📚 Cambridge Year 9 Statistics: Quick Glossary Guide | 剑桥Year 9统计：词汇术语速记指南
Mastering Statistics begins with understanding its language. This guide breaks down the essential terms you will encounter in the Cambridge Year 9 Statistics syllabus, pairing clear English definitions with Chinese explanations and memory tips. Use it to build confidence before tackling data handling, charts, averages, and probability.
掌握统计学首先要理解它的语言。本指南将拆解剑桥Year 9统计大纲中的核心术语，提供清晰的英文定义与中文解释，并附上记忆技巧。在处理数据、图表、平均数和概率之前，用它来建立信心。
1. Core Concepts | 核心概念
Population: The entire set of individuals or items that we are interested in studying. For example, all Year 9 students in your school.
总体： 我们感兴趣研究的全部个体或对象的集合。例如，你们学校所有的Year 9学生。
Sample: A smaller, manageable subset of a population selected to represent it. A survey of 30 randomly chosen Year 9 students is a sample.
样本： 从总体中选出的、能代表总体的一个较小的、可处理的子集。随机选择30名Year 9学生进行的调查就是一个样本。
Variable: A characteristic or attribute that can vary among individuals in a population or sample. Examples include height, favourite colour, or test score.
变量： 在总体或样本中，不同个体可能有所不同的特征或属性。比如身高、最喜欢的颜色或考试分数。
Data: The actual values or observations collected about a variable. Data is plural; a single piece of information is a datum.
数据： 关于变量收集到的实际值或观察结果。Data是复数形式；单条信息是datum。Tip：想象一整个数据集是复数。
Memory trick: Population is the whole pie; sample is just a slice. Variable is what changes.
记忆窍门：总体是整个馅饼；样本只是其中一块。变量是会变化的东西。
2. Types of Data | 数据类型
Qualitative data: Non-numerical data that describes qualities or categories. Also called categorical data. Examples: eye colour (blue, brown), type of transport (bus, walk).
定性数据： 描述性质或类别的非数值数据，也称分类数据。例如：眼睛颜色（蓝色、棕色）、交通方式（公交、步行）。Tip：定性 (Qualitative) 与“质量” (Quality) 相关。
Quantitative data: Numerical data that can be counted or measured. Examples: number of siblings, temperature in °C.
定量数据： 可计数或测量的数值型数据。例如：兄弟姐妹的数量、摄氏温度。Tip：定量 (Quantitative) 和“数量” (Quantity) 同源。
Discrete data: Quantitative data that can only take specific, separate values (often whole numbers). You cannot have 2.5 siblings in a family. Counted data is usually discrete.
离散数据： 只能取特定、分离的值（通常为整数）的定量数据。一个家庭不可能有2.5个孩子。计数数据通常是离散的。Tip：离散像独立的台阶。
Continuous data: Quantitative data that can take any value within a given range. Height can be 162.3 cm, weight can be 50.7 kg. Measured data is usually continuous.
连续数据： 可在给定范围内取任意值的定量数据。身高可以是162.3厘米，体重可以是50.7千克。测量数据通常是连续的。Tip：连续像平滑的斜坡。
3. Collecting Data | 收集数据
Primary data: Data that you collect yourself for a specific purpose. Conducting your own experiment or designing a questionnaire gathers primary data.
原始数据（一手数据）： 你为特定目的亲自收集的数据。自己做实验或设计问卷收集到的就是原始数据。
Secondary data: Data that someone else has already collected, which you use for your analysis. Examples: data from the internet, newspapers, or a published database.
二手数据： 别人已经收集好的、你拿来分析用的数据。例如：来自网络、报纸或公开数据库的数据。
Survey: A method of gathering information from a sample by asking questions. A survey can be a questionnaire or an interview.
调查： 通过提问从样本中收集信息的方法。调查可以是问卷或访谈。
Questionnaire: A set of written questions designed to collect data from respondents. Questions should be clear and unbiased.
问卷： 一套为向受访者收集数据而设计的书面问题。问题应当清晰且不带有偏见。
4. Organising Data | 整理数据
Frequency: The number of times a particular value or category occurs in a data set. If 12 students chose ‘blue’, the frequency of blue is 12.
频数： 某个特定值或类别在数据集中出现的次数。如果有12名学生选择了“蓝色”，那么蓝色的频数就是12。
Tally chart: A table using tally marks (usually in groups of five) to record frequencies as data is collected. Each diagonal line across four vertical marks completes a group of five.
频数划记表： 使用划记符号（通常5个一组）在收集数据时记录频数的表格。四条竖线加一条对角线凑成一组“正”字（英文为五划一组）。
Frequency table: A table that summarises a data set by showing values or categories alongside their frequencies. It organises data for easy analysis.
频数分布表： 通过列出数值或类别及其频数来总结数据集的表格。它将数据组织起来以便分析。
Grouped frequency table: Used for continuous data or data with many different values; data is sorted into class intervals. E.g., heights 140–149 cm, 150–159 cm.
分组频数表： 用于连续数据或数值众多的情况；数据被归入几个组距。例如身高140–149厘米，150–159厘米。
5. Data Representation: Charts | 数据图示：图表
Bar chart: A diagram using rectangular bars of equal width with heights proportional to frequencies. Bars have gaps between them to show separate categories.
条形图： 用等宽矩形条、高度与频数成正比的图。条与条之间有间隔，表示独立的类别。
Pictogram: A chart using identical symbols or pictures to represent a certain number of items. A key explains how many items one symbol stands for.
象形图： 用相同的符号或图片代表一定数量项目的图表。图例会说明每个符号代表的数量。
Pie chart: A circular chart divided into sectors; each sector’s angle is proportional to the frequency of the category it represents. The whole circle represents the total data set.
饼图： 分为若干个扇形的圆形图；每个扇形的角度与该类别的频数成比例。整个圆代表全部数据。
Line graph: Used to display continuous data over time. Points are plotted and joined by straight lines, often showing trends or changes.
折线图： 用来展示随时间变化的连续数据。描出数据点并用直线连接，常用来显示趋势或变化。
Stem-and-leaf diagram: A way of organising numerical data while retaining the original values. The ‘stem’ represents the larger place value(s) and the ‘leaf’ shows the last digit.
茎叶图： 一种在保留原始数值的同时组织数值数据的方法。“茎”代表较大的数位，“叶”表示最后一位数字。例如42的茎为4，叶为2。
6. Measures of Central Tendency | 集中趋势的度量
Mean: The average of a set of numbers, found by dividing the sum of all values by the total number of values. Often simply called the average.
平均数（均值）： 一组数的平均值，通过所有数值之和除以数值总个数求得。常简称为平均。
Median: The middle value when data is arranged in order. For an even number of values, the median is the mean of the two middle numbers.
中位数： 数据排序后位于正中间的值。如果数据个数为偶数，中位数是中间两个数的平均值。Tip：Median像道路的“中”央分隔带。
Mode: The value or category that appears most frequently. A data set can have one mode, more than one mode (bimodal/multimodal), or no mode at all.
众数： 出现频数最高的数值或类别。一组数据可以有一个众数、多个众数，或者没有众数。Tip：Mode和“最”流行（most）谐音。
Range: A measure of spread; range = highest value − lowest value. It tells you how spread out the data is.
全距（极差）： 一种离散程度的度量；全距 = 最大值 − 最小值。它告诉你数据的分散程度。
7. Measures of Spread | 离散程度的度量
Lower quartile (Q1): The median of the lower half of the data set (below the overall median). About 25% of data values lie below Q1.
下四分位数 (Q1)： 数据下半部分（低于总中位数）的中位数。大约25%的数据值低于Q1。
Upper quartile (Q3): The median of the upper half of the data set (above the overall median). About 75% of data values lie below Q3.
上四分位数 (Q3)： 数据上半部分的中位数。大约75%的数据值低于Q3。Tip：Q1和Q3像一本书的前四分之一和后四分之一。
Interquartile range (IQR): IQR = Q3 − Q1. It measures the spread of the middle 50% of the data, ignoring extreme values.
四分位距： IQR = Q3 − Q1。它衡量中间50%数据的分散程度，不受极端值影响。
Outlier: An extreme value that lies well outside the overall pattern of the data. Often defined as a value more than 1.5 × IQR below Q1 or above Q3.
异常值： 严重偏离数据整体模式的极端值。通常定义为低于 Q1 − 1.5×IQR 或高于 Q3 + 1.5×IQR 的数值。
8. Scatter Graphs & Correlation | 散点图与相关性
Scatter graph: A graph with two numerical axes where each pair of values is plotted as a point. It helps investigate the relationship between two continuous variables.
散点图： 具有两个数值轴的图表，每对数值以一个点表示。它用来探究两个连续变量之间的关系。
Positive correlation: As one variable increases, the other also tends to increase. Points on the scatter graph slope upwards roughly from left to right.
正相关： 一个变量增大，另一个变量也倾向增大。散点图上各点大致从左到右向上倾斜。
Negative correlation: As one variable increases, the other tends to decrease. Points slope downwards roughly from left to right.
负相关： 一个变量增大，另一个变量倾向减小。点大致从左到右向下倾斜。
No correlation: There is no clear pattern; the points appear randomly scattered. The variables are not related.
零相关： 没有明显模式；点看起来随机散布。变量之间不相关。
Line of best fit: A straight line drawn through the middle of the points on a scatter graph to show the trend. It should have roughly equal numbers of points above and below it.
最佳拟合线： 在散点图中间穿过各点的直线，用来显示趋势。直线上方和下方的点数应大致相等。
9. Basic Probability | 概率基础
Probability: A measure of how likely an event is to happen, expressed as a number between 0 (impossible) and 1 (certain). Can be written as a fraction, decimal, or percentage.
概率： 衡量事件发生可能性的指标，用0（不可能）到1（一定）之间的数字表示。可以写成分数、小数或百分数。
Outcome: A single possible result of an experiment or trial. When rolling a fair die, the outcomes are 1, 2, 3, 4, 5, 6.
结果： 试验或尝试的一个可能结果。掷一个均匀骰子时，结果是1、2、3、4、5、6。
Event: A set of one or more outcomes that we are interested in. ‘Rolling an even number’ is an event containing outcomes 2, 4, 6.
事件： 我们所关心的一个或多个结果的集合。“掷出偶数”是一个事件，包含结果2、4、6。
Sample space: The complete list of all possible outcomes of an experiment. Usually represented as a list, table, or tree diagram.
样本空间： 试验所有可能结果的完整列表。常用列表、表格或树状图表示。
Theoretical probability: Probability based on reasoning without performing the experiment. P(head) = ½ when flipping a fair coin.
理论概率： 不进行试验，通过推理得出的概率。抛一枚均匀硬币，P(正面)=½。
Experimental probability: Probability based on actual trials or experiments. If you flip a coin 50 times and get 28 heads, experimental probability = 28/50.
实验概率： 基于实际试验或实验的概率。如果你抛硬币50次得到28次正面，实验概率=28/50。
Expected frequency: The number of times we predict an event will occur in repeated trials. Expected frequency = theoretical probability × number of trials.
期望频数： 在重复试验中，我们预测事件会发生的次数。期望频数 = 理论概率 × 试验次数。
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