📚 Year 7 Cambridge Statistics: Quick Vocabulary Memorization Guide | Year 7 Cambridge 统计：词汇术语速记指南
Welcome to your quick guide for mastering statistics vocabulary in Year 7 Cambridge Mathematics. Understanding key terms is the first step to success in data handling and probability. This article provides simple definitions, memory tricks, and examples to help you remember each term effortlessly.
欢迎来到 Year 7 剑桥数学统计词汇速记指南。掌握关键术语是学好数据处理和概率的第一步。本文提供简明定义、记忆技巧和示例，帮助你轻松记住每个术语。
1. Collecting Data | 数据收集
Data is a collection of facts, numbers, or measurements. We gather data by carrying out a survey or using a questionnaire. When you collect information yourself for a specific purpose, it is called primary data. Data that has been collected by someone else is secondary data.
数据是事实、数字或测量值的集合。我们通过进行调查或使用问卷来收集数据。当你为特定目的自己收集信息时，称为一手数据。由别人收集好的数据则是二手数据。
Memory trick: Think of ‘primary’ as the first data you produce; ‘secondary’ means second‑hand data.
记忆技巧：把 ‘primary’ 想象成你亲手产生的第一手数据；’secondary’ 就是别人用过的二手数据。
2. Tally Marks and Frequency Tables | 划记与频数表
Tally marks are short vertical lines used to count items one by one; every fifth line is drawn diagonally across the previous four to make groups of five easy to read. The word frequency tells you how many times something occurs. A frequency table organises data by listing categories alongside their tally marks and frequencies.
划记是用来逐一计数的短竖线；每数到第五个时，用一条斜线划过前四条线，方便按五个一组快速读取。频数一词指的是某事物出现的次数。频数表将各类别与其划记和频数列在一起，把数据整理得清清楚楚。
Memory trick: ‘Tally’ sounds a bit like ‘count-alley’ – a small alley where you count. Frequency = how frequent something is.
记忆技巧：’Tally’ 的发音有点像 “count-alley”（计数小巷）；频率就是看某个事件多频繁出现。
3. Bar Charts and Pictograms | 条形图与象形图
A bar chart uses bars of equal width to represent frequencies. The height of each bar shows the frequency of that category. Bars can be drawn vertically or horizontally, and there are usually gaps between them. A pictogram uses small pictures or symbols to represent data; each symbol stands for a certain number of items. You must always include a key to explain what one symbol represents.
条形图用宽度相等的长条来表示频数。每个长条的高度代表该类别出现的次数。长条可以竖着画，也可以横着画，而且长条之间通常留有间隙。象形图使用小图片或符号来表示数据；每个符号代表一定数量的物品。一定要附带图例，说明每个符号代表多少。
Memory trick: Bar chart – imagine a bar of chocolate divided into equal pieces. Pictogram = picture + diagram – a diagram made of pictures.
记忆技巧：Bar chart — 想象一块巧克力掰成同样大小的几块。Pictogram 就是 picture + diagram（图片构成的图）。
4. Pie Charts | 饼图
A pie chart is a circle divided into sectors, just like slices of a pie. Each sector represents a category, and its central angle shows the proportion of the data it represents. The total of all angles is 360°. You can calculate the angle for a sector using the formula Angle = (Frequency of category ÷ Total frequency) × 360°.
饼图是一个被划分成扇区的圆，就像切好的馅饼。每个扇区代表一个类别，扇区的圆心角大小表示该类别所占的比例。所有扇区的角度之和是 360°。你可以用公式：扇区角度 = (该类别的频数 ÷ 总频数) × 360° 来计算。
Angle = (Frequency of category ÷ Total frequency) × 360°
扇区角度 = (类别的频数 ÷ 总频数) × 360°
Memory trick: A pie chart is like a real pie – the bigger the slice you take, the more data you are representing!
记忆技巧：饼图就像真正的馅饼 — 你切的那块越大，代表的数据就越多！
5. Line Graphs | 折线图
A line graph is used to display how data changes over a period of time. Individual data points are plotted and then connected by straight lines. Line graphs are particularly useful for showing trends in continuous data, such as temperature throughout a day or height over several years.
折线图用来展示数据在一段时间内是如何变化的。先把各个数据点标出来，再用直线把它们依次连接起来。折线图特别适合显示连续数据的趋势，比如一天中的气温变化或几年的身高增长。
Memory trick: A line graph uses a ‘line’ to link points over time – think of following a line on a journey.
记忆技巧：折线图用一条 ‘线’ 把不同时间点连接起来 — 就像沿着路线前进。
6. Mean | 平均数
The mean is commonly called the average. To find the mean, add up all the data values and then divide by the number of values. The mean gives you an idea of a ‘typical’ value if the total were shared equally.
平均数通常就称为平均值。要计算平均数，先把所有数据值加起来，然后除以数据的个数。平均数告诉你如果把总数平均分配，每个值大概是多少。
Mean = Sum of all values ÷ Number of values
平均数 = 所有数值的总和 ÷ 数值的个数
Example: For the numbers 3, 5 and 10, the sum is 18, there are 3 values, so the mean = 18 ÷ 3 = 6.
示例：对于数字 3、5 和 10，总和是 18，有 3 个数，平均数 = 18 ÷ 3 = 6。
Memory trick: The mean is ‘mean’ because it makes everyone share equally – you work out what each person would get if the total were split fairly.
记忆技巧：Mean 有点 ‘小气’，因为它要求大家平均分配 — 你想像把总数平均分给每个人，每人得到的就是平均数。
7. Median and Mode | 中位数与众数
The median is the middle value when the data is arranged in order from smallest to largest. If there is an even number of values, the median is the mean of the two middle numbers. The mode is the value that appears most often. A data set may have one mode, more than one mode, or no mode at all.
中位数就是把数据从小到大排序后，处于正中间的那个值。如果数据个数是偶数，中位数就是中间两个数的平均数。众数是出现次数最多的那个值。一组数据可能有一个众数、多个众数，或者根本没有众数。
Median (odd number of values) = the middle value
中位数（奇数个数据） = 中间那个数
Median (even number) = (middle value 1 + middle value 2) ÷ 2
中位数（偶数个数据） = (中间值1 + 中间值2) ÷ 2
Example: Data 2, 3, 3, 7, 9. Median = 3 (the third value). Mode = 3 (appears twice).
示例：数据 2, 3, 3, 7, 9。中位数 = 3（第三个值）。众数 = 3（出现了两次）。
Memory trick: Median and ‘middle’ both start with M. Mode and ‘most’ both start with M.
记忆技巧：Median（中位数）和 ‘middle’（中间）都以 M 开头。Mode（众数）和 ‘most’（最多）都以 M 开头。
8. Range | 极差
The range measures how spread out the data is. It is simply the difference between the largest value and the smallest value. A small range means the data are quite close together; a large range means they are more spread out.
极差衡量的是数据分布的分散程度。它就是最大值和最小值之间的差。极差小说明数据比较集中；极差大说明数据比较分散。
Range = Maximum value – Minimum value
极差 = 最大值 – 最小值
Example: For the data set 4, 8, 15, 22, the range = 22 – 4 = 18.
示例：对于数据集 4, 8, 15, 22，极差 = 22 – 4 = 18。
Memory trick: The range tells you the ‘reach’ of your data – how far it stretches from the smallest to the largest.
记忆技巧：极差就像数据的’跨度’ — 从最小到最大拉得有多远。
9. Introduction to Probability | 概率入门
Probability is a measure of how likely an event is to happen. It always has a value between 0 and 1. A probability of 0 means the event is impossible, while a probability of 1 means it is certain. Probabilities can be written as fractions, decimals, or percentages.
概率用来衡量一个事件发生的可能性大小，它的值总是在 0 到 1 之间。概率为 0 表示事件不可能发生，概率为 1 表示事件一定发生。概率可以用分数、小数或百分数表示。
Probability of an event = Number of favourable outcomes / Total number of possible outcomes
事件的概率 = 有利结果的数量 / 可能结果的总数
Example: The probability of rolling an even number on a fair six‑sided dice is 3/6, which simplifies to 1/2.
示例：掷一个公平的六面骰子得到偶数的概率是 3/6，化简后为 1/2。
10. Probability Scale and Likelihood Words | 概率尺度与可能性词语
We often describe probability using words placed on a probability scale. ‘Impossible’ has probability 0, ‘unlikely’ is around 1/4, ‘even chance’ is 1/2, ‘likely’ is about 3/4, and ‘certain’ equals 1. These words help you estimate probability without using numbers.
我们经常用放在概率尺度上的词语来描述可能性。’不可能’的概率是 0，’不太可能’大约是 1/4，’等可能’是 1/2，’很可能’大约是 3/4，’一定’等于 1。这些词语帮助你在不用数字的情况下估测概率。
| Word | Probability |
|---|---|
| Impossible | 0 |
| Unlikely | About 1/4 |
| Even chance | 1/2 |
| Likely | About 3/4 |
| Certain | 1 |
Memory trick: Imagine the probability scale as a number line running from 0 to 1; place the words where you feel they belong.
记忆技巧：把概率尺度想象成一条从 0 到 1 的数轴，然后把词语放在你觉得合适的位置上。
11. Sample Space | 样本空间
The sample space is a list of all possible outcomes of an experiment. For a single coin toss, the sample space is {Head, Tail}. For rolling a dice, it is {1, 2, 3, 4, 5, 6}. When two events happen together, you can use a sample space diagram or table to list all combinations.
样本空间是某项试验所有可能结果的清单。抛一枚硬币的样本空间是 {正面, 反面}。掷一个骰子的样本空间是 {1, 2, 3, 4, 5, 6}。当两个事件同时发生时，你可以用样本空间图或表格列出所有组合。
Example: When you flip two coins, the sample space is {HH, HT, TH, TT} where H stands for Head and T for Tail.
示例：当你同时抛两枚硬币时，样本空间是 {HH, HT, TH, TT}，其中 H 代表正面，T 代表反面。
Memory trick: Think of the sample space as a ‘sample box’ containing every single outcome that could possibly happen.
记忆技巧：把样本空间想成一个 ‘样品盒’，里面装着所有可能发生的结果。
12. Experimental vs Theoretical Probability | 实验概率与理论概率
Theoretical probability is what you expect to happen based on equally likely outcomes. It is calculated using the formula we saw earlier. Experimental probability (also called relative frequency) is based on actually performing the experiment or trial. You find it by dividing the number of times the event occurs by the total number of trials.
理论概率是根据等可能结果预先计算出的期望概率，用我们前面见过的公式计算。实验概率（也称相对频率）则是通过实际进行试验或实验得出的。它由事件发生的次数除以总试验次数得到。
Theoretical probability = Favourable outcomes / Total outcomes
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