📚 Interdisciplinary Integrated Exercises for Year 10 WJEC Statistics | WJEC 十年级统计跨学科综合题型训练
In WJEC Year 10 Statistics, the ability to apply statistical methods across different subjects is essential. Real-world data does not arrive in neat, single‑subject packages; it flows between biology, geography, psychology, business, and sport. This article helps you build confidence in tackling interdisciplinary integrated exercises by moving beyond standalone calculations and exploring how scatter graphs, probability, sampling, averages, and data representation connect with other fields you study at school. Each section presents a paired English–Chinese explanation, followed by worked examples and tips aligned to the WJEC specification.
在 WJEC 十年级统计学中，跨学科应用统计方法的能力至关重要。现实世界的数据并非整齐地按照单一学科分类；它流动于生物学、地理学、心理学、商业和体育之间。本文通过超越孤立计算、探索散点图、概率、抽样、平均数和数据表示如何与你在学校所学的其他领域相联系，帮助你建立应对跨学科综合题型的信心。每个部分都提供英中对照讲解，之后是符合 WJEC 大纲的解题示例与技巧。
1. Statistics in Biology: Genetics and Probability | 生物学中的统计：遗传学与概率
When studying inheritance, Punnett squares link directly to theoretical probability. A dihybrid cross can be modelled using the sample space of gamete combinations. The probability of an offspring having a certain genotype is simply the number of favourable outcomes divided by the total outcomes. This cross‑curricular link tests your understanding of equally likely events and sample space diagrams.
在学习遗传学时，旁氏方格直接与理论概率相连。双性状杂交可以用配子组合的样本空间来建模。子代具有某种基因型的概率就是有利结果的数量除以总结果数。这种跨学科联系考察你对等可能事件和样本空间图的理解。
Example: In pea plants, the allele for tall (T) is dominant over dwarf (t), and round seed (R) is dominant over wrinkled (r). Two heterozygous plants (TtRr) are crossed. The sample space has 16 equally likely outcomes. The probability that a seed is tall and round is 9/16. This is a simple application of the multiplication rule for independent events, but it can also be read directly from a 4×4 Punnett square.
示例：在豌豆植株中，高茎等位基因 (T) 对矮茎 (t) 为显性，圆粒 (R) 对皱粒 (r) 为显性。两株杂合植株 (TtRr) 杂交。样本空间有 16 种等可能结果。种子既高又圆的概率是 9/16。这是独立事件乘法规则的简单应用，但也可以直接从 4×4 旁氏方格中读出。
In WJEC exam questions, you may be given a partially filled Punnett square and asked to complete it, then calculate probabilities. Pay attention to whether they ask for a ratio or a probability. A ratio like 9:3:3:1 is not a probability; always express probability as a fraction, decimal, or percentage.
在 WJEC 试题中，你可能会拿到一个部分填充的旁氏方格，并被要求完成它，然后计算概率。注意题目要求的是比例还是概率。像 9:3:3:1 这样的比例不是概率；请始终将概率表示为分数、小数或百分比。
2. Geography: Population Pyramids and Averages | 地理学：人口金字塔与平均数
Population pyramids display age‑and‑sex distributions. A statistics question might ask you to estimate the median age from a population pyramid, or to compare the mean age of two countries. You will need to interpret grouped frequency tables derived from the pyramid, applying the formula for mean of grouped data: ∑(midpoint × frequency) ÷ total frequency.
人口金字塔显示年龄和性别分布。一道统计题可能要求你从人口金字塔中估算中位年龄，或比较两个国家的平均年龄。你需要解释从金字塔导出的分组频率表，应用分组数据平均数公式：∑(组中值 × 频率) ÷ 总频率。
Consider a pyramid for Country A: 0‑14 years: 3 million males and 2.9 million females; 15‑64: 10 million males, 9.8 million females; 65+: 2 million males, 2.5 million females. To find an estimate for the mean age, you must choose midpoints (e.g. 7, 39.5, 74.5) and multiply by the total frequency in each class. This demonstrates how statistics serves demography.
考虑 A 国的人口金字塔：0‑14 岁：300 万男性，290 万女性；15‑64 岁：1000 万男性，980 万女性；65 岁以上：200 万男性，250 万女性。要估算平均年龄，你必须选择组中值（例如 7, 39.5, 74.5）并乘以每个类别的总频率。这便是统计学如何为人口学服务。
WJEC often includes a comparison question: ‘Use the mean and median to decide which country has an older population.’ Here you must recognise that a higher mean age might be pulled up by a small number of very elderly people, so the median may give a better picture of a typical resident. Always comment on the shape of the distribution (e.g. symmetrical or right‑skewed) when justifying your choice.
WJEC 常包含比较题：“使用平均数和中位数判断哪个国家的人口更老。”此时你必须认识到，较高的平均年龄可能被少数非常年长的人拉高，所以中位数也许能更准确地反映典型居民的情况。在说明你的选择时，请始终评论分布的形状（例如对称或右偏）。
3. Business and Economics: Market Research Sampling | 商业与经济学：市场调研抽样
Businesses rely on surveys to understand consumer behaviour. In WJEC statistics, you must evaluate different sampling methods – simple random, stratified, systematic, and quota – within real business contexts. A question might describe a company wanting to launch a new product and ask which sampling technique is most appropriate, giving reasons related to cost, time, and representativeness.
企业依赖调查了解消费者行为。在 WJEC 统计学中，你必须在真实商业情境中评估不同的抽样方法——简单随机、分层、系统抽样和配额抽样。题目可能描述一家公司想要推出新产品，并询问哪种抽样技术最合适，给出与成本、时间和代表性相关的理由。
For instance, a supermarket chain wants to survey customer satisfaction across its 50 UK stores, each of differing size. A stratified sample by store size (small, medium, large) ensures representation from each category. You could calculate the number of questionnaires per stratum using (stratum size ÷ total customers) × sample size. This proportional allocation reduces bias and improves accuracy. Alternatively, a systematic sample (every 15th customer entering) might be cheaper but could miss those who shop at quieter times.
例如，一家连锁超市想要调查其全英 50 家门店的顾客满意度，各门店规模不同。按门店规模（小型、中型、大型）进行分层抽样可确保每个类别都有代表。你可以使用（层大小 ÷ 总顾客数）× 样本容量来计算每层应发放的问卷数。这种比例分配能减少偏差、提高准确度。另一方面，系统抽样（每第 15 位进入的顾客）可能成本更低，但可能会遗漏在较安静时段购物的顾客。
WJEC questions often provide a table of population data and ask you to select a sample size, then calculate the numbers for each stratum. Be careful to round to the nearest whole number and adjust if the total does not sum exactly to your target sample size. Also be prepared to discuss non‑sampling errors like voluntary response bias from online surveys, linking back to business reliability.
WJEC 题目常给出一个人口数据表，要求你选择样本容量，然后计算每层的数量。注意四舍五入到最接近的整数，如果总计不完全等于目标样本容量则进行调整。同时准备讨论非抽样误差，如在线调查中的自愿响应偏差，并联系到商业数据的可靠性。
4. Physical Education: Comparing Athlete Performance Using Box Plots | 体育：利用箱线图比较运动员表现
In sport science, box plots (box‑and‑whisker diagrams) are used to compare the consistency and central tendency of athletes’ times or scores. A WJEC question may present the times of two sprinters over several races and ask you to draw and interpret box plots, commenting on the interquartile range (IQR) and range.
在体育科学中，箱线图（盒须图）被用来比较运动员成绩的一致性和集中趋势。WJEC 题目可能给出两名短跑运动员多场比赛的成绩，并要求你绘制并解读箱线图，评论四分位距 (IQR) 和全距。
Suppose Sprinter A has times: 10.1, 10.3, 10.4, 10.5, 10.5, 10.6, 10.8. The five‑number summary: min 10.1, Q₁ 10.35, median 10.5, Q₃ 10.55, max 10.8. IQR = 0.2. Sprinter B: 10.2, 10.2, 10.4, 10.5, 10.7, 11.0, 11.2. Summary: 10.2, 10.3, 10.5, 10.85, 11.2; IQR = 0.55. Although medians are identical, Sprinter A’s smaller IQR shows greater consistency. In a match context, you would recommend Sprinter A for a relay requiring reliability.
假设运动员 A 的成绩为：10.1, 10.3, 10.4, 10.5, 10.5, 10.6, 10.8。五数概括：最小值 10.1，Q₁ 10.35，中位数 10.5，Q₃ 10.55，最大值 10.8。IQR = 0.2。运动员 B：10.2, 10.2, 10.4, 10.5, 10.7, 11.0, 11.2。概括：10.2, 10.3, 10.5, 10.85, 11.2；IQR = 0.55。尽管中位数相同，运动员 A 更小的 IQR 显示出更高的一致性。在比赛情境中，你会推荐运动员 A 参加对可靠性要求高的接力赛。
WJEC marks are awarded for correctly identifying outlier boundaries (1.5 × IQR rule) and for context‑based comparisons: ‘Athlete B’s larger range shows that he can produce very fast times but is less predictable.’ Always link statistical measures to the real‑world implication asked for in the question.
WJEC 会根据正确识别异常值界限（1.5 × IQR 规则）以及基于情境的比较来评分：“运动员 B 更大的全距表明他能跑出非常快的成绩但较不可预测。”始终将统计量与题目所要求的现实含义联系起来。
5. Biology and Environmental Science: Scatter Graphs of Growth | 生物学与环境科学：生长散点图
Measuring plant growth under different light intensities generates bivariate data. You might plot height against light intensity and notice a positive correlation up to a point, after which it plateaus. This leads naturally to WJEC tasks: draw a scatter graph, describe the correlation (strong/weak, positive/negative), draw a line of best fit, and interpolate or extrapolate.
测量在不同光照强度下的植物生长会生成二元数据。你可能会绘制高度与光照强度的关系图，并注意到在一定范围内呈正相关，之后趋于平缓。这自然会引出 WJEC 的任务：绘制散点图、描述相关性（强/弱、正/负）、绘制最佳拟合线，并进行内插或外推。
An exam question might give data for 10 seedlings: light (lux) and height (cm). After plotting, the points rise steeply then level off, forming a curve. While the ‘line of best fit’ in WJEC Year 10 is usually a straight line, questions sometimes ask you to fit a line by eye to the linear part only. The phrase ‘up to about 2000 lux’ allows you to ignore the plateau, showing a very strong positive correlation (r close to 1). You can then estimate the height at 1500 lux by reading from your line.
考试题可能给出 10 株幼苗的数据：光照（勒克斯）和高度（厘米）。绘图后，点先陡升然后趋于平缓，形成曲线。尽管在 WJEC 十年级中“最佳拟合线”通常是直线，但题目有时会让你仅在线性部分凭眼力拟合一条直线。“约 2000 勒克斯以下”这一表述让你忽略平缓段，显示出非常强的正相关（r 接近 1）。然后你可以通过读图估算在 1500 勒克斯下的高度。
Extrapolation beyond the data range (e.g. predicting height at 5000 lux) requires a warning: the relationship may no longer be linear, and the prediction is unreliable. This concept appears in WJEC ‘evaluate the reliability’ questions, linking statistics to biological understanding of limiting factors.
超出数据范围的外推（例如预测 5000 勒克斯下的高度）需要给出警告：该关系可能不再是线性的，预测并不可靠。这一概念会出现在 WJEC “评价可靠性”的提问中，将统计学与生物学中对限制因素的理解联系起来。
6. Citizenship and Social Science: Interpreting Bar Charts and Misleading Graphs | 公民教育与社会学：解读条形图和误导性图表
Social statistics frequently appear in the media. WJEC expects you to critique bar charts, pictograms, and pie charts that may be misleading due to truncated axes, irregular scaling, or omitted data. A question might present two bar charts about crime rates in two areas and ask why the chart appears to exaggerate differences.
社会统计常出现在媒体上。WJEC 期待你学会批评条形图、象形图和饼图中可能因切断坐标轴、不规则的刻度或遗漏数据而造成的误导。题目可能呈现两个地区犯罪率的条形图，并询问为什么图表看起来夸大了差异。
For example, a bar chart shows Town X with 20 crimes and Town Y with 25 crimes, but the vertical axis starts at 15 instead of 0. The bar for Town X appears three times shorter than the bar for Town Y, giving a false impression. You need to state that the difference is actually only 5, which is relatively small, and that the scale is misleading. Another common trick is using 3D bars that distort height perception. Always check labelling, scale, and whether frequencies or percentages are used.
例如，一张条形图显示 X 镇犯罪 20 起，Y 镇犯罪 25 起，但纵轴起始于 15 而非 0。X 镇的条看起来比 Y 镇的条短了三分之二，给人以错误印象。你需要指出实际差异只有 5，相对较小，而刻度的设置具有误导性。另一个常见花招是使用扭曲高度感知的 3D 条形。始终检查标签、刻度，以及使用的是频数还是百分比。
WJEC also tests if you can improve the presentation: redraw the chart with a zero base, use simple 2D bars, and perhaps add data labels to show exact values. This links to the ‘presenting data’ objective in the specification.
WJEC 也会测试你是否能改进呈现方式：用零基线重新绘制图表，使用简单的 2D 条形，或许添加数据标签以显示确切数值。这与大纲中“呈现数据”的目标相联系。
7. Geography: Cumulative Frequency and River Discharge | 地理学：累积频率与河流流量
Cumulative frequency curves are used in hydrology to analyse river discharge data over time. A WJEC question might provide a table of daily discharge (cubic metres per second) and ask you to construct a cumulative frequency table and draw an ogive, then find the median and interquartile range of discharge.
水文学中使用累积频率曲线来分析河流流量随时间变化的数据。WJEC 题目可能提供一个日流量（立方米/秒）表，让你构建累积频率表并绘制拱形图，然后求流量的中位数和四分位距。
Given classes 0‑50, 50‑100, 100‑200 m³/s, you first calculate upper class boundaries: 50, 100, 200. Cumulative frequencies are plotted at these upper boundaries. From the curve, the median discharge is read at 50% of total frequency, Q₁ at 25%, and Q₃ at 75%. The IQR indicates the spread of typical flow; a small IQR means the river is regulated, a large IQR suggests flashy discharge. You can then compare two rivers: one with a steep curve in the middle (less variability) and one with a gentle slope (high variability).
给定组 0‑50, 50‑100, 100‑200 m³/s，你首先计算上限组界：50, 100, 200。在这些上限处绘制累积频率点。从曲线上，中位数流量在总频数的 50% 处读出，Q₁ 在 25%，Q₃ 在 75%。IQR 表明典型流量的分散程度；小的 IQR 意味着河流受调节，大的 IQR 则暗示暴涨暴落的流量。然后你可以比较两条河流：一条曲线中段陡峭（变异性较小），另一条平缓（变异性大）。
WJEC often interleaves ‘describe the relationship’ with a scatter graph of discharge vs rainfall, so you might need to switch between statistical techniques in one question. Practise explaining why the median is more appropriate than the mean when the data is skewed by a flood event.
WJEC 常将“描述关系”与流量 vs 降雨量的散点图交织在一起，因此你可能需要在一道题中切换不同的统计方法。练习解释为什么当数据被洪水事件影响而出现偏态时，中位数比平均数更合适。
8. Psychology: Designing a Questionnaire and Types of Data | 心理学：设计问卷与数据类型
Psychological research relies heavily on questionnaires. In WJEC statistics, you might be asked to critique a questionnaire on a topic like sleep habits, then suggest improvements. You must identify question design features: open vs closed questions, leading questions, double barrelled questions, overlapping response categories, and whether data collected is qualitative or quantitative, discrete or continuous.
心理学研究严重依赖问卷。在 WJEC 统计学中，你可能会被要求评论一份关于睡眠习惯等主题的问卷，然后提出改进建议。你必须识别问题设计的特点：开放式与封闭式问题、诱导性问题、双重提问、重叠的响应类别，以及收集到的数据是定性的还是定量的、离散的还是连续的。
Example of a poor question: ‘Do you always sleep well and feel refreshed?’ This is double barrelled; a respondent might sleep well but not feel refreshed. Response options: ‘Yes / No / Sometimes’ is not exhaustive and includes a frequency in a yes/no set. An improved version: two questions, one about sleep quality and another about feeling refreshed, each with a 5‑point Likert scale from ‘Never’ to ‘Always’. The resulting data is ordinal (qualitative but ordered), which you can summarise with the mode and median, not the mean.
一个糟糕问题的例子：“你总是睡得好并感到神清气爽吗？”这是双重提问；受访者可能睡得好但并未感到神清气爽。响应选项：“是 / 否 / 有时”既非穷尽又在是否题里加了频率。改进版：两个问题，一个关于睡眠质量，另一个关于是否感到神清气爽，各自使用从“从不”到“总是”的 5 级李克特量表。结果数据为有序数据（定性但有序），你可以用众数和中位数来总结，而不能用平均数。
WJEC expects you to link questionnaire analysis to sampling. If a psychology teacher hands out a questionnaire to only his own class, the sample is a convenience sample, prone to bias. You must be able to suggest and justify a better sampling frame.
WJEC 期待你将问卷分析与抽样联系起来。如果一位心理学老师只将问卷发给他自己班的同学，那么样本就是便利样本，易于产生偏差。你必须能够提出并说明更好的抽样框架。
9. Economics: Time Series and Trend Lines | 经济学：时间序列与趋势线
Economic data such as monthly unemployment rates allow you to practise time series analysis. A WJEC question may give a table of values over 12 months and ask for a four‑point moving average to smooth out seasonal fluctuations, then plot both the raw data and the moving average on a graph to identify the trend.
诸如月度失业率之类的经济数据可让你练习时间序列分析。WJEC 题目可能给出 12 个月的数据表，要求你计算四点移动平均数以平滑季节波动，然后在图上同时绘制原始数据和移动平均数以识别趋势。
To calculate the first four‑point moving average for Jan‑Apr values: (Jan+Feb+Mar+Apr) ÷ 4, placed at the centre between Feb and Mar. The second is (Feb+Mar+Apr+May) ÷ 4. Plot these moving averages and join them with a line – this is the trend line. You can then comment on whether unemployment is generally increasing, decreasing, or steady. If a question asks for a prediction, you can extrapolate the trend line, but always mention reliability decreases the further you go from the data.
计算一至四月数值的第一个四点移动平均数：(Jan+Feb+Mar+Apr) ÷ 4，放置于二月和三月之间。第二个是 (Feb+Mar+Apr+May) ÷ 4。绘制这些移动平均数并用线相连——这就是趋势线。然后你可以评论失业率总体是在上升、下降还是保持平稳。如果题目要求预测，你可以外推趋势线，但始终要提及离现有数据越远，可靠性越低的道理。
WJEC sometimes combines this with seasonal variation: subtract the trend value from the actual value to get the seasonal effect. For a Year 10 student, the main focus is calculating moving averages and plotting them, but a simple descriptive comment on peaks and troughs can gain marks.
WJEC 有时会将此与季节波动结合：用实际值减去趋势值即可得到季节效应。对十年级学生而言，重点在于计算移动平均数并进行绘图，但对波峰和波谷的简单描述性评论也能得分。
10. Environmental Science: Interpret and Compare Two-Way Tables | 环境科学：解读和比较双向表
Two‑way tables appear in studies of recycling habits, energy use, or wildlife sightings across habitats. These tables allow you to compute marginal, joint, and conditional relative frequencies. A WJEC task could provide a table of whether households recycle (yes/no) across three towns, then ask for proportions and a comparison.
双向表出现在对回收习惯、能源使用或不同栖息地野生动物目击的研究中。这些表格让你能够计算边际、联合和条件相对频率。WJEC 的任务可能提供一份表格，列出三个城镇中家庭是否回收（是/否）的情况，然后让你计算比例并进行比较。
| Town / 城镇 | Recycle / 回收 | Do not recycle / 不回收 | Total / 总计 |
|---|---|---|---|
| A | 120 | 30 | 150 |
| B | 85 | 65 | 150 |
| C | 40 | 110 | 150 |
| Total | 245 | 205 | 450 |
From this table, 80% of households in Town A recycle (120/150), compared to only 26.7% in Town C (40/150). The proportion of all households that recycle is 245/450 ≈ 0.544 (54.4%). A conditional proportion like ‘of those who recycle, what proportion live in Town A?’ is 120/245 ≈ 0.49. This interpretation is directly useful in environmental campaigns, where statistics identifies target areas for intervention.
由该表可知，A 镇 80% 的家庭回收（120/150），而 C 镇仅有 26.7%（40/150）。全部家庭中回收的比例为 245/450 ≈ 0.544（54.4%）。条件比例如“在回收家庭中，有多少比例住在 A 镇？”为 120/245 ≈ 0.49。这种解读在环保运动中非常实用，可利用统计学确定干预的目标地区。
WJEC questions frequently ask ‘Compare the recycling rates in Town A and Town C’ — ensure your comparison uses both absolute numbers and proportions to demonstrate deeper understanding, and speculate on a possible reason (e.g. Town A may have a better recycling infrastructure).
WJEC 题目经常要求“比较 A 镇和 C 镇的回收率”——确保你的比较同时使用了绝对数和比例以展示更深入的理解，并推测可能的原因（例如 A 镇可能有更完善的回收基础设施）。
11. Combining Probability with Health Science: Screening Tests | 概率与健康科学的结合：筛查检测
Medical screening tests illustrate conditional probability in a powerful way. A WJEC question may describe a test for a virus that is 95% accurate, but the virus is rare (affects 1 in 500). Using a two‑way table or tree diagram, you can calculate the probability that a person actually has the virus given a positive test result – a classic ‘false positive’ problem.
医学筛查检测强有力地展示了条件概率。WJEC 题目可能描述一种对病毒检测的准确率为 95%，但该病毒很罕见（每 500 人中有 1 人感染）。利用双向表或树状图，你可以计算在检测结果为阳性的条件下，一个人真正感染病毒的概率——一个经典的“假阳性”问题。
Assume a population of 10,000. Infected: 20 (1 in 500). Non‑infected: 9,980. Test is positive for 95% of infected: 19; negative for 5%: 1. For non‑infected, 5% test positive (false positive): 499; 95% negative: 9,481. So total positive tests = 19 + 499 = 518. Of these, only 19 have the virus. The conditional probability = 19/518 ≈ 0.0367, or about 3.7%. Thus even with a positive test, the chance is very low – a surprising but logically sound conclusion that tests probabilistic reasoning.
假设人口为 10,000。感染者：20（每 500 人中 1 人）。未感染者：9,980。检测对 95% 的感染者呈阳性：19；5% 呈阴性：1。对未感染者，5% 检测呈阳性（假阳性）：499；95% 呈阴性：9,481。因此阳性检测总数 = 19 + 499 = 518。其中只有 19 人确实感染病毒。条件概率 = 19/518 ≈ 0.0367，约 3.7%。因此即使检测呈阳性，感染的概率也非常低——这是一个令人惊讶但在逻辑上合理的结论，考察你的概率推理能力。
WJEC requires clear communication: you must define the events, draw an accurate tree diagram with probabilities on the branches, and use the formula P(virus|positive) = P(virus ∩ positive) / P(positive). This cross‑curricular link with health education makes statistics memorable and relevant.
WJEC 要求清晰表述：你必须定义事件，绘制标有概率的准确树状图，并使用公式 P(感染|阳性) = P(感染∩阳性) / P(阳性)。这种与健康教育的跨学科联系让统计学变得既难忘又贴近现实。
12. Critical Thinking and Summative Practice Across Disciplines | 批判性思维与跨学科总结练习
The ultimate skill WJEC aims to test is your ability to move flexibly between statistical tools when given a complex, multi‑part scenario. You might receive a brief from a council about litter, integrating survey results, correlation with footfall, sampling considerations, and misleading claims. Practice by designing your own interdisciplinary problem: take one dataset and ask at least three different statistical questions that link to three different subjects.
WJEC 最终要考察的技能是，当你拿到一个复杂的、多部分的情境时，能否灵活地在不同的统计工具之间切换。你可能会收到一份来自市政厅关于乱扔垃圾的简报，它综合了调查结果、与人流量的相关性、抽样考虑以及误导性声称。通过自己设计跨学科问题来练习：取一个数据集，提出至少三个不同的统计问题，分别与三个不同的学科相联系。
For example, using heart rate data from a PE lesson: (1) Calculate the mean and range of resting and post‑exercise heart rates (Sports Science); (2) Draw a scatter graph of heart rate vs time after exercise to describe correlation (Biology); (3) Evaluate whether a sample of 10 students from one class can be generalised to the whole school (Social Science). This method trains you to see statistics not as an isolated subject but as a language for understanding the world.
例如，利用体育课上的心率数据：(1) 计算静息心率和运动后心率的平均数和全距（运动科学）；(2) 绘制运动后心率与时间的散点图并描述相关性（生物学）；(3) 评价一个班级 10 名学生的样本能否推广到全校（社会科学）。这种方法训练你不要将统计学视为一门孤立的学科，而是将其视为理解世界的一种语言。
As you revise for WJEC Year 10 Statistics, keep a list of cross‑curricular vocabulary: ‘reliable’, ‘valid’, ‘representative’, ‘bias’, ‘extrapolation’, ‘causation vs correlation’. Ensure you can use these terms precisely in English and in your mother tongue to unlock top marks in written evaluations.
在你为 WJEC 十年级统计复习时，请保留一份跨学科词汇表：“可靠的”、“有效的”、“有代表性的”、“偏倚”、“外推”、“因果关系 vs 相关关系”。确保你能用英语和母语准确使用这些术语，以便在书面评估中获得高分。
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