📚 Statistics Vocabulary Quick-Memorisation Guide | 统计学术语速记指南
Mastering the language of statistics is half the battle in your Eduqas GCSE course. This guide gives you clear definitions, memorable hooks and cross-language support to lock in every key term for Year 10. Use it alongside your class notes and past papers to strengthen both English recall and bilingual understanding.
掌握统计学的语言，是攻克Eduqas GCSE课程的关键一步。本指南为你提供清晰的定义、巧妙的记忆点和双语言支持，帮你牢牢记住Year 10的每个核心术语。结合课堂笔记和历年真题一起使用，既能巩固英文回忆，也能加深中英双语理解。
1. Types of Data | 数据类型
Qualitative data describes qualities or categories that cannot be measured with numbers, such as eye colour or favourite sport. Think of ‘quality’ not ‘quantity’.
定性数据描述无法用数字衡量的性质或类别，例如眼睛颜色或最喜欢的运动。记住“定‘性’”与“性质”挂钩，而不是数值。
Quantitative data is numerical and tells us ‘how many’ or ‘how much’. It splits into discrete data, which can only take certain values (like shoe sizes or number of siblings), and continuous data, which can take any value in a range (like height or time).
定量数据是数值型的，告诉我们“多少”或“多大”。它分为离散数据，只能取特定的值（如鞋码或兄弟姐妹数量），和连续数据，可以在一个范围内取任何值（如身高或时间）。
Memory trigger: discrete = counted (think ‘discreet steps’), continuous = measured (think of a continuous line on a ruler).
记忆触发点：离散 = 可数的（想象离散的台阶），连续 = 可测量的（联想尺子上的连续刻度线）。
2. Primary and Secondary Data | 一手数据与二手数据
Primary data is information you collect yourself for a specific purpose – like running a survey or measuring plant growth in an experiment. It gives you full control but costs time.
一手数据是你自己为某个特定目的收集的信息——比如开展问卷调查或测量实验中植物的生长。你能完全掌控，但需要花费时间。
Secondary data has been collected by someone else already, such as census records, newspaper statistics or data from textbooks. It is quick to obtain but you must check its reliability.
二手数据是别人已经收集好的，例如人口普查记录、报纸上的统计数字或教科书上的数据。获取很快，但必须核查其可靠性。
Remember: primary = your own first-hand work; secondary = second-hand source.
记忆方法：primary（一手）意味着你自己的第一手工作；secondary（二手）就是现成的第二手来源。
3. Sampling Methods | 抽样方法
A population is the whole group you are interested in. A sample is a smaller subset selected to represent the population. Good sampling avoids bias.
总体是你感兴趣的整个群体。样本是从中选出的一个较小的子集，用来代表总体。好的抽样要避免偏差。
Random sampling gives every member an equal chance of being picked; think of names in a hat. Stratified sampling divides the population into groups (strata) and takes random samples from each in proportion to group size.
随机抽样让每个成员被选中的机会均等；想象从帽子里抽名字。分层抽样把总体分成几个层，然后按各层大小的比例从每层随机抽取样本。
Systematic sampling picks every k-th person from a list. Convenience sampling just uses whoever is easiest to reach – quick but often biased.
系统抽样是从名单上每隔k个人选一个。便利抽样就是找最容易接触到的人——快速但常有偏差。
Key phrase: stratified = proportional layers; systematic = fixed interval; convenience = easiest available.
关键短语：分层 = 按比例分层；系统 = 固定间隔；便利 = 最顺手可得的。
4. Frequency Tables and Diagrams | 频率表与图表
A frequency table tallies data into groups or categories, showing how often each occurs. Tally marks are grouped in fives – 卌 (four vertical lines crossed by a diagonal).
频率表把数据分组或分类记录，显示每项出现的次数。计数符号通常五个一组——四个竖线加一道斜线。
A bar chart is for categorical (qualitative) data with gaps between bars. A histogram is for continuous data with no gaps; the area of each bar represents frequency, so bar width matters.
条形图用于分类（定性）数据，条形之间有间隙。直方图用于连续数据，条形之间无间隙；每个条形的面积代表频率，因此条宽也很重要。
Pictograms use symbols to represent a number of items – always show a key. Pie charts display proportions of a whole, with angles calculated as (frequency ÷ total) × 360°.
象形图使用符号代表一定数量的项目——一定要有图例。饼图展示整体中各部分的比例，扇形角度 = (频数÷总数) × 360°。
5. Measures of Central Tendency | 集中趋势测量
The mean is the arithmetic average. Sum all values and divide by the number of values.
mean x̄ = Σx / n
均值就是算术平均数。把所有数值加起来再除以数值的个数。
The median is the middle value when data is ordered. If n is even, take the mean of the two middle numbers. The mode is the most frequent value. Remember: median = middle, mode = most.
中位数是数据排序后中间的值。如果n为偶数，就取中间两个数的均值。众数是出现次数最多的值。记住：median见“mid”（中间），mode见“most”（最多）。
For grouped data, the modal class is the interval with the highest frequency, and you can estimate the mean using midpoints: estimated mean = Σ(f × midpoint) / Σf.
对于分组数据，众数所在的组是频数最高的区间，可以用组中值估算平均数：估计均值 = Σ(频数×组中值) / Σ频数。
6. Measures of Spread | 离散程度测量
The range is simplest: largest value minus smallest value. It only uses two points so is affected by outliers.
极差最简单：最大值减去最小值。它只用到两个点，因此容易受异常值影响。
Quartiles split ordered data into four parts. Q₁ (lower quartile) is the median of the lower half, Q₂ is the overall median, Q₃ (upper quartile) is the median of the upper half. The interquartile range IQR = Q₃ – Q₁.
四分位数将有序数据分成四部分。下四分位数Q₁是下半部分的中位数，Q₂是整体的中位数，上四分位数Q₃是上半部分的中位数。四分位距 IQR = Q₃ – Q₁。
Standard deviation measures how spread out numbers are around the mean. For a sample, use the formula:
s = √[ Σ(x – x̄)² / (n – 1) ]
标准差衡量数据围绕均值的分散程度。对于样本，使用公式：s = √[ Σ(x – x̄)² / (n – 1) ]。
A smaller standard deviation means data points are closer to the mean; a larger one shows more variability.
标准差越小，数据点越靠近均值；标准差越大，变异性越强。
7. Box Plots and Cumulative Frequency | 箱线图与累积频率
A box plot (box-and-whisker) shows the minimum, Q₁, median, Q₃ and maximum. It is great for comparing distributions and spotting skew.
箱线图（箱须图）展示最小值、Q₁、中位数、Q₃和最大值，非常适合比较分布和识别偏态。
Cumulative frequency is the running total of frequencies. Plotting cumulative frequency against the upper class boundary gives an s-shaped curve, which you use to find medians and quartiles by reading off the graph.
累积频率是频率的累加总和。将累积频率对组的上限绘制出S形曲线，通过读图可以找出中位数和四分位数。
Memory: box plot = five numbers in a picture; cumulative = running total until you hit 100%.
记忆法：箱线图 = 五个数字画成一幅图；累积频率 = 不断累加直到抵达100%。
8. Scatter Diagrams and Correlation | 散点图与相关性
A scatter diagram plots bivariate data – pairs of values – to see if there is a relationship. Correlation describes the direction and strength.
散点图绘制双变量数据——成对的值——来观察是否存在关系。相关性描述关系的方向和强度。
Positive correlation means as one variable increases, the other tends to increase. Negative correlation means as one increases, the other tends to decrease. No correlation shows no clear pattern.
正相关表示一个变量增加时另一个也倾向于增加。负相关表示一个增加时另一个倾向于减少。无相关则没有明显模式。
The line of best fit goes through the points and is used to make predictions. Avoid extrapolating far beyond the data – that is unreliable.
最佳拟合线穿过各点，用于做预测。避免将预测外推得太远——那样不可靠。
Correlation does not imply causation! Just because two things are linked does not mean one causes the other.
相关不表示因果！两个事物有关联，并不意味着一个导致了另一个。
9. Probability Basics | 概率基础
Probability measures how likely an event is, from 0 (impossible) to 1 (certain). The probability of an event A is written as P(A).
P(A) = number of favourable outcomes / total number of possible outcomes
概率衡量事件发生的可能性，从0（不可能）到1（必然）。事件A的概率记作P(A)。P(A) = 有利结果数 / 所有可能结果数。
An experiment is a repeatable process; an outcome is a result; the sample space is the set of all possible outcomes. An event is a set of one or more outcomes.
试验是可重复的过程；结果是一次试验的结果；样本空间是所有可能结果的集合。事件是由一个或多个结果组成的集合。
Complementary events: P(A’) = 1 – P(A). Mutually exclusive events cannot happen at the same time; their probabilities simply add. Independent events do not affect each other; for independent A and B, P(A and B) = P(A) × P(B).
对立事件：P(A’) = 1 – P(A)。互斥事件不能同时发生，它们的概率直接相加。独立事件互不影响；对于相互独立的A和B，P(A 且 B) = P(A) × P(B)。
10. Probability Diagrams | 概率图
Tree diagrams show combined events branch by branch; multiply along branches for ‘and’, add different branches for ‘or’. Always check that probabilities on branches sum to 1.
树状图逐分支展示复合事件；沿分支相乘表示“且”，不同分支相加表示“或”。始终检查各分支概率之和是否为1。
Venn diagrams use overlapping circles to display relationships. The intersection (A ∩ B) is the overlap; the union (A ∪ B) is everything in either circle. Use the formula: P(A ∪ B) = P(A) + P(B) – P(A ∩ B).
韦恩图用重叠的圆圈展示关系。交集 (A ∩ B) 是重叠部分；并集 (A ∪ B) 是圆圈内所有区域。使用公式：P(A ∪ B) = P(A) + P(B) – P(A ∩ B)。
Two-way tables help organise conditional probabilities; read off totals from margins to solve problems.
双向表帮助整理条件概率；从表格边缘读取总数来解决问题。
11. Statistical Enquiry Cycle | 统计调查循环
The statistical enquiry cycle (Problem, Plan, Data, Analysis, Conclusion) is a structured way to tackle any statistical investigation. Begin by clearly stating the problem or question.
统计调查循环（问题、计划、数据、分析、结论）是处理任何统计调查的结构化方法。从清楚地陈述问题或疑问开始。
Plan how to collect reliable, unbiased data – choose sampling method, sample size and recording tools. Then collect the data, clean it and present it with suitable diagrams.
计划如何收集可靠、无偏差的数据——选择抽样方法、样本大小和记录工具。然后收集数据，清洗数据，并用合适的图表呈现。
Analyse using averages, spread and graphical insights. Finally, draw conclusions that answer the original question and discuss limitations.
分析时使用平均数、离散度和图形洞察。最后得出结论来回答原始问题，并讨论局限性。
Cycle reminder: PPDAC – Problem, Plan, Data, Analysis, Conclusion. This framework is the backbone of your coursework.
循环记忆：PPDAC——问题、计划、数据、分析、结论。这个框架是你课程作业的支柱。
12. Hypothesis Testing Intro | 假设检验入门
A hypothesis is a statement that can be tested. The null hypothesis (H₀) is the current belief, often stating ‘no effect’ or ‘no difference’. The alternative hypothesis (H₁) is what you suspect might be true instead.
假设是一个可以检验的陈述。零假设(H₀)是现有的看法，常表示“没有效果”或“没有差异”。备择假设(H₁)是你怀疑可能正确的情况。
A test statistic is calculated from sample data. You compare it to a critical value; if the test statistic is more extreme, you reject H₀ in favour of H₁.
检验统计量由样本数据计算得出。将其与临界值比较；如果检验统计量更极端，就拒绝H₀，接受H₁。
A p-value measures the probability of getting results at least as extreme as the observed ones, assuming H₀ is true. A small p-value (usually < 0.05) leads to rejecting H₀.
p值衡量在H₀为真的前提下，得到至少和观测结果一样极端的概率。很小的p值（通常小于0.05）意味着拒绝H₀。
Quick link: H₀ = ‘nothing is happening’; H₁ = ‘something is happening’. Small p → reject H₀, big p → do not reject H₀. Never ‘prove’ H₁ – only gather evidence against H₀.
快速联想：H₀ = “什么都没发生”；H₁ = “有事发生”。p值小 → 拒绝H₀，p值大 → 不拒绝H₀。永远不要声称“证明”了H₁——只是收集了反对H₀的证据。
Published by TutorHao | Statistics Revision Series | aleveler.com
更多咨询请联系16621398022（同微信）
屏轩国际教育cambridge primary/secondary checkpoint, cat4, ukiset,ukcat,igcse,alevel,PAT,STEP,MAT, ibdp,ap,ssat,sat,sat2课程辅导，国外大学本科硕士研究生博士课程论文辅导Cancel reply