📚 KS3 Edexcel Statistics: Glossary Quick-Reference Guide | KS3 Edexcel 统计：词汇术语速记指南
This guide is designed to help KS3 students following the Edexcel curriculum master essential statistical vocabulary. Understanding these terms is the first step to confidently collecting, analysing, and presenting data. Each key English term is paired with its Chinese equivalent, a clear definition, and a memorable example, followed by a mnemonic tip to lock it into your long-term memory.
本指南旨在帮助学习 Edexcel 课程的 KS3 学生掌握核心统计词汇。理解这些术语是自信地收集、分析和呈现数据的第一步。每个关键英文术语都配有其中文对应词、清晰的定义和一个易于记忆的示例，随后附上一个助记技巧，帮助你将知识牢牢锁定在长期记忆中。
1. Data | 数据
Data refers to a collection of facts, numbers, or measurements that describe something. Think of it as raw material before we process it into information. At KS3, we often classify data into qualitative categories, which describe qualities like eye colour, and quantitative numbers, which represent measurable counts like height in centimetres.
数据是指描述某事物的一组事实、数字或测量值。可以把它看作是加工成信息之前的原材料。在 KS3 阶段，我们通常将数据分为描述性质（如眼睛颜色）的定性分类数据和代表可测量计数（如以厘米为单位的的身高）的定量数字数据。
- Qualitative data: ‘The favourite crisp flavour in class is salt and vinegar.’
- 定性数据：“班上最喜欢的薯片口味是盐醋味。”
- Quantitative data: ‘The average handspan in Year 8 is 17.3 cm.’
- 定量数据：“八年级学生的平均手掌宽度为 17.3 厘米。”
- Memory tip: Data is the plural of datum, just like facts are many pieces of a puzzle. 助记技巧：Data 是 datum 的复数形式，就像拼图由许多小块拼成。
2. Mean | 平均数
The mean is a measure of average found by adding up all the values in a set and dividing by the total number of values. It is the ‘fair share’ value that each item would get if the total were split equally. Be careful: the mean can be affected by extremely large or small outliers.
平均数是把所有数值加起来，再除以数值的总个数，得到的一种集中趋势度量。它是如果总和被平均分配，每个项目所得到的“公平份额”。要注意：平均数会受到极大或极小异常值的影响。
- Formula: Mean = (Sum of all values) ÷ (Number of values).
- 公式：平均数 = （所有数值之和）÷ （数值的个数）。
- Example: The mean of 3, 5, and 7 is (3 + 5 + 7) ÷ 3 = 5.
- 示例：3、5 和 7 的平均数为 (3 + 5 + 7) ÷ 3 = 5。
- Memory tip: Think of ‘mean’ as ‘sharing the MEANz’ equally. 助记技巧：将“mean”想象成“平均地分享财富（means）”。
3. Median | 中位数
The median is the middle value when a data set is ordered from smallest to largest. If there is an even number of values, the median is the average of the two central numbers. Because it only cares about position, the median is not influenced by outliers, making it useful for house prices or salaries.
中位数是将一组数据集从小到大排序后，位于中间的那个值。如果数据的个数是偶数，则中位数是中间两个数值的平均数。由于它只关心位置，中位数不受异常值的影响，因此对于房价或工资这类数据很有用。
- Odd count: The median of 2, 5, 9 is 5.
- 奇数个：2、5、9 的中位数是 5。
- Even count: The median of 2, 4, 8, 10 is (4 + 8) ÷ 2 = 6.
- 偶数个：2、4、8、10 的中位数是 (4 + 8) ÷ 2 = 6。
- Memory tip: A ‘median’ strip runs down the middle of a road. 助记技巧：道路中间那条隔离带就叫“median”。
4. Mode | 众数
The mode is the value that appears most often in a data set. A set may have one mode, more than one mode (bimodal or multimodal), or no mode at all if no value repeats. The mode is the only average that can be used with non-numerical qualitative data, such as favourite colours.
众数是数据集中出现次数最多的值。一个数据集可能有一个众数、多个众数（双众数或多众数），或者如果没有重复值，可能没有众数。众数是唯一能用于非数值定性数据的平均数，比如最喜欢的颜色。
- Example: In the list red, blue, blue, green, the mode is blue.
- 示例：在红、蓝、蓝、绿这个列表中，众数是蓝色。
- Bimodal: The set 1, 1, 3, 5, 5 has modes 1 and 5.
- 双众数：数据集 1、1、3、5、5 的众数是 1 和 5。
- Memory tip: ‘Mode’ sounds like ‘most’. 助记技巧：“Mode”的发音听起来像“most（最多）”。
5. Range | 极差
The range is a simple measure of spread telling you how far apart the smallest and largest values are. It is calculated by subtracting the smallest value from the largest value. A small range means the data is consistent; a large range means there is wide variation in the scores.
极差是一种简单的离散程度度量，告诉你最小值和最大值之间的差距有多大。计算方法是用最大值减去最小值。极差小意味着数据较为一致；极差大意味着分数存在很大差异。
- Formula: Range = Largest value − Smallest value.
- 公式：极差 = 最大值 − 最小值。
- Example: For heights 130 cm, 145 cm, and 160 cm, the range is 160 − 130 = 30 cm.
- 示例：对于身高 130 厘米、145 厘米和 160 厘米，极差为 160 − 130 = 30 厘米。
- Memory tip: A mountain ‘range’ stretches from a low start to a high peak. 助记技巧：一条山脉（range）从低起点延伸到高峰。
6. Frequency | 频数
Frequency is simply the number of times a particular value or category occurs. Tally charts help us count frequencies before we forget. The total frequency is the sum of all the individual frequencies, which equals the total number of observations in your sample.
频数简单来说就是某个特定值或类别出现的次数。计数表可以帮助我们在忘记之前统计频数。总频数是所有单个频数的总和，也等于样本中观察结果的总数。
- Tally: |||| represents a frequency of 4. A crossed slanted line through four tallies represents 5.
- 计数：|||| 表示频数为 4。穿过四个竖线的斜线代表 5。
- Example: If 8 students scored 70% on a test, the frequency of the score 70 is 8.
- 示例：如果 8 名学生在考试中得了 70 分，那么分数 70 的频数为 8。
- Memory tip: How ‘frequently’ does something happen? 助记技巧：某事发生的“频繁程度（frequently）”是多少？
7. Primary and Secondary Data | 一手数据与二手数据
Primary data is information you collect yourself for a specific purpose, such as conducting a survey in your school. Secondary data is information someone else has already collected, like statistics from a government website or a textbook table. Primary data is reliable and specific to your question, while secondary data is often faster and cheaper to obtain.
一手数据是你为特定目的自己收集的信息，比如在学校进行一项调查。二手数据是别人已经收集好的信息，比如政府网站上的统计数据或教科书中的表格。一手数据可靠且针对你的问题，而二手数据通常获取起来更快、成本更低。
- Primary example: Measuring the pulse rates of classmates before and after exercise.
- 一手数据示例：测量同学运动前后的脉搏率。
- Secondary example: Using a Wikipedia table of football league attendance figures.
- 二手数据示例：使用维基百科足球联赛上座率数据表。
- Memory tip: Primary = you are the first person collecting it. Secondary = second-hand. 助记技巧：Primary = 你是第一个收集的人。Secondary = 二手的。
8. Discrete vs. Continuous Data | 离散数据与连续数据
Discrete data can only take specific numerical values, usually whole numbers that you count. Continuous data can take any value within a given range because you measure it on a scale. Knowing this difference helps you decide which type of graph to draw; bar charts suit discrete, while histograms suit continuous.
离散数据只能取特定的数值，通常是可以计数的整数。连续数据可以取给定范围内的任何值，因为是在一个连续尺度上测量的。了解这种差异有助于你决定绘制哪种类型的图表；条形图适用于离散数据，而直方图适用于连续数据。
- Discrete: The number of pets in a household (you cannot have 2.5 cats).
- 离散数据：家庭中宠物的数量（你不可能养 2.5 只猫）。
- Continuous: The weight of a parcel (it could be 2.75 kg).
- 连续数据：包裹的重量（可能是 2.75 千克）。
- Memory tip: Discrete data has ‘gaps’ between values; continuous data flows like time. 助记技巧：离散数据在数值间有“间隙”；连续数据像时间一样流动。
9. Hypothesis | 假设
A hypothesis is a testable statement predicting the outcome of an investigation. It is not a wild guess; it should be based on reasoning and phrased clearly so you can collect data to support or refute it. In KS3, you often use ‘I think that… because…’ to structure your hypothesis.
假设是一个可检验的陈述，用于预测调查的结果。它并非胡乱猜想；应当基于推理，并且表述清晰，以便你能够收集数据来支持或反驳它。在 KS3 阶段，你通常用“我认为……因为……”来构建你的假设。
- Good hypothesis: ‘I think that Year 9 pupils have a larger handspan than Year 7 pupils because they are older and more physically developed.’
- 好的假设：“我认为九年级学生的手掌宽度大于七年级学生，因为他们年龄更大，身体发育更成熟。”
- Poor hypothesis: ‘Pupils are different.’ (This is not measurable).
- 差的假设：“学生是不同的。”（这无法测量）。
- Memory tip: A hypothesis is your ‘theory’ you need to ‘test’. 助记技巧：假设（hypothesis）就是你需要去“检验（test）”的“理论（theory）”。
10. Bias | 偏误
Bias is a systematic error that makes a sample unrepresentative of the whole population. A biased question might lead respondents towards a specific answer, or a biased sampling method might ignore a large group of people. Avoiding bias ensures your statistics are fair and trustworthy.
偏误是一种系统性的错误，导致样本不能代表整个总体。带有偏误的问题可能会引导受访者给出特定答案，或者有偏误的抽样方法可能忽略了一大群人。避免偏误可以确保你的统计数据是公正和可信的。
- Biased question: ‘Don’t you agree that homework is a waste of time?’
- 有偏误的问题：“难道你不认为家庭作业是浪费时间吗？”
- Unbiased question: ‘What is your opinion on the value of homework?’
- 无偏误的问题：“你对家庭作业的价值持什么看法？”
- Memory tip: A line that is ‘biased’ leans to one side, just like unfair data. 助记技巧：一条有“偏斜（biased）”的线会倾向一侧，就像不公平的数据一样。
11. Sample and Population | 样本与总体
The population is the entire group of people, items, or events you are interested in studying. Sampling means selecting a smaller, manageable subset from the population. The sample size should be large enough to be reliable: a sample of five friends is unlikely to represent the whole school’s opinion.
总体是你有兴趣研究的整个人群、物品或事件的集合。抽样是指从总体中选取一个较小的、易于管理的子集。样本量应该足够大以保证可靠性：仅凭五个朋友的意见样本不太可能代表整个学校的看法。
- Population: All 800 students in a secondary school.
- 总体：一所中学的全部 800 名学生。
- Sample: 50 students randomly chosen from the school directory.
- 样本：从学校名册中随机选出的 50 名学生。
- Memory tip: Surveying a population is like trying to drink from an ocean; a sample is a sensible cupful. 助记技巧：调查总体就像试图喝干大海；样本则是明智的一杯水。
12. Correlation | 相关性
Correlation describes the relationship between two variables on a scatter graph. Positive correlation means as one variable increases, the other tends to increase. Negative correlation means as one increases, the other tends to decrease. Most importantly, correlation does not imply causation: just because two things happen together does not mean one causes the other.
相关性描述的是散点图上两个变量之间的关系。正相关意味着一个变量增加时，另一个也傾向于增加。负相关意味着一个变量增加时，另一个傾向于减少。最重要的是，相关性并不意味着因果关系：两个事件同时发生并不意味着一个引起了另一个。
- Positive: Shoe size and height tend to show a positive correlation.
- 正相关：鞋码和身高通常呈正相关。
- Negative: The number of layers worn and the outdoor temperature show a negative correlation.
- 负相关：穿衣服的层数与室外温度呈负相关。
- Memory tip: Look at the slope of the pattern, but remember ‘correlation is NOT causation’. 助记技巧：观察模式的斜率，但记住“相关性不等于因果关系”。
Published by TutorHao | Statistics Revision Series | aleveler.com
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