📚 Year 13 CCEA Statistics: A Quick Memorisation Guide to Key Terms | Year 13 CCEA 统计：关键术语速记指南
Memorising statistical terminology is essential for success in CCEA Year 13 Statistics. This guide breaks down key terms into logical groups and offers memory aids, helping you recall definitions quickly during exams.
记忆统计学术语对在 CCEA 13 年级统计考试中取得成功至关重要。本指南将关键术语划分为逻辑组，并提供记忆辅助，帮助你在考试中快速回忆定义。
1. Population, Sample and Census | 总体、样本与普查
Population: the entire set of individuals or items we wish to study. Think of it as the ‘whole pie’.
总体：我们想要研究的全部个体或项目的集合。把它想象成”整个馅饼”。
Sample: a subset of the population selected for investigation. A ‘slice of the pie’ that represents the whole.
样本：从总体中选出来用于调查的一个子集。代表整体的”一块馅饼”。
Census: a survey that measures every member of the population. Very accurate but often expensive and time-consuming.
普查：测量总体中每个成员的调查。非常准确，但通常昂贵且耗时。
Sampling frame: a list of all the members of the population from which the sample is drawn. Without a good frame, bias creeps in.
抽样框：总体所有成员的名单，从中抽取样本。没有一个好的抽样框，就会产生偏差。
Sampling unit: each individual member that could be selected for the sample.
抽样单位：每个可能被选入样本的个体成员。
2. Parameter and Statistic | 参数与统计量
Parameter: a numerical summary describing a characteristic of a population. Usually unknown and fixed. Symbolised by Greek letters such as μ (population mean) and σ (population standard deviation).
参数：描述总体某一特征的数值摘要。通常是未知且固定的。用希腊字母表示，如 μ（总体均值）和 σ（总体标准差）。
Statistic: a numerical summary calculated from a sample. It is an estimate of the parameter and varies from sample to sample. Denoted by Latin letters: x̄ (sample mean), s (sample standard deviation).
统计量：从样本中计算得出的数值摘要。它是参数的估计值，并且随样本不同而变化。用拉丁字母表示：x̄（样本均值），s（样本标准差）。
Memory tip: Parameter → Population; Statistic → Sample. Greek letters for the population, Latin for the sample.
记忆技巧：参数（Parameter）对应总体（Population）；统计量（Statistic）对应样本（Sample）。总体用希腊字母，样本用拉丁字母。
3. Types of Data | 数据类型
Qualitative data: non-numerical categories or labels, also called categorical. Examples: eye colour, favourite sport.
定性数据（质性数据）：非数字的类别或标签，也称为分类数据。例如：眼睛颜色、最喜欢的运动。
Quantitative data: numerical measurements or counts. Can be discrete or continuous.
定量数据：数字度量的值或计数。可以是离散的或连续的。
Discrete data: can only take specific, separate values, often integers. For example, the number of pets in a household (0, 1, 2, …).
离散数据：只能取特定、分离的值，通常是整数。例如，家庭中宠物的数量（0, 1, 2, …）。
Continuous data: can take any value within a given range. Examples: height, weight, time. You can always measure to a finer level.
连续数据：可以在给定范围内取任意值。例如：身高、体重、时间。你总可以测量到更精细的程度。
- Nominal: no natural order (e.g. hair colour).
- 名义：无自然顺序（例如发色）。
- Ordinal: categories have a meaningful order (e.g. satisfaction ratings).
- 有序：类别有有意义的顺序（例如满意度评级）。
4. Sampling Methods | 抽样方法
Simple random sampling: every member of the population has an equal chance of selection. Requires a sampling frame and random numbers.
简单随机抽样：总体中每个成员有相等的被选概率。需要抽样框和随机数。
Systematic sampling: choose every kth individual from the frame after a random start. Easy but can be biased if there is a hidden pattern.
系统抽样：在随机起点后，从抽样框中每隔 k 个抽取一个个体。简便易行，但如果存在隐藏模式，可能产生偏差。
Stratified sampling: divide the population into distinct groups (strata) and take a simple random sample from each. Ensures proportional representation.
分层抽样：将总体划分为不同组（层），并从每层中抽取简单随机样本。确保比例代表。
Quota sampling: non-random; interviewer selects a set number of people from each category. Quick but subject to interviewer bias.
配额抽样：非随机；采访者从每个类别中选择固定数量的人。快速但受采访者偏差影响。
Cluster sampling: divide the population into clusters, randomly select some clusters, and then survey all members within them.
整群抽样：将总体划分为群，随机选取一些群，然后调查其中所有成员。
5. Bias and Errors | 偏差与误差
Bias: systematic error that leads to over- or underestimation. Arises from poor sampling design, non-response, or measurement errors.
偏差：导致高估或低估的系统性误差。来源于不良的抽样设计、无回应或测量误差。
Sampling error: the natural variability between
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