📚 Y8 SQA Statistics: Vocabulary Quick-Memory Guide | Year 8 SQA 统计：词汇术语速记指南
Mastering statistics starts with understanding the language. In Year 8 SQA Statistics, you will meet a whole new set of words that describe data, charts, averages, and chance. This guide is designed to help you learn each term quickly and remember it for good. Each key idea appears in English first, followed by its Chinese translation, so you can build your bilingual confidence while revising for tests and classroom checks.
掌握统计学的第一步是理解它的语言。在 SQA 八年级统计课程中，你会遇到一整套全新的词汇，用来描述数据、图表、平均数和概率。本指南旨在帮助你快速学会每个术语，并长久地记住它。每一个关键概念都先给出英文解释，再附上中文翻译，让你在备考和课堂测验的过程中，既能巩固知识，也能建立双语自信心。
1. Data and Types of Data | 数据与数据类型
Data is any collection of facts, numbers, or measurements that we can analyse. In statistics, we categorise data into two main types: discrete data and continuous data. Discrete data can only take specific values, usually whole numbers, such as the number of books in a bag or goals scored in a match – you count discrete data. Continuous data can take any value within a range and is measured, like height, mass, or time. A quick memory trick is to link ‘Discrete = Count’ and ‘Continuous = Measure’, because you count discrete items but measure continuous quantities with tools like rulers or stopwatches.
数据是我们可以分析的任何事实、数字或测量结果的集合。在统计学中，我们将数据分为两个主要类型：离散数据和连续数据。离散数据只能取特定的值，通常是整数，比如书包里的书本数量或一场比赛的进球数——离散数据是数出来的。连续数据可以在一个范围内取任意值，并且是测量得到的，比如身高、质量或时间。一个快速记忆的小窍门是把“Discrete（离散）→ Count（计数）”，“Continuous（连续）→ Measure（测量）”联系起来，因为离散的物体是一个个数的，而连续的量是用尺子或秒表等工具测量的。
You might also hear about primary data and secondary data. Primary data is information you collect yourself through an experiment or survey. Secondary data is information gathered by someone else, like data from a website or a newspaper. Imagine you are the ‘primary’ detective collecting clues firsthand – that helps you remember primary data is your own work.
你可能还会听到一手数据和二手数据。一手数据是你自己通过实验或调查收集的信息。二手数据是别人收集的信息，比如来自网站或报纸的数据。想象你自己是“第一”侦探亲自收集线索，这能帮你记住一手数据是你自己的成果。
2. Mean, Median, Mode | 平均数、中位数、众数
The three ‘M’s are the most common averages. The mean is what most people call the average. To calculate it, add up all the values and divide by how many values there are. For the numbers 4, 8, 6, the mean is (4+8+6) ÷ 3 = 18 ÷ 3 = 6. Think of ‘mean’ as the ‘fair share’ – if you share the total equally among everyone, each gets the mean.
三个“M”是最常见的平均数。平均数就是大多数人所说的平均值。要计算它，先把所有数值加起来，再除以数值的个数。对于数字 4、8、6，平均数是 (4+8+6) ÷ 3 = 18 ÷ 3 = 6。可以把平均数想象成“平均分配”——如果你把总数平均分给每个人，每人得到的就是平均数。
The median is the middle value when your data is sorted from smallest to largest. If you have 2, 5, 9, 12, 15, the median is 9. If there are two middle numbers, you find the mean of those two. A quick memory hack: ‘Median’ sounds like ‘medium’ – it sits right in the middle, not too big, not too small.
中位数是数据从小到大排序后中间的那个值。比如你有 2、5、9、12、15，中位数就是 9。如果有两个中间的数，就取这两个数的平均数。一个速记方法：“Median”听起来像“medium”（中等）——它正好坐在中间，不大也不小。
The mode is the value that appears most often. In the set 3, 7, 7, 4, 9, 7, the mode is 7 because it occurs three times. Some sets have more than one mode, and some have no mode at all. Remember ‘mode = most’ – the value that appears in the ‘most’ numbers of times.
众数是出现次数最多的数值。在集合 3、7、7、4、9、7 中，众数是 7，因为它出现了三次。有些数据集有多个众数，有些则没有众数。记住“mode = most”——出现次数“最多”的数值。
3. Range and Extremes | 极差与极值
The range tells you how spread out the data is. It is the difference between the largest value and the smallest value. For the numbers 3, 11, 7, 5, 9, the largest is 11 and the smallest is 3, so the range = 11 – 3 = 8. The range is a single number, not ‘from 3 to 11’. A large range means the data is very spread out; a small range means the data is clustered closely together.
极差告诉你数据的分散程度。它是最大值和最小值的差。对于数字 3、11、7、5、9，最大是 11，最小是 3，所以极差 = 11 – 3 = 8。极差是一个数字，不是“从 3 到 11”。极差大意味着数据非常分散；极差小意味着数据紧密地聚集在一起。
The extremes are simply the highest and lowest values in the set. They are useful for spotting outliers – extreme points that do not fit the pattern of the rest of the data. Think of the range as a quick health check: if the range is huge, your data might be telling different stories at the two ends.
极值就是数据集中的最大值和最小值。它们有助于发现异常值——那些与其余数据模式不符的极端点。把极差看作一种快速健康检查：如果极差很大，你的数据可能在两端讲述着截然不同的故事。
4. Frequency and Tally Charts | 频数与频数表
Frequency is simply how many times a piece of data occurs. When you roll a dice 20 times and get the number 4 six times, the frequency of 4 is 6. To record frequencies neatly, we use a tally chart. A tally mark is a vertical stroke, and every fifth mark is drawn diagonally across the previous four to make a group of five – this makes counting totals much faster.
频数简单来说就是某个数据出现的次数。当你掷骰子 20 次，得到数字 4 一共六次，那么 4 的频数就是 6。为了整齐地记录频数，我们使用频数表。计数符号是垂直的竖线，每第五个符号斜着划过前四条线，构成一组五个——这让统计总数快得多。
A frequency table organises data into rows. One column shows the category or value, and another shows the frequency. Often, you will see a third column for the tally marks themselves. This method turns a messy list of raw data into a clear summary. To remember ‘tally’, picture counting sheep and marking a stroke for each one.
频数表将数据整理成行。一列显示类别或数值，另一列显示频数。通常还会看到第三列用来记录计数符号本身。这种方法把凌乱的原始数据列表变成了清晰的总结。要记住“tally”（计数），可想象数羊时每数一只就划一道记号。
5. Bar Charts and Pictograms | 条形图与象形图
A bar chart uses rectangular bars to represent frequencies. The height of each bar corresponds to the frequency of that category. Bars are drawn with gaps between them to show that the categories are separate. Bar charts are brilliant for comparing discrete data, like favourite flavours of crisps or shoe sizes. Always label your axes and give the chart a title. A memory trick: ‘Bar = compare’ – use it when you want to see which group is tallest at a glance.
条形图使用矩形条来表示频数。每个矩形条的高度对应该类别的频数。条与条之间留有空隙，表示类别是分开的。条形图非常适合比较离散数据，比如最受欢迎的薯片口味或鞋码。记住要标注坐标轴并给图表加上标题。一个记忆小窍门：“Bar = compare（比较）”——当你想一眼看出哪个组最高时就用它。
A pictogram uses pictures or symbols to show data. Each symbol stands for a certain number of items, such as one circle representing 2 pupils. A key must be shown so the reader knows what each symbol means. Pictograms are visually appealing and great for younger audiences. However, they can be tricky when a fraction of a symbol is needed. Always check the key first!
象形图使用图画或符号来展示数据。每个符号代表一定数量的单位，比如一个圆形代表 2 名学生。必须提供图例，让读者知道每个符号的含义。象形图在视觉上很吸引人，非常适合低龄读者。不过，当需要用到半个符号时会比较棘手。一定要先看图例！
6. Pie Charts and Angles | 饼图与角度计算
A pie chart is a circle split into sectors, each representing a category’s frequency. The full circle is 360°, and the angle of each sector is worked out using the formula: Sector angle = (Frequency of category ÷ Total frequency) × 360°. If a category has 10 out of 40 total, its angle is (10 ÷ 40) × 360° = 90°, a quarter of the circle. The pie chart lets us see proportions at a glance – a larger slice means a bigger share of the whole.
饼图是一个被分成扇形的圆，每个扇形代表一个类别的频数。整个圆是 360°，每个扇形的角度通过公式计算：扇形角度 = (类别频数 ÷ 总频数) × 360°。如果一个类别在总数 40 中占了 10，它的角度就是 (10 ÷ 40) × 360° = 90°，即圆形的四分之一。饼图让我们一眼就能看出比例——较大的扇形表示整体中较大的份额。
When interpreting pie charts, you do not need to measure every angle if the chart is well labelled. However, in Year 8, you might be asked to construct a pie chart from a frequency table using a protractor. A handy memory phrase is: ‘Pie is 360, divide and multiply’ – start with the total frequency, then work out each slice’s turn.
在解读饼图时，如果图表标注清晰，就不需要测量每一个角度。不过，在八年级，你可能需要根据频数表用量角器绘制饼图。一个实用的记忆口诀是：“饼图 360，先除后乘”——从总频数开始，然后算出每一片扇形占的角度。
7. Scatter Graphs and Correlation | 散点图与相关性
A scatter graph (or scatter plot) displays paired numerical data – for example, the number of hours studied and the test score. Each point on the graph represents one pair of values. We look for a relationship, called correlation. If the points slope upwards from left to right, it is a positive correlation: as one variable increases, so does the other. If they slope downwards, it is a negative correlation: as one increases, the other decreases. If there is no clear pattern, there is no correlation.
散点图（或散点图）用来展示成对的数值数据——例如，学习的小时数和考试分数。图上的每个点代表一对数值。我们在图表上寻找一种关系，即相关性。如果各点从左到右向上倾斜，就是正相关：当一个变量增加时，另一个也增加。如果点从左到右向下倾斜，就是负相关：一个增加，另一个减少。如果没有清晰的模式，就是没有相关性。
Sometimes we draw a line of best fit, which is a straight line that goes through the middle of the scattered points. This line helps us make predictions. ‘Line of best fit’ doesn’t have to pass through every point – it should balance the points above and below. Think of it as the ‘line of best balance’.
有时我们会画一条最佳拟合线，它是一条穿过散点中心的直线。这条线可以帮助我们进行预测。“最佳拟合线”不必穿过每一个点——它应该平衡线上方和线下方的点。可以把它想象成“最佳平衡线”。
8. Probability Vocabulary | 概率词汇
Probability is the measure of how likely an event is to happen. It can be written as a fraction, decimal, or percentage, and always lies between 0 and 1. A probability of 0 means impossible, 1 means certain, and 0.5 is an even chance. In words, we often use: impossible, unlikely, even chance, likely, certain. Try to match these to numbers: 0, 0.25, 0.5, 0.75, 1.
概率是衡量一个事件发生可能性的量度。它可以用分数、小数或百分数表示，并且总是在 0 到 1 之间。概率为 0 表示不可能，1 表示必然发生，0.5 表示机会均等。用词语描述时，我们常用：不可能、不太可能、机会均等、很可能、必然。试着把这些词语与数字匹配：0、0.25、0.5、0.75、1。
The basic formula for theoretical probability is:
Probability of an event = Number of favourable outcomes ÷ Total number of equally likely outcomes
基本的理论概率公式是：
事件的概率 = 有利结果的数量 ÷ 所有等可能结果的总数
For example, when rolling a fair six-sided dice, the probability of rolling an even number is 3/6 = 1/2 because the favourable outcomes are 2, 4, 6 and there are six possible outcomes in total.
例如，抛掷一个均匀的六面骰子时，掷出偶数的概率是 3/6 = 1/2，因为有利结果是 2、4、6，而总共有六个可能结果。
9. Experiments, Outcomes, and Sample Space | 实验、结果与样本空间
An experiment in probability is a repeatable process that gives a set of possible results, such as tossing a coin, rolling a dice, or spinning a spinner. A single result of an experiment is called an outcome. An event is a set of one or more outcomes that we are interested in, for example ‘rolling a number greater than 4’ includes the outcomes 5 and 6.
概率中的实验是一个可重复的过程，它会产生一组可能的结果，例如抛硬币、掷骰子或转动转盘。实验的一个单独结果称为结果。事件是我们感兴趣的一个或多个结果的集合，比如“掷出大于 4 的数”包含结果 5 和 6。
The sample space is a list or diagram of all possible outcomes of an experiment. If you flip a coin, the sample space is {Heads, Tails}. If you roll a dice, it is {1,2,3,4,5,6}. You can draw a two-way table or a tree diagram to help list the sample space when two things happen together, like flipping two coins. A systematic approach avoids missing any possibilities.
样本空间是一个实验所有可能结果的列表或图示。如果抛一枚硬币，样本空间是 {正面, 反面}。如果掷骰子，样本空间是 {1,2,3,4,5,6}。当两个事件同时发生时，比如同时抛两枚硬币，你可以画一个二维表格或树状图来帮助列出样本空间。采用系统的方法可以避免遗漏任何可能性。
10. Memory Hacks and Quick Self-Test | 速记窍门与快速自测
Here are some memory aids to lock all these terms into your mind. For averages, think ‘MMMR’ – Mean, Median, Mode, Range. For chart types, remember ‘BPP Scratch’: Bar, Pictogram, Pie, Scatter. For probability steps, use ‘OSE’: Outcome, Sample space, Event. Create silly sentences: ‘Clever Cats Measure Continually’ highlights that Continuous data involves Measurement. Draw a mind map with the word ‘Statistics’ in the centre and branches for Data, Averages, Charts, Probability – adding one key term to each branch.
这里有一些记忆辅助方法，帮助你把这些术语牢牢锁在脑海中。对于平均数，记住“MMMR”——平均数、中位数、众数、极差。对于图表类型，记住“BPP Scratch”：条形图、象形图、饼图、散点图。对于概率步骤，使用“OSE”：结果、样本空间、事件。还可以编造一些滑稽的句子：“Clever Cats Measure Continually（聪明的猫不断测量）”强调了连续数据涉及测量。画一张思维导图，把“Statistics”放在中心，分支写上数据、平均数、图表、概率，并在每个分支上加一个关键术语。
Now try this quick self-test. Read each description and name the term. (1) The value that occurs most often. Answer: Mode. (2) The diagram that uses pictures to represent numbers. Answer: Pictogram. (3) The measure that shows how spread out data is, found by subtracting the smallest from the largest. Answer: Range. (4) A diagram that needs a protractor to draw. Answer: Pie chart. (5) The set of all possible outcomes for an experiment. Answer: Sample space. (6) Data that can only take whole-number values. Answer: Discrete data. How many did you get right? Go back to the section if you missed any.
现在试试这个快速自测。阅读每条描述并说出对应的术语。（1）出现次数最多的值。答案：众数。（2）用图片表示数字的图表。答案：象形图。（3）通过最大值减最小值得到的、显示数据分散程度的量度。答案：极差。（4）需要使用量角器绘制的图表。答案：饼图。（5）一个实验所有可能结果的集合。答案：样本空间。（6）只能取整数值的数据。答案：离散数据。你答对了几道？如果漏掉了哪个，回头看看相应小节。
Published by TutorHao | Statistics Revision Series | aleveler.com
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