 使所有读数向同一方向偏移（如天平未归零），影响准确度。随机误差 导致不可预测的离散，影响精密度；可通过多次读数取均值来减小。
| Term (术语) | Affects (影响) | Reduced by (减小方法) |
|---|---|---|
| Systematic error (系统误差) | Accuracy (准确度) | Recalibrate apparatus, correct zero error (重新校准仪器，修正零误差) |
| Random error (随机误差) | Precision (精密度) | Repeat readings, use more sensitive equipment (重复读数，使用更灵敏设备) |
4. Reliability, Validity, and Resolution | 可靠性、有效性与分辨率
Reliability (or repeatability) indicates whether similar results are obtained when an experiment is repeated under the same conditions. Validity is whether the experiment truly tests the hypothesis and measures the intended variable, while controlling others. Resolution is the smallest change an instrument can detect; an instrument with higher resolution gives more precise readings but does not guarantee accuracy. A reliable experiment is reproducible, and a valid conclusion comes from a fair test where only the IV affects the DV.
可靠性（或可重复性）是指在相同条件下重复实验时能否获得相似的结果。有效性 是指实验是否真正检验了假设并测量了预定的变量，同时控制住了其他变量。分辨率 是仪器可检测到的最小变化；分辨率更高的仪器能给出更精密的读数，但不保证准确。可靠的实验具有可复现性，有效的结论来自自变量单独影响因变量的公平测试。
- Reliable: consistent results; ‘Repeats give similar numbers.’
- 可靠的：结果一致；”重复得到相近的数字”。
- Valid: tests the intended idea; ‘measures what it’s supposed to.’
- 有效的：检验了预期的想法；”测量了该测量的量”。
5. Measurements and SI Units | 测量与国际单位制
All AS science subjects rely on SI (Systeme International) units. The seven base quantities and their units are shown below. All other units are derived units formed by combining base units, e.g., velocity in m s⁻¹, force in kg m s⁻² (Newton, N). Always present your measurements with the correct unit and to an appropriate number of significant figures.
所有 AS 科学学科都依赖 SI（国际单位制）。下面列出了七个基本量及其单位。所有其他单位都是通过组合基本单位形成的导出单位，例如速度的单位是 m s⁻¹，力的单位是 kg m s⁻²（牛顿，N）。始终用正确的单位和适当的有效数字位数来表示你的测量结果。
| Quantity (量) | Unit (单位) | Symbol (符号) |
|---|---|---|
| Length (长度) | metre (米) | m |
| Mass (质量) | kilogram (千克) | kg |
| Time (时间) | second (秒) | s |
| Electric current (电流) | ampere (安培) | A |
| Thermodynamic temperature (热力学温度) | kelvin (开尔文) | K |
| Amount of substance (物质的量) | mole (摩尔) | mol |
| Luminous intensity (发光强度) | candela (坎德拉) | cd |
6. Prefixes and Powers of Ten | 词头与10的幂次
Prefixes are used with units to express very large or very small quantities without writing many zeros. You must know the names, symbols, and corresponding powers of ten for the most common prefixes used in AQA AS Science. Converting between units (e.g., cm to m) is a key skill.
词头与单位连用，以表达非常大或非常小的量，而无需书写很多个零。你必须掌握 AQA AS 科学中最常见的词头名称、符号以及相应的 10 的幂次。单位换算（例如 cm 与 m 之间的换算）是一项关键技能。
| Prefix (词头) | Symbol (符号) | Power of Ten (10的幂) | Example (示例) |
|---|---|---|---|
| pico (皮可) | p | 10⁻¹² | 1 pF = 10⁻¹² F |
| nano (纳诺) | n | 10⁻⁹ | 1 nm = 10⁻⁹ m |
| micro (微) | μ | 10⁻⁶ | 1 μA = 10⁻⁶ A |
| milli (毫) | m | 10⁻³ | 1 mV = 10⁻³ V |
| centi (厘) | c | 10⁻² | 1 cm = 10⁻² m |
| kilo (千) | k | 10³ | 1 kg = 10³ g |
| mega (兆) | M | 10⁶ | 1 MHz = 10⁶ Hz |
| giga (吉伽) | G | 10⁹ | 1 GHz = 10⁹ Hz |
| tera (太拉) | T | 10¹² | 1 TB = 10¹² bytes |
7. Data Presentation Terms | 数据呈现术语
Data can be displayed in tables, line graphs (for continuous variables, often with a line of best fit), bar charts (for discrete categories), scatter graphs, and histograms (for frequency distributions). An anomalous result / outlier is a data point that does not fit the overall trend; it should be identified, repeated if possible, and excluded from the line of best fit. The line of best fit (or curve) shows the underlying relationship and can be used to make interpolations.
数据可以用表格、线形图（用于连续变量，常带有最佳拟合线）、条形图（用于离散类别）、散点图和直方图（用于频率分布）来展示。异常结果 / 异常值 是不符合整体趋势的数据点；应当识别出来，如果可能则予以重做，并在画最佳拟合线时予以剔除。最佳拟合线（或曲线）显示了基本的关系，可用于进行内插。
- Categoric variable: labels or names (e.g., colour, type of material) → bar chart
- 分类变量：标签或名称（例如颜色、材料种类）→ 条形图
- Continuous variable: any numerical value within a range → line graph
- 连续变量：某个范围内的任何数值 → 线形图
- Trend: a pattern or relationship, e.g., ‘as force increases, extension increases proportionally.’
- 趋势：一种模式或关系，例如”随着力增加，伸长量成正比增加”。
8. Uncertainty and Significant Figures | 不确定度与有效数字
Uncertainty expresses the range within which the true value is expected to lie. The absolute uncertainty of a single reading is often ± half the smallest scale division; for digital instruments it is ±1 in the last digit. When two readings are taken to find a difference (e.g., temperature rise), the absolute uncertainty is ± the smallest scale division. Percentage uncertainty = (absolute uncertainty / measured value) × 100%. Significant figures reflect the precision of a measurement; your final answer should generally be given to the same number of significant figures as the least precise piece of data used in the calculation.
不确定度 表示真值预期所在的范围。单次读数的绝对不确定度 通常为 ± 最小刻度的一半；对于数字仪器，则取 ± 最后一位的 1。当使用两次读数求差值（如温升）时，绝对不确定度为 ± 最小刻度值。百分不确定度 = (绝对不确定度 / 测量值) × 100%。有效数字 反映测量的精密度；最终答案通常应保留与计算中所用最不精密数据相同的有效数字位数。
Percentage uncertainty = (Absolute uncertainty / Measured value) × 100%
百分不确定度 = (绝对不确定度 / 测量值) × 100%
- 2.50 ± 0.05 cm has absolute uncertainty 0.05 cm and percentage uncertainty (0.05/2.50)×100 = 2.0%.
- 2.50 ± 0.05 cm 的绝对不确定度为 0.05 cm，百分不确定度为 (0.05/2.50)×100 = 2.0%。
9. Evaluating Evidence | 评估证据
A conclusion states whether the data supports the hypothesis and should refer to the trend or pattern observed. Evaluation involves discussing the limitations of the experiment and suggesting improvements. Consider whether systematic or random errors were present, whether control variables were adequately managed, and whether the data are reliable (repeatable) and valid. Propose specific, practical improvements, e.g., ‘use a data logger to reduce reaction time error’ or ‘insulate the beaker to minimise heat loss.’
结论 说明数据是否支持假设，并应提及观察到的趋势或模式。评估 包括讨论实验的局限性并提出改进建议。思考是否存在系统或随机误差、控制变量是否得到充分管理、数据是否可靠（可重复）以及是否有效。提出具体、切实可行的改进措施，例如”使用数据记录仪以减少反应时间误差”或”将烧杯隔热以尽量减少热量散失”。
- Limitation: a weakness in the method that could affect accuracy or reliability.
- 局限性：方法中可能影响准确度或可靠性的弱点。
- Improvement: a specific action to overcome a limitation, e.g., ‘use a fiducial marker for timing oscillations.’
- 改进：克服局限性的具体行动，例如”使用一个定位标记来为振荡计时”。
10. Memory Techniques and Mnemonics | 记忆技巧与助记符
Mnemonics make recall faster. For variables, remember ‘Cows Moo Softly’ – Change, Measure, Same (Change = IV, Measure = DV, Same = Control variables). Another is ‘DRY MIX’: Dependent, Responding, Y-axis; Manipulated, Independent, X-axis. For prefixes, use the phrase ‘King Henry Died By Drinking Chocolate Milk’ (Kilo, Hecto, Deca, Base, Deci, Centi, Milli) but adapt to AS needs. Visualise accuracy vs precision with a target board: arrows clustered together but away from bullseye are precise but not accurate. Link ‘precise’ with ‘reproducible’ (both start with ‘p’ helps some). To distinguish reliability and validity: a broken thermometer gives reliable (consistent) results but they are not valid because it measures the wrong temperature.
助记符能让回忆更快。对于变量，记住 “Cows Moo Softly” – Change, Measure, Same（Change = 自变量，Measure = 因变量，Same = 控制变量）。另一个是 “DRY MIX”：Dependent, Responding, Y-axis; Manipulated, Independent, X-axis。对于词头，可以使用短语 “King Henry Died By Drinking Chocolate Milk”（Kilo, Hecto, Deca, 基本单位, Deci, Centi, Milli），但需根据 AS 需要进行调整。用箭靶图来形象化准确度与精密度：箭矢簇拥在一起但偏离靶心，就是精密但不准确。将 “precise” 与 “reproducible” 联系起来（都以 “p” 开头，对部分人有帮助）。要区分可靠性和有效性：一支破损的温度计能给出可靠（一致）的结果，但它们无效，因为它测量的是错误的温度。
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