Year 7 Cambridge Statistics: Key Terms Speed Memorisation Guide | Year 7 剑桥统计：词汇术语速记指南

📚 Year 7 Cambridge Statistics: Key Terms Speed Memorisation Guide | Year 7 剑桥统计：词汇术语速记指南

Welcome to your quick memorisation guide for Year 7 Cambridge Statistics! Understanding the language of statistics is the first step to mastering data handling. This article breaks down every essential term you will encounter, gives you visual memory hooks, and builds your confidence before you sit any test. Read each term’s explanation, lock in the memory shortcut, and you will soon speak ‘data’ fluently.

欢迎使用这份 Year 7 剑桥统计词汇速记指南！理解统计语言是掌握数据处理的第一步。本文拆解了你会遇到的每一个核心术语，提供形象记忆窍门，帮助你在考试前建立信心。先读英文解释，再锁定中文记忆方法，你很快就能流利地“说数据”了。

1. What Is Statistics? | 什么是统计学？

Statistics is the branch of mathematics that deals with collecting, organising, displaying, and interpreting data. In Year 7, you use statistics to answer questions like “What is the most popular snack in my class?” or “How much do my friends’ pets weigh on average?” The subject turns messy numbers into clear stories.

统计学是数学的一个分支，负责收集、整理、展示和解读数据。在 Year 7 的学习中，你会用统计学回答“班上最受欢迎的零食是什么？”或“朋友们的宠物平均体重是多少？”这样的问题。这门学科能把杂乱的数据变成清晰的故事。

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2. Types of Data: Qualitative and Quantitative | 数据类型：定性与定量

Data can be qualitative (descriptive, non-numerical) or quantitative (numerical). Qualitative data describes qualities, such as eye colour, favourite subject, or brand of phone. Quantitative data records quantities that can be counted or measured, like height, number of siblings, or test scores.

数据可以是定性数据（描述性、非数值型）或定量数据（数值型）。定性数据描述属性，例如眼睛颜色、最喜爱的科目或手机品牌。定量数据记录可以计数或测量的数量，如身高、兄弟姐妹个数或测验分数。

Memory tip: ‘Qualitative’ has ‘quality’ inside it – focus on descriptions. ‘Quantitative’ has ‘quantity’ – think of numbers.

记忆技巧： ‘Qualitative’ 里面藏着 ‘quality’，联想描述性特征。‘Quantitative’ 包含 ‘quantity’，想到数字。

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3. Discrete vs Continuous Data | 离散型与连续型数据

Quantitative data splits further into discrete and continuous. Discrete data can only take specific, separate values – usually whole numbers, like the number of students in a room (27, 28, 29). Continuous data can take any value within a range and is often measured, such as length (1.75 m) or time (3.2 seconds).

定量数据可进一步分为离散型和连续型。离散数据只能取特定的、分离的值——通常是整数，比如房间里学生的人数（27, 28, 29）。连续数据可以取一个范围内的任何值，通常是测量得到的，例如长度（1.75 米）或时间（3.2 秒）。

Memory tip: ‘Discrete’ sounds like ‘discreet spots’ – something you can count individually. ‘Continuous’ flows like a liquid stream, so it can take any measurement.

记忆技巧： ‘Discrete’ 类似“离散的斑点”，可以一个一个数出来。‘Continuous’ 像连续流淌的溪水，可以取任何测量值。

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4. Primary and Secondary Data | 一手数据与二手数据

Primary data is information YOU collect yourself for a specific purpose – for example, doing a survey in your school. Secondary data is information gathered by someone else that you then use, such as weather records from a website or statistics from a textbook table.

一手数据是你自己为特定目的而收集的信息，例如在学校开展调查。二手数据是由别人收集、你随后使用的信息，比如来自网站的天气记录或教科书表格里的统计数据。

Memory tip: Primary = personal, you are the first. Secondary = second-hand, someone else did it first.

记忆技巧： Primary 就像第一手，你自己是第一人。Secondary 是二手，别人先做过。

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5. Population and Sample | 总体与样本

A population is the entire group you want to find out about – all Year 7 students in the UK. A sample is a smaller, manageable selection taken from the population, such as 50 Year 7 pupils from one school. Researchers use samples to make predictions because asking everyone is often impossible.

总体是你想要了解的整个群体，比如全英国所有 Year 7 学生。样本是从总体中选出的较小的、便于处理的一部分，例如来自一所学校的 50 名 Year 7 学生。研究者用样本做预测，因为询问所有人往往不可能完成。

Memory tip: Think of ‘population’ as the whole pizza, and ‘sample’ as the slice you taste before judging the whole pizza.

记忆技巧： 把“总体”想象成整张披萨，“样本”则是你品尝的一角，用来推断整张披萨的味道。

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6. Frequency and Frequency Table | 频数与频数表

Frequency is simply how many times something occurs. A frequency table organises data into categories with a tally column and a frequency column. For example, if six pupils have brown eyes, the frequency for ‘brown’ is 6.

频数就是指某事物出现的次数。频数表将数据按类别分组，包含画正字的计数栏和频数栏。例如，如果有六名学生有棕色眼睛，那么“棕色”的频数就是 6。

Memory tip: ‘Frequent’ means happening often – frequency counts how ‘frequent’ a value is.

记忆技巧： ‘Frequent’ 表示经常发生，频数就是计算一个值有多“频繁”。

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7. Mean (Average) | 平均数（均值）

The mean is often called the average. To find the mean, add up all the values and then divide by the number of values. It represents a fair share of the total if everyone got the same amount.

平均数常被称为均值。求平均数时，先把所有数值加起来，再除以数值的个数。它表示如果把总量平均分配，每人得到的公平份额。

Mean = (Sum of all values) ÷ (Number of values)

平均数 = 数值总和 ÷ 数值个数

Memory tip: Mean is the “feel fair” number – share the total equally. Visualise pouring water into same-sized cups.

记忆技巧： 平均数是“公平分配”的数字，想象把水倒进大小相同的杯子里。

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8. Median (Middle Value) | 中位数（中间值）

The median is the middle value when your data is ordered from smallest to largest. If there is an even number of values, the median is the mean of the two middle numbers. It is useful when data has extremely high or low outliers.

中位数是将数据从小到大排序后处于中间位置的值。如果数据个数为偶数，中位数就是中间两个数的平均数。当数据存在极大或极小的异常值时，中位数非常有用。

To find the median of 3, 5, 8, 9, 12: the middle is 8. For 3, 5, 8, 11: median = (5+8) ÷ 2 = 6.5.

找 3, 5, 8, 9, 12 的中位数：中间数是 8。对 3, 5, 8, 11：中位数 = (5+8) ÷ 2 = 6.5。

Memory tip: Median sounds like ‘medium’ – the middle size. Think of the central reservation (median strip) on a motorway.

记忆技巧： Median 发音接近 “medium”（中等），联想高速公路中间的分隔带（median strip），正好在正中间。

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9. Mode (Most Frequent) | 众数（最频繁值）

The mode is the value that appears most often in a data set. A set of data can have one mode (unimodal), more than one mode (bimodal or multimodal), or no mode at all if every value occurs only once.

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（单峰）、多个众数（双峰或多峰），或者没有众数（若每个值都只出现一次）。

Memory tip: Mode and ‘most’ both start with ‘mo’. The mode is the most popular value.

记忆技巧： Mode 和 “most” 都以 “mo” 开头。众数就是最“流行”的值。

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10. Range (Spread) | 极差（范围）

The range measures how spread out the data is. It is calculated by subtracting the smallest value from the largest value. A smaller range means the data is more clustered together; a larger range indicates wider spread.

极差衡量数据的离散程度。它的计算方法是最大值减去最小值。极差越小说明数据越集中；极差越大意味着数据分布越广。

Range = Largest value − Smallest value

极差 = 最大值 − 最小值

Memory tip: Imagine two sheep on a field. The range is the distance between the far-left sheep and the far-right sheep. ‘Range’ is how far your numbers roam.

记忆技巧： 想象田野里的两只羊，极差就是最左边羊和最右边羊之间的距离。“Range” 就是数字游走的范围。

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11. Bar Charts and Pictograms | 条形图与象形图

A bar chart uses rectangular bars of equal width, with the height or length representing frequency. Gaps between bars show that the data is categorical. A pictogram uses small pictures or symbols to represent data; each picture stands for a certain number of items, and a key must always be given.

条形图使用等宽的长方形条，条的高度或长度代表频数。条与条之间的空隙表明数据是分类数据。象形图使用小图标或符号代表数据；每个图画代表一定数量的物品，并且必须附上图例说明。

Memory tip for bar chart: Bars like chocolate bars – each bar stands alone. For pictogram: Picture + -gram (like telegram) sends a visual message. Remember to check the key: half a picture equals half the value.

条形图记忆技巧： Bars 像巧克力棒，每根竖立独立。 象形图记忆技巧： Picture + -gram 发送图画信息。切记核对图例：半个图画等于一半的数值。

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12. Pie Charts and Sector Angles | 饼图与扇形角度

A pie chart displays data as slices of a circle. The whole circle (360°) represents the total. To find the angle for each category, use the formula: (category frequency ÷ total frequency) × 360°. The slice size shows proportion at a glance, making pie charts excellent for comparing parts of a whole.

饼图将数据表示为圆形中的扇形切片。整个圆（360°）代表总量。要计算每个类别对应的角度，使用公式：(类别频数 ÷ 总频数) × 360°。扇形大小直观显示比例，因此饼图非常适合比较整体中的各个部分。

Sector angle = (Frequency of category ÷ Total frequency) × 360°

扇形角度 = (类别频数 ÷ 总频数) × 360°

Memory tip: Picture a real pie cut into slices. The bigger the share, the wider the slice angle. Remember that 360° is the ‘whole pie’.

记忆技巧： 想象一个真正的派，切成几块。份额越大，扇形角度越宽。记住 360° 是一整个“派”。

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Summary Table of Key Terms | 核心术语速查表

The table below gives you an at-a-glance revision card for your Year 7 statistics vocabulary. Use it to test yourself: cover the meaning column and try to recall the definition in English and Chinese.

下面的表格为你提供了 Year 7 统计词汇的速查卡片。用它来测试自己：遮住含义一栏，尝试用中英文回忆定义。

Term (术语)	Meaning (含义)
Qualitative data	Descriptive, non-numerical information (定性数据：描述性信息)
Quantitative data	Numerical information (定量数据：数值型信息)
Discrete data	Countable, separate values (离散数据：可数的独立值)
Continuous data	Measurable, can take any value in a range (连续数据：可测量，可取范围内任意值)
Primary data	Data you collect firsthand (一手数据：自己收集的数据)
Secondary data	Data collected by someone else (二手数据：别人收集的数据)
Population	The whole group of interest (总体：感兴趣的整个群体)
Sample	A subset of the population (样本：总体的一个子集)
Frequency	How often a value occurs (频数：某值出现的次数)
Mean	Sum of values ÷ number of values (平均数：总和÷个数)
Median	Middle value when ordered (中位数：排序后的中间值)
Mode	Most frequent value (众数：出现最频繁的值)
Range	Largest − smallest value (极差：最大值−最小值)
Bar chart	Rectangular bars with gaps between (条形图：有空隙的长方形条)
Pictogram	Uses pictures and a key (象形图：使用图画和图例)
Pie chart	Circular chart with proportional slices (饼图：按比例分割的圆形图)

Published by TutorHao | Statistics Revision Series | aleveler.com

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