📚 Year 8 AQA Statistics: Vocabulary & Terminology Quick Memorisation Guide | Year 8 AQA 统计：词汇术语速记指南
Welcome to your essential fast-track memorisation guide for Year 8 AQA Statistics. Mastering statistical vocabulary is like learning the alphabet before reading – it unlocks every graph, calculation, and probability statement you will encounter. This guide pairs each term with a clever memory hook, supported by clear bilingual explanations, so you can recall definitions accurately under exam pressure.
欢迎来到 Year 8 AQA 统计的必备词汇速记指南。掌握统计术语如同阅读前先学字母表——它是理解所有图表、计算和概率陈述的基础。本指南为每个术语搭配巧妙的记忆钩子，配合清晰的中英双语讲解，帮助你考试时准确回忆定义。
1. The Average Family: Mean, Median, Mode & Range | 平均数家族：均值、中位数、众数与极差
In any data set, averages help us identify a typical value. There are three main averages – the mean, median and mode – and alongside them we often calculate the range to measure how spread out the data are.
任何数据集中，平均数帮我们找到典型值。主要的平均数有三种——均值、中位数和众数——此外我们常计算极差来衡量数据的分散程度。
The mean is found by adding up all values and dividing by the number of values. A quick memory tip: the ‘mean’ teacher makes you do all the adding and dividing, so ‘mean’ rhymes with ‘keen’ on calculation. The median is the middle value when the data are sorted. Picture the median strip on a dual carriageway – it sits right in the middle. The mode is the value that appears most often; think M.O. = Most Often. The range is the difference between the largest and smallest values, a simple subtraction.
计算均值时，先将所有数值相加，再除以数据个数。记忆秘诀：均值的“均”需要“均匀”地计算。找中位数要把数据排序后取中间位置的数，想象马路中间的隔离带，不偏不倚。找众数就看出现次数最多的那个值，英文 mode 的首字母可联想为 Most Often。极差就是最大值减去最小值，反映跨度。
| Term 术语 | Definition 定义 | Quick Memory Aid 速记法 |
|---|---|---|
| Mean 均值 | Sum divided by count | Mean = ‘keen’ on arithmetic |
| Median 中位数 | Middle value when ordered | Median strip in road |
| Mode 众数 | Most frequent value | M.O. = Most Often |
| Range 极差 | Maximum – minimum | Range of spread |
Mean = (Σ x) ÷ n
2. Data Types: Qualitative vs Quantitative | 数据类型：定性数据与定量数据
Before you can choose the right diagram or statistic, you must identify the type of data. The first big distinction is between qualitative and quantitative data.
在选择合适的图表或统计量之前，必须先识别数据类型。第一个重要区分就是定性数据和定量数据。
Qualitative data describes qualities or categories – it answers questions like ‘what colour?’ or ‘which favourite subject?’. These data are non-numerical, even if you encode them with numbers (e.g. 1 for blue, 2 for red). In contrast, quantitative data measures quantities and is truly numerical, such as height in centimetres or test scores. Memorise it simply: ‘Qual’ belongs to quality, ‘Quan’ belongs to quantity.
定性数据描述性质或类别，回答“什么颜色？”“喜欢哪个科目？”之类的问题。这类数据本质是非数字的，即使你用数字编码（如1代表蓝色，2代表红色）。定量数据则是测量数量的大小，是真正的数值，例如身高（厘米）或考试分数。简单记忆：“定性”讲品质，“定量”讲数量。
3. Quantitative Subtypes: Discrete and Continuous | 定量数据分类：离散数据与连续数据
Quantitative data can be further split into two important subtypes – discrete and continuous. Recognising the difference determines whether you draw a bar chart or a line graph later.
定量数据可进一步细分为两个重要子类——离散数据与连续数据。识别两者的区别将决定你之后是画条形图还是折线图。
Discrete data can only take specific, separate values, usually counts. Examples include the number of pets in a household or shoe sizes (you cannot have 2.3 pets!). Continuous data can take any value within a given range, such as height, mass, or temperature. Imagine discrete data as steps on a staircase – you can only stand on one step. Continuous data is like a ramp or a smooth line – you can stop at any point. Remember: ‘discrete’ means distinct and countable, while ‘continuous’ flows without gaps.
离散数据只能取特定、可数的值，通常是计数结果。例如家里的宠物数量或鞋码（你不可能有2.3只宠物！）。连续数据在一定范围内可取任意值，例如身高、体重或温度。想象离散数据就像楼梯的台阶，你只能踩在某一级上；连续数据则像斜坡或平滑线条，你可以在任意位置停住。记住：离散可数，连续无间断。
4. Population & Sample: The Whole and the Part | 总体与样本：全体与部分
When collecting data, you rarely ask everyone. Understanding the difference between a population and a sample is central to fair statistics.
收集数据时，很少能询问到每一个人。理解总体与样本的区别是实现公正统计的核心。
The population is the entire group you wish to investigate – all students in a school, all cars made in a factory. A sample is a smaller group selected from the population to represent it. Because surveying a whole population can be impossible or expensive, we rely on samples. Think: ‘Pop’ like ‘popular’ – everyone included; ‘Sam’ like ‘some’ – just a selection. To be useful, the sample must be representative and ideally random.
总体是你想要调查的全部对象——如果研究全校学生，全校学生就是总体。样本是从中抽取的一个较小群体，用以代表总体。由于普查往往费时费力，我们常通过样本推断。联想：“总”即全体，“样”即一部分。为了让样本有用，它必须具有代表性，最好通过随机方式抽取。
5. Avoiding Bias: Fair Sampling | 避免偏差：公平抽样
If your sample does not truly reflect the population, your conclusions may be biased – and that is a serious error in statistics.
如果样本不能真实反映总体，你的结论就可能存在偏差——这在统计中是严重的错误。
Bias occurs when some members of the population are more likely to be chosen than others. For example, asking only your friends about a new school rule gives a biased view. To avoid this, use random sampling where each individual has an equal chance of being picked. Pulling names from a hat or using a random number generator are good methods. Steer clear of convenience sampling, where you just choose whoever is easy to reach; that rarely produces a representative picture.
当总体中某些成员比其他成员更容易被选入样本时，就产生了偏差。比如只向自己的朋友询问对某条新校规的看法，得到的观点就会片面。为避免偏差，应采用随机抽样，让每个个体被选中的机会相等。抽签或使用随机数生成器都是好方法。要避免便利抽样，也就是图省事只选容易接触到的人，那样几乎无法得到有代表性的结果。
6. Organising Data: Frequency Tables & Tally Charts | 数据整理：频数表与划记表
Raw data can look like a jumble of numbers or words. Before you can draw any chart, you need to organise it using frequency tables and tally charts.
原始数据往往是一堆混杂的数字或词语。在画出任何图表之前，你需要用频数表和划记表把数据整理清楚。
A frequency table lists each possible value or category alongside how many times it appears – its frequency. To build it, you can use a tally chart where each observation is recorded as a small mark; every fifth mark is drawn diagonally across the previous four (~~IIII~~) to speed up counting by fives. This turns messy raw data into neat, organised information ready for graphing.
频数表会列出每个可能的取值或类别，并在旁边注明它出现的次数——即频数。制作频数表时，可以先用划记表，每观察到一个数据就画一个记号，满五个时在前四个记号上斜画一笔(“正”字计数)，这样以五为一组可以加快计数。这样就能把杂乱的原始数据变成整齐有序的信息，为绘图做好准备。
| Colour 颜色 | Tally 划记 | Frequency 频数 |
|---|---|---|
| Red 红 | ~~IIII~~ | 5 |
| Blue 蓝 | III | 3 |
7.
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