📚 Year 10 CIE Statistics: Key Vocabulary Quick-Reference Guide | CIE 统计学关键术语速记指南
Welcome to your essential statistics vocabulary guide. Whether you’re preparing for CIE IGCSE Mathematics or a dedicated Statistics paper, knowing the precise meaning of keywords builds a solid foundation. This resource explains core terms with clear examples, helping you memorise definitions quickly and apply them correctly in exams.
欢迎使用这本统计学必备词汇指南。无论您正在备考 CIE IGCSE 数学还是独立的统计学考试，准确理解关键词的含义都能打下坚实基础。本资源通过清晰的例子解释核心术语，帮助您快速记忆定义并在考试中正确应用。
1. Types of Data | 数据类型
Qualitative Data: Non-numerical information that describes qualities or categories, also called categorical data. Examples: colours, types of car, survey responses like ‘yes’ or ‘no’.
定性数据（Qualitative Data）：描述性质或类别的非数值信息，也称为分类数据。例如：颜色、汽车类型、调查中的“是”或“否”。
Quantitative Data: Numerical information that can be measured or counted. It answers questions of ‘how much’ or ‘how many’. Examples: height, mass, test scores.
定量数据（Quantitative Data）：可测量或计数的数值信息。它回答“多少”的问题。例如：身高、质量、考试分数。
Discrete Data: Quantitative data that can only take specific, separate values, often counted in whole numbers. For instance, number of students in a class, shoe sizes.
离散数据（Discrete Data）：只能取特定、分离数值的定量数据，通常以整数计数。例如：班级学生人数、鞋码。
Continuous Data: Quantitative data that can take any value within a range, measured rather than counted. Examples: time taken to run 100 metres, temperature, length.
连续数据（Continuous Data）：在某个范围内可以取任意值的定量数据，通常是测量而非计数所得。例如：跑100米的时间、温度、长度。
2. Measures of Central Tendency | 集中趋势的度量
The mean (arithmetic average) is found by adding all data values and dividing by the number of values. It is the most common average, but can be affected by outliers.
Mean = (∑x) ÷ n
平均数（均值）：将所有数据值相加再除以数据的个数。这是最常见的平均数，但容易受异常值影响。公式：平均数 = (∑x) ÷ n。
The median is the middle value when the data are arranged in order. If there are n values, the median is at position (n+1)/2. For an even number of data, it is the average of the two middle numbers. The median is not affected by extreme values.
中位数：将数据按大小顺序排列后处于中间位置的值。若有 n 个数据，中位数的位置是 (n+1)/2。当数据个数为偶数时，中位数是中间两个数的平均值。中位数不受极端值影响。
The mode is the value that occurs most frequently in a data set. A data set can have one mode (unimodal), more than one mode (bimodal or multimodal), or no mode if all values appear with the same frequency.
众数：在一组数据中出现次数最多的值。一组数据可能有一个众数（单峰）、多个众数（双峰或多峰），或者所有值出现频数相同则没有众数。
3. Measures of Dispersion | 离散程度的度量
The range is the simplest measure of spread, calculated as the difference between the largest and smallest values: Range = Maximum − Minimum. It gives a quick sense of how spread out the data are, but it is highly sensitive to outliers.
极差（范围）：最简单的离散度量，计算最大值与最小值之差：范围 = 最大值 − 最小值。它能快速反映数据的分散程度，但对异常值非常敏感。
The interquartile range (IQR) measures the spread of the middle 50% of the data, making it more resistant to outliers. IQR = Upper quartile (Q&sb3;) − Lower quartile (Q&sb1;). It gives a more stable indication of dispersion.
四分位距（IQR）：衡量中间50%数据的散布程度，更能抵抗异常值的影响。IQR = 上四分位数 (Q₃) − 下四分位数 (Q₁)。它能更稳定地反映离散程度。
Variance and standard deviation: Variance (σ²) is the average of the squared differences from the mean. Standard deviation (σ) is the square root of variance. These measures describe how much data values deviate from the mean. For a population: σ² = ∑(x − &xbar;)² / n
方差与标准差：方差 (σ²) 是各个数据与平均数之差的平方的平均数。标准差 (σ) 是方差的平方根。它们描述数据值偏离平均数的程度。总体公式：σ² = ∑(x − x̄)² ÷ n。
4. Quartiles and Percentiles | 四分数与百分位数
The lower quartile (Q&sb1;) is the median of the lower half of the data, leaving 25% of observations below it. To find Q&sb1;, you can use the position (n+1)/4 and interpolate if necessary.
下四分位数 (Q₁)：数据较小一半的中位数，有25%的观测值小于它。找到 Q₁ 可用位置 (n+1)/4，必要时进行插值。
The upper quartile (Q&sb3;) is the median of the upper half; 75% of data lie below it. Its position is given by 3(n+1)/4.
上四分位数 (Q₃)：数据较大一半的中位数，75%的数据小于它。它的位置由 3(n+1)/4 给出。
A percentile indicates the value below which a given percentage of observations fall. The k-th percentile is the value below which k% of data lie. The median is the 50th percentile, Q&sb1; is the 25th percentile, and Q&sb3; is the 75th percentile.
百分位数：表示在某一百分比以下的观测值。第k百分位数就是有k%的数据小于该值。中位数是第50百分位数，Q₁是第25百分位数，Q₃是第75百分位数。
5. Frequency Distributions | 频数分布
Frequency is the number of times a particular data value or event occurs. A frequency table organises raw data by listing values alongside their counts. It is the starting point for most statistical displays.
频数：某一特定数据值或事件出现的次数。频数表通过列出各值及相应次数来整理原始数据，是大多数统计图的起点。
For grouped data, data are organised into class intervals (bins) such as 10–19, 20–29, etc. The class width is the difference between the upper and lower class boundaries. The midpoint of a class is (lower boundary + upper boundary) / 2, used for estimating the mean.
对于分组数据，数据被组织成组距（如10–19、20–29等）。组距宽度是上下限之差。组中点是（下限 + 上限）÷ 2，用于估算平均值。
Cumulative frequency is the running total of frequencies up to the end of each class interval. It helps locate quartiles and medians in grouped data.
累积频数：到每一个组距末尾为止的频数逐次累加之和。它有助于在分组数据中确定四分位数和中位数。
6. Graphical Representations | 图形表示
A bar chart uses rectangular bars of equal width for categorical data, with heights proportional to frequency or magnitude. Gaps between bars emphasise that the categories are separate.
条形图：用于分类数据，使用等宽长方形条形，高度与频数或数值成比例。条形之间的间隙强调类别是分开的。
A pie chart displays proportions of a whole by dividing a circle into sectors. The sector angle equals (category frequency / total frequency) × 360°.
饼图：通过将圆分割成扇形显示各组成部分占整体的比例。扇形角度 = （类别频数 ÷ 总频数）× 360°。
A histogram represents grouped
Published by TutorHao | Year 10 统计 Revision Series | aleveler.com
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