Stats Terms Memory Guide for Year 8 Cambridge | 剑桥八年级统计词汇速记指南

📚 Stats Terms Memory Guide for Year 8 Cambridge | 剑桥八年级统计词汇速记指南

Welcome to your Year 8 Cambridge Statistics memory guide! This article will help you quickly master key vocabulary through bilingual explanations and clever mnemonics. By linking technical terms to mental images and patterns, you’ll build a solid foundation for data handling and probability. Let’s dive into the world of data, charts, averages and chance.

欢迎来到八年级剑桥统计词汇速记指南！本文通过双语解释和巧妙记忆法帮助你快速掌握核心术语。把专业词汇与心理图像和模式联系起来，你就能为数据处理和概率打下扎实基础。下面我们一起进入数据、图表、平均数和概率的世界。

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1. Data and Surveys | 数据与调查

Data is the raw information we collect, measure and analyse. In statistics, a survey uses questions to gather data from a group. If you collect data yourself, it’s primary data; if you use data someone else collected, it’s secondary data. Remember: primary = personal, secondary = second-hand.

数据是我们收集、测量和分析的原始信息。在统计学中，调查通过提问从群体中收集数据。如果你自己收集数据，那就是一手数据；若使用他人收集的数据，则是二手数据。记住：一手数据亲自采集，二手数据来自别人。

A well-designed survey uses clear, unbiased questions. Always check whether the data is categorical (like favourite colour) or numerical (like height). Think of categories as ‘labels’ and numbers as ‘measurements’.

一份设计良好的调查会使用清晰、无偏见的问题。始终检查数据是分类数据（如最喜欢的颜色）还是数值数据（如身高）。把分类想成“标签”，数值想成“测量值”。

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2. Population and Sample | 总体与样本

The population is the entire group you want to know about. A sample is a smaller, manageable subset selected from the population. The sample must be representative, meaning it mirrors the population without bias. Imagine a population as the whole cake and the sample as a slice you taste.

总体是你要了解的全部群体。样本是从总体中选出的较小、可处理的子集。样本必须具有代表性，即它无偏见地反映总体。把总体想象成整个蛋糕，样本就是尝的那一小块。

A key skill in Year 8 is identifying whether a sample is random or biased. A random sample gives every member an equal chance of being chosen, like drawing names from a hat. A biased sample over-represents certain groups, e.g., asking only football players about sports preferences.

八年级的一项关键技能是判断样本是随机的还是有偏的。随机样本让每个成员都有相等机会被选中，比如从帽子里抽名字。有偏样本则过度代表某些群体，例如只问足球运动员关于运动偏好。

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3. Data Types: Discrete, Continuous and Categorical | 数据类型：离散、连续和分类

Discrete data can only take separate, countable values, like the number of students in a class (0, 1, 2, …). There are no in-between values – you can’t have 2.5 students. Think discrete = distinct points on a number line.

离散数据只能取分离、可数的值，如班级学生人数（0, 1, 2, …）。没有中间值——你不可能有2.5个学生。把离散想象成数字线上分开的点。

Continuous data can take any value within a range, like height, mass or temperature. You measure rather than count it. The word ‘continuous’ hints that the number line continues smoothly without gaps.

连续数据可以取某个范围内的任何值，如身高、质量或温度。你需要测量而不是计数。‘连续’这个词暗示数字线平滑延续，没有间隔。

Categorical data (also called qualitative data) describes qualities or groups, e.g., hair colour, types of pet. These can be ordered (ordinal, like survey ratings) or not (nominal, like colours). Think of categories as ‘what kind’ not ‘how much’.

分类数据（也称定性数据）描述性质或组别，如头发颜色、宠物类型。它们可以是有序的（序数，如调查评分）或无序的（名义，如颜色）。把分类想成“哪种”而非“多少”。

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4. Frequency and Tally Charts | 频率与计数表

Frequency tells you how often something occurs. Tally charts use tally marks (|||| with the fifth mark crossing through) to count quickly. Each group of five makes totals easy to read. The frequency column then records the total for each category.

频率告诉你某件事发生的次数。计数表使用标记（画四竖一横进行五进制计数）快速计数。每五个一组使总数易于读取。然后频率栏记录每个类别的总数。

When creating a frequency table, always label columns clearly: category, tally, frequency. This organises raw data into a neat summary. A useful mnemonic: ‘Tally Today, Frequency Final’ to remember the order.

创建频率表时，始终清晰地标记各列：类别、计数、频率。这就把原始数据整理成简洁的摘要。一个有用的记忆法：‘Tally Today, Frequency Final’（今天计数，频率最终）来记住顺序。

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5. Bar Charts, Pictograms and Pie Charts | 柱状图、象形图和饼图

Bar charts use rectangular bars to represent frequencies of categories. Bar heights are proportional to the values. In a dual bar chart, two sets of bars are placed side by side for comparison. A key feature: there are gaps between bars because categories are separate.

柱状图用矩形条来表示各类别的频率。条的高度与数值成比例。在双柱状图中，两组条并排放置以便比较。一个关键特征：条之间有间隔，因为类别是分开的。

Pictograms use pictures or symbols to show data. Each picture represents a certain number of items. Always check the key – one smiley face might equal 5 students! Pictograms make data visually engaging but can be tricky if the symbol has to be split for exact values.

象形图用图片或符号来表示数据。每个图片代表一定数量的项目。始终检查图例——一个笑脸可能等于5个学生！象形图让数据更具视觉吸引力，但如果需要拆分符号来表示精确值，就可能变得麻烦。

Pie charts display proportions of a whole. The full circle (360°) represents all the data. Each slice angle equals (category frequency ÷ total frequency) × 360°. A pie chart answers ‘what share of the whole does each part take?’

饼图显示整体的比例。整个圆（360°）代表所有数据。每个扇区的角度等于（类别频率 ÷ 总频率）× 360°。饼图回答“各部分占整体的份额是多少？”这个问题。

Quick memory: Bar for comparing amounts, Pictogram for fun pictures, Pie for parts of a whole.

快速记忆：柱状图比大小，象形图有趣图，饼图看部分。

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6. Line Graphs and Scatter Graphs | 线形图与散点图

A line graph is used to show continuous data changing over time. Dots are plotted and connected with straight lines, making trends easy to spot. The horizontal axis often shows time, while the vertical axis shows the measured variable. Remember: ‘Line Links Time’.

线形图用于显示连续数据随时间的变化。点被标出并用直线连接，便于发现趋势。横轴通常表示时间，纵轴表示测量变量。记住：‘Line Links Time’（线连接时间）。

A scatter graph (or scatter plot) compares two sets of continuous data to see if there is a relationship. Each dot represents one piece of data with an x-value and a y-value. If the dots go upward, there’s a positive correlation; downward shows a negative correlation; scattered randomly means no correlation.

散点图比较两组连续数据，看是否存在关系。每个点代表一个数据，具有x值和y值。如果点向上走，存在正相关；向下走体现负相关；随机散布则无相关。

In Year 8, you describe correlation as positive, negative or none; you don’t calculate exact strength. Just like ‘up together, down opposite’.

在八年级，你只需将相关性描述为正、负或无；不需要计算精确强度。就像是‘同增为正，一增一减为负’。

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7. Stem-and-Leaf Diagrams | 茎叶图

A stem-and-leaf diagram organises numerical data while keeping the original values visible. The ‘stem’ is the leading digit(s) and the ‘leaf’ is the final digit. For example, in the number 45, the stem is 4 and the leaf is 5. A key explains the place value, e.g., ‘4|5 means 45’.

茎叶图在保留原始值的同时组织数值数据。‘茎’是前导数字，‘叶’是最后一位数字。例如，数字45中，茎为4，叶为5。图例说明了位值，如‘4|5 表示 45’。

Stem-and-leaf plots make it easy to find the median (middle value) and mode (most frequent leaf). Always order the leaves from smallest to largest. A back-to-back stem-and-leaf diagram compares two related datasets by mirroring leaves either side of the stem.

茎叶图便于找到中位数（中间值）和众数（出现最频繁的叶）。始终将叶从小到大排列。背靠背茎叶图通过在茎的两侧对称排列叶子来比较两个相关的数据集。

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8. Mean, Median and Mode | 平均数：均值、中位数与众数

The three measures of central tendency help find a typical value in a dataset. Mean is the sum of all values divided by the number of values. The formula:

三种集中趋势量度帮助找到一个数据集中的典型值。均值是所有值的总和除以值的个数。公式：

Mean = (Sum of all values) ÷ (Number of values)

Median is the middle value when data is ordered. If there are two middle numbers, take their mean. Mode is the value that appears most often. A mnemonic: ‘Mean that shares, Median the middle, Mode the most.’

中位数是将数据排序后中间的值。如果有两个中间数，则取它们的均值。众数是出现频率最高的值。记忆口诀：‘均值求平均，中位数居中，众数看最多’。

When data is symmetric, mean ≈ median; if skewed, median is a better typical value. In a stem-and-leaf, find the median by crossing off equally from both ends.

当数据对称时

Published by TutorHao | Year 8 统计 Revision Series | aleveler.com

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