📚 KS3 CIE Statistics: A Fast-Track Vocabulary and Terminology Guide | KS3 CIE 统计：词汇术语速记指南
Mastering statistics starts with understanding the language of data. This guide breaks down the essential terms you will encounter in Key Stage 3 CIE Statistics, helping you remember them quickly and use them with confidence. Whether you are describing a survey, interpreting a chart, or calculating an average, a solid vocabulary gives you the foundation for success.
掌握统计学始于理解数据的语言。本指南拆解了你在 Key Stage 3 CIE 统计课程中会碰到的关键术语，帮助你快速记忆并自信地运用。无论你是在描述一项调查、解读一张图表还是计算一个平均值，扎实的词汇基础都会为你的成功铺路。
1. Data Fundamentals | 数据基础
Data is any collection of facts, numbers, or measurements that can be used for analysis. In statistics, we gather data to answer questions, spot patterns, or make decisions.
数据是任何可用于分析的事实、数字或测量值的集合。在统计学中，我们收集数据来回答问题、发现规律或做出决策。
Primary data is information you collect yourself for a specific purpose, such as conducting a traffic count outside your school. It is original and directly from the source.
原始数据是你自己为特定目的而收集的信息，比如在学校外面进行车流量计数。它是第一手的，直接来源于源头。
Secondary data is information that someone else has already collected. Examples include government census reports, weather records, or data found on reputable websites.
二手数据是别人已经收集好的信息。例子包括政府人口普查报告、天气记录或在可靠网站上找到的数据。
Raw data is data that has not yet been organised, cleaned, or summarised. It often appears as a simple list of numbers or responses, waiting to be sorted into tables or charts.
原始数据是尚未整理、清洗或汇总的数据。它通常表现为一组简单的数字或回答，等待被分类到表格或图表中。
An observation refers to each individual piece of recorded information. In a survey of pet ownership, every student's answer about having a dog, cat, or no pet is an observation.
观测值指每一个被记录下来的单独信息。在一次关于养宠物的调查中，每位学生对是否有狗、有猫或没有宠物的回答就是一个观测值。
2. Types of Data | 数据类型
We classify data to choose the right way to display and analyse it. The main distinction is between qualitative and quantitative data.
我们对数据进行分类，是为了选择正确的展示和分析方式。主要的区别在于定性数据和定量数据之间。
Qualitative data describes qualities, categories, or labels and cannot be measured with numbers in a meaningful arithmetic way. Colours, favourite subjects, and types of transport are all qualitative.
定性数据描述的是性质、类别或标签，无法用数字进行有意义的算术测量。颜色、最喜欢的学科、交通方式类型都属于定性数据。
Quantitative data is numerical and tells us about quantities or amounts. It can be measured and used in calculations. Height, test scores, and the number of siblings are quantitative.
定量数据是数字型的，告诉我们的量或多少。它可以被测量并用于计算。身高、测验分数和兄弟姐妹的数量都是定量数据。
Quantitative data is further split into discrete and continuous data. Discrete data can only take certain separate values, usually whole numbers. Continuous data can take any value within a range.
定量数据可进一步分为离散数据和连续数据。离散数据只能取某些分开的值，通常是整数。连续数据可以取一个范围内的任何值。
| Type | Definition | Example |
|---|---|---|
| Discrete | Countable gaps between values | Shoe size (whole sizes), number of books in a bag |
| Continuous | Can take any value on a continuum | Height (cm), time (seconds), mass (kg) |
Remember: if you are counting something, it is usually discrete. If you are measuring with an instrument, it is likely continuous.
记住：如果你是在计数，通常就是离散数据。如果你是在用工具测量，很可能就是连续数据。
3. Measures of Central Tendency | 集中趋势度量
These measures summarise a data set by identifying a typical or central value. The three most common ones are the mean, median, and mode.
这些度量通过确定一个典型值或中心值来概括一组数据。最常见的三个是平均数、中位数和众数。
The mean is what most people call the average. It is found by adding up all the values and then dividing by how many values there are.
平均数就是大多数人所说的平均值。它的计算方法是把所有数值加起来，然后除以数值的个数。
Mean = (Sum of all values) ÷ (Number of values)
The median is the middle value when the data is arranged in order from smallest to largest. If there are two middle numbers, the median is the mean of those two.
中位数是将数据从小到大排列后位于中间的那个值。如果中间有两个数，中位数就是这两个数的平均值。
The mode is the value that appears most frequently in a data set. A set can have one mode, more than one mode (bimodal or multimodal), or no mode at all if all values occur equally often.
众数是数据集中出现次数最多的值。一组数据可能有一个众数、多个众数（双众数或多众数），如果所有值出现次数相同则没有众数。
4. Measures of Dispersion | 离散度量
Central tendency tells you where the centre is, but dispersion tells you how spread out the data are. The simplest measure of spread is the range.
集中趋势告诉你中心在哪里，而离散度量则告诉你数据的分散程度。最简单的离散度量就是极差。
The range is the difference between the largest and smallest values in a data set. It gives a quick idea of variability but can be heavily influenced by outliers.
极差是数据集中最大值和最小值之间的差值。它能快速了解变异程度，但容易受到异常值的影响。
Range = Maximum value − Minimum value
In Key Stage 3 you will often use the range to compare the consistency of two groups. A smaller range suggests the data are more tightly clustered together.
在 KS3 阶段，你经常会使用极差来比较两组的稳定性。极差较小意味着数据更加集中。
Later you may meet the interquartile range (IQR), which is the range of the middle 50% of the data, focusing on the spread that ignores extreme values.
以后你还会接触到四分位距 (IQR)，它是中间 50% 数据的范围，重点关注忽略极值的分散情况。
5. Frequency Distributions | 频数分布
A frequency distribution shows how often each value or category occurs. It is the backbone of many statistical diagrams.
频数分布展示了每个值或类别出现的频率。它是许多统计图表的支柱。
Frequency is simply the number of times a particular data value or event happens. For instance, if 8 students walk to school, the frequency of 'walk' is 8.
频数就是某个特定的数据值或事件发生的次数。例如，若有 8 名学生步行上学，那么 "步行" 的频数就是 8。
A tally is a quick counting method using vertical marks, often grouped in fives for easy reading. It helps you record data accurately before putting it into a table.
划记是一种使用竖线标记的快速计数方法，通常每五个一组以便认读。它帮助你在整理成表格之前准确记录数据。
A frequency table lists all outcomes or categories alongside their frequencies. For continuous data, we often use a grouped frequency table with class intervals.
频数表列出了所有结果或类别及其相应的频数。对于连续数据，我们常常使用带有组距的分组频数表。
The class interval is the width of each group in a grouped frequency table. Intervals such as '10-19', '20-29' must not overlap and should be the same width where possible.
组距是分组频数表中每一组的宽度。像 "10-19", "20-29" 这样的区间不能重叠，且应尽可能保持宽度一致。
6. Charts and Pictograms | 图表与象形图
Visual representations make data easier to understand. At KS3 you need to be familiar with several chart types and know when to use each one.
可视化的呈现方式让数据更容易理解。在 KS3 阶段，你需要熟悉几种图表类型，并知道何时使用每种图表。
A bar chart uses rectangular bars of equal width to show frequencies. The bars do not touch, because the data are categories or discrete values.
条形图使用宽度相等的矩形条来展示频数。条与条之间不接触，因为数据是类别或离散值。
A pictogram uses simple pictures or symbols to represent data. Each symbol stands for a fixed number of units, and a key must be provided to explain this.
象形图使用简单的图片或符号来呈现数据。每个符号代表固定数量的单位，并且必须给出图例来解释这一点。
A pie chart displays proportions as slices of a circle. The whole circle represents 100% of the data, and each slice shows a category's share of the total.
饼图将比例显示为一个圆的扇形。整个圆代表数据的 100%，每个扇区显示该类别在总数中所占的份额。
A line graph plots data points connected by straight line segments. It is particularly useful for showing changes over time, such as temperature readings throughout a day.
折线图用直线段连接各个数据点。它对于显示随时间变化的情况特别有用，比如一天内的温度读数。
7. Probability Concepts | 概率概念
Probability is the branch of mathematics that deals with how likely events are to happen. Its vocabulary is very precise.
概率是数学中处理事件发生可能性的分支。它的词汇非常精确。
An experiment is any process that produces outcomes, such as rolling a dice or spinning a spinner. A trial is one repetition of the experiment.
试验是任何产生结果的过程，比如掷骰子或转动转盘。一次试做就是试验的一次重复。
An outcome is a single possible result of an experiment. When a fair coin is tossed, the two possible outcomes are 'heads' and 'tails'.
结果是一次试验中可能出现的单个结果。抛掷一枚公平硬币时，两个可能的结果是 "正面" 和 "反面"。
The sample space is the set of all possible outcomes. For a single dice roll, the sample space is {1, 2, 3, 4, 5, 6}.
样本空间是所有可能结果的集合。单次掷骰子的样本空间是 {1, 2, 3, 4, 5, 6}。
An event is a set of outcomes that we are interested in. For example, rolling an even number on a dice is an event that includes the outcomes 2, 4, and 6.
事件是我们感兴趣的一组结果。例如，掷骰子出现偶数就是一个事件，包含了 2、4 和 6 这三个结果。
The probability of an event is a number between 0 and 1, representing how likely it is. It is calculated as:
一个事件的概率是一个介于 0 和 1 之间的数，表示它发生的可能性大小。计算方式为：
P(Event) = Number of favourable outcomes ÷ Total number of possible outcomes
A probability of 0 means the event is impossible, while a probability of 1 means the event is certain. An even chance has a probability of 0.5 or 1/2.
概率为 0 意味着事件不可能发生，而概率为 1 意味着事件必然发生。均等机会的概率是 0.5 或 1/2。
8. Sampling and Surveys | 抽样与调查
When we cannot collect data from the whole population, we rely on a sample. The population is the entire group we want to know about.
当我们无法从整个总体收集数据时，就要依靠样本。总体是我们想了解的全部对象。
A sample is a smaller group selected from the population. The key is that the sample must be representative so that we can draw valid conclusions about the whole population.
样本是从总体中选出的一个较小的群体。关键在于样本必须具有代表性，这样我们才能对总体得出有效的结论。
In a survey, we ask a set of questions to gather data. Designing good questions without ambiguity helps collect reliable primary data.
在调查中，我们提出一系列问题来收集数据。设计明确的好问题有助于收集到可靠的原始数据。
A questionnaire is a written form containing the questions. It may include tick-box answers, rating scales, or open-ended text responses for qualitative information.
问卷是一份包含问题的书面表格。它可以包括勾选框、评价量表或用于定性信息的开放式文字回答。
Random sampling means every member of the population has an equal chance of being chosen. This avoids favouring any particular group and reduces bias.
随机抽样意味着总体中的每个成员都有均等的机会被选中。这样做避免了偏向任何特定群体，减少了偏差。
9. Common Pitfalls and Bias | 常见陷阱与偏差
Bias is anything that systematically distorts the data or the conclusions drawn from it. Understanding bias helps you criticise statistics and design better investigations.
偏差是任何系统性地扭曲数据或从中得出的结论的因素。理解偏差能帮助你批判统计数据，并设计出更好的调查。
A leading question is one that pushes people towards a particular answer. 'You agree that maths is the best subject, don't you?' is clearly biased.
诱导性问题会推动人们给出特定的答案。"你同意数学是最棒的学科，不是吗？" 就明显带有偏差。
Using a sample that is too small can give unreliable results. A tiny sample might not capture the full picture and could lead to wrong conclusions about the population.
样本太小可能导致结果不可靠。一个微小的样本可能无法反映全貌，从而得出关于总体的错误结论。
Non-response bias occurs when a significant number of chosen individuals do not participate. The opinions of those who respond might differ greatly from those who stay silent.
无回应偏差发生在大量被选择的个人不参与调查时。那些回应者的观点可能与保持沉默的人大相径庭。
Always relate the vocabulary you learn to fairness and critical thinking. Before trusting a statistic, ask: How was the data collected? Who was asked? Is the sample representative?
永远要将你所学的词汇与公平性和批判性思维联系起来。在相信一个统计数字之前，先问一问：数据是如何收集的？问了谁？样本有代表性吗？
10. Vocabulary in Action | 词汇应用
Being able to remember these terms is only half the battle – you must also use them accurately in sentences and when interpreting real data.
能记住这些术语只是成功的一半——你还必须能在句子中和解读真实数据时准确地使用它们。
When describing a bar chart, say: 'The mode is blue, with a frequency of 15. The range of the data is small, so there is little variation between categories.'
在描述一个条形图时，可以说："众数是蓝色，频数为 15。数据的极差很小，所以类别之间的差异不大。"
For a probability question, use: 'The sample space contains six equally likely outcomes. The probability of the event "rolling a factor of 6" is 4/6, or 2/3.'
对于概率问题，使用："样本空间包含六个等可能的结果。事件 '掷出一个 6 的因数' 的概率是 4/6，即 2/3。"
When criticising a survey, you might write: 'The sample is biased because only students in the playground were asked, ignoring those who stay indoors at break time.'
在批评一个调查时，你可以写道："这个样本有偏差，因为只询问了操场上的学生，忽略了那些课间待在室内的学生。"
Create your own mnemonics to lock in terms. For discrete versus continuous, think: 'Discrete = Dots you can separate; Continuous = Connected values.' Repeated use in context builds lasting memory.
创造属于你自己的助记法来牢记术语。对于离散和连续，可以想："Discrete = 可分开的点；Continuous = 相连的值。" 在语境中反复使用可以形成持久的记忆。
Keep a glossary where you write the term, its definition, an example, and a short sentence. This active recall method is proven to make statistical vocabulary stick.
准备一个词汇表，写下术语、定义、例子和一个简短的句子。这种主动回忆的方法已被证实能让统计词汇深深印在脑海中。
Published by TutorHao | Statistics Revision Series | aleveler.com
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