📚 Year 7 CIE Statistics: Experiment and Practical Assessment Key Points | Year 7 CIE 统计：实验/实践考核要点
In CIE Year 7 Statistics, the experiment and practical assessment component is designed to evaluate your ability to apply statistical methods to real-world situations. Instead of simply recalling definitions, you will be expected to plan an investigation, collect and organise data, display it appropriately, perform calculations, and draw sensible conclusions. The following guide outlines the essential points that examiners look for, helping you to avoid common mistakes and achieve a high mark.
在 CIE 七年级统计课程中，实验与实践考核部分旨在评估你将统计方法应用于实际情境的能力。你不仅需要记住定义，更要学会规划调查、收集整理数据、用合适的方式展示数据、进行计算，并得出合理的结论。以下指南梳理了考官关注的核心要点，能帮助你避开常见错误，拿到理想分数。
1. Understanding the Practical Assessment Criteria | 理解实践考核标准
Your practical work will be judged against several key criteria: planning, data collection, processing and presentation, analysis, and evaluation. Each stage carries marks, so you must demonstrate skills in all areas, not just the final graph or conclusion.
实践作业会从几个关键标准来评分：规划、数据收集、处理与展示、分析以及评价。每个环节都占分，因此你需要展示出每一方面的技能，而不能只靠最后的图表或结论。
Read the task instructions carefully and identify exactly what you are being asked to investigate. If the question asks you to compare two groups or look for a relationship, your entire plan should be built around that aim.
仔细阅读任务说明，明确你需要调查什么问题。如果题目要求比较两组数据或探究某种关系，你的整个计划就必须围绕这一目标展开。
2. Planning Your Investigation | 规划你的调查
Start by writing a clear hypothesis or research question. For example, ‘Year 7 boys spend more time on outdoor sports than Year 7 girls’ is a hypothesis you can test with data.
首先写下清晰的假设或研究问题。例如，“七年级男生花在户外运动上的时间比女生多”就是一个可以用数据检验的假设。
Identify what data you need to collect, whether it is categorical (e.g. favourite subject) or numerical (e.g. height in cm). Decide if you will use primary data (collected by you) or secondary data (from books, websites or provided by the teacher).
确定需要收集的数据类型，是分类数据（如最喜爱的科目）还是数值数据（如身高，单位厘米）。决定使用一手数据（自己收集）还是二手数据（来自书籍、网站或教师提供）。
Plan the sample size and method. For a fair investigation, you should describe how you will select participants randomly or systematically to avoid bias. Always state your plan before you begin collecting data.
规划样本量和抽样方法。为了保证调查公平，你需要说明如何随机或系统地选择参与者，避免偏见。务必在开始收集数据之前先陈述计划。
3. Designing Data Collection Tools | 设计数据收集工具
Design a data collection sheet or a simple questionnaire that is easy to record. Your recording table should have clear headings, units where necessary, and a tally column for organising data as you go.
设计一份便于记录的数据收集单或简单问卷。记录表应有清晰的标题、必要的单位，并留出画“正”字计数的栏目，便于边收集边整理。
Make sure your questions are unambiguous. For instance, instead of asking ‘How much do you exercise?’, ask ‘How many minutes did you exercise yesterday?’ This helps collect consistent numerical data.
确保问题没有歧义。例如，不要问“你运动多吗？”，而应问“昨天你运动了多少分钟？”，这有助于收集一致的数值数据。
In practice assessments, you often need to include a frequency table with columns for the data value, tally and frequency. Preparing this ahead of time saves time and reduces mistakes during the experiment.
在实践考核中，通常需要准备一个包含数据值、划记和频数的频数表。提前画好这类表格能节省时间，减少实验时的错误。
4. Gathering Data Responsibly | 负责任地收集数据
When conducting experiments or surveys, always follow ethical guidelines. Ask for permission, keep responses anonymous, and do not pressure anyone to take part. In a classroom setting, your classmates and teachers are usually the source of data.
进行实验或调查时，始终遵守道德准则。要征得同意，对回答进行匿名处理，不强迫任何人参与。在课堂上，同学和老师通常是数据的来源。
Record raw data immediately and accurately. If you are measuring lengths or times, use suitable instruments and note the units. Record every reading carefully, even if it seems unusual – never ignore an outlier without a good reason.
立即、准确地记录原始数据。测量长度或时间时，使用合适的工具并标注单位。仔细记录每一个读数，即便它看起来不寻常——没有充分理由绝不要忽视异常值。
If you are using secondary data, always note the source and check its reliability. Data from a reputable government website is more reliable than data from an unverified personal blog.
如果使用二手数据，一定要记录来源并检查其可靠性。来自可信政府网站的数据比未经核实的个人博客数据更可靠。
5. Organising Data into Tables | 将数据整理成表格
Once collected, data should be organised into a clear frequency table. This makes patterns easier to spot and prepares the data for graphing. A typical frequency table might look like this:
数据收集完毕后，应整理成清晰的频数表。这会让规律更容易被发现，也为绘制图表做好准备。一个典型的频数表可能如下所示：
| Number of books read last month | Tally | Frequency |
|---|---|---|
| 0-2 | IIII | 4 |
| 3-5 | IIII II | 7 |
| 6-8 | III | 3 |
| 9 or more | I | 1 |
Grouping numerical data into class intervals (like 0–2, 3–5) helps when you have a wide range of values. Always check that the intervals are equal in size and do not overlap.
把数值数据分组到区间里（如 0–2、3–5）有助于处理取值范围较广的情况。要始终检查区间宽度是否相等且不重叠。
For categorical data, simply list the categories and their frequencies. Include a total row to confirm you haven’t missed any responses. A well-organised table immediately earns marks for presentation.
对于分类数据，可以直接列出类别及其频数。加上合计行以确认没有遗漏任何回答。一张整理清楚的表格能立刻赢得展示分。
6. Creating Appropriate Graphs and Charts | 创建合适的图表
Choosing the right chart is crucial. Use a bar chart for categorical data or discrete numerical data – the bars should not touch. For continuous data or to show trends over time, a line graph is more suitable.
选择合适的图表至关重要。分类数据或离散数值数据应使用条形图，条形之间要留空隙。对于连续数据或要展示随时间变化的趋势，折线图更为合适。
A pie chart works well when you want to show proportions of a whole. Before drawing, calculate the angle for each sector using the formula: Angle = (Frequency ÷ Total frequency) × 360°. Always label sectors clearly or provide a key.
要展示部分与整体的比例时，饼图是很好的选择。绘制前，用公式 角度 = (频数 ÷ 总频数) × 360° 计算出每个扇形的角度。务必给各扇形加上清晰标签或图例。
All graphs must have a title, labelled axes (with units if applicable) and a consistent scale. In an exam practical, neatness counts – use a ruler for straight lines and a compass for pie charts.
所有图表都必须有标题、标好坐标轴（必要时带单位）以及一致的刻度。在考试实践中，整洁度很重要——画直线要用尺子，画饼图要用圆规。
7. Calculating Measures of Central Tendency and Spread | 计算集中趋势与离散程度的度量
You are expected to find the mean, median, mode and range of a data set by hand or using a calculator. For the mean, use:
你需要用手工或计算器求出一组数据的平均数、中位数、众数和极差。计算平均数时使用：
Mean = Sum of all data values ÷ Number of values
The median is the middle value when data are ordered. If there are two middle numbers, the median is their average. The mode is the value that appears most often.
中位数是数据排序后居于中间位置的数值。如果有两个中间数，中位数就是它们的平均值。众数是出现次数最多的数值。
Range is a simple measure of spread: Range = Highest value – Lowest value. Always state the range along with the averages to give a better picture of the data’s variability.
极差是一种简单的离散度量：极差 = 最大值 – 最小值。在给出平均数的同时，务必报告极差，以便更好地了解数据的波动情况。
In your practical write-up, show all steps of your calculations clearly. Even if your final answer is wrong, you can still earn marks for a correct method.
在实践报告中，要清晰展示所有计算步骤。即便最终答案错了，正确的计算方法仍能为你赢得步骤分。
8. Performing Probability Experiments | 进行概率实验
Probability experiments help you understand chance. A classic experiment is tossing a fair coin 50 times and recording the number of heads and tails. You can then calculate the experimental probability:
概率实验有助于理解随机性。经典的实验是抛掷一枚均匀硬币 50 次，记录正面和反面的次数，然后计算实验概率：
Experimental Probability = Number of times the event occurs ÷ Total number of trials
For example, if you get 23 heads in 50 tosses, the experimental probability of heads is 23/50 = 0.46. Compare this with the theoretical probability of 0.5 to discuss how randomness causes variation in short experiments.
例如，若 50 次抛掷中出现 23 次正面，则正面的实验概率为 23/50 = 0.46。将其与理论概率 0.5 对比，可以讨论在少量试验中随机性如何导致偏差。
Use a tally chart to record outcomes as you go. In a practical assessment, you might be asked to repeat the experiment several times to demonstrate that results tend towards the theoretical probability as the number of trials increases (the law of large numbers).
一边实验一边用划记表记录结果。在实践考核中，你可能被要求重复实验多次，以展示随着试验次数增加，结果会趋向理论概率（大数定律）。
9. Interpreting and Analysing Your Findings | 解释和分析你的发现
After presenting your graphs and calculations, you must write about what the data shows. Look for patterns, trends or comparisons between groups. For instance, ‘The median screen time for Year 7 students is 2.5 hours, and the range is 4 hours, showing considerable variation.’
展示完图表和计算后，你必须写出数据说明了什么。寻找规律、趋势或组间对比。例如，“七年级学生屏幕使用时间的中位数为 2.5 小时，极差为 4 小时，表明差异较大。”
Use numbers from your analysis to support each statement. Avoid vague comments like ‘most people like football’. Instead, say ’12 out of 30 students chose football as their favourite sport, which is 40% of the sample.’
用分析得出的数字来支撑每一条陈述。避免模糊的评论，如“大多数人喜欢足球”。应该说“30 名学生中有 12 人选择足球作为最喜爱的运动，占样本的 40%”。
Link your findings back to your original hypothesis. State whether the evidence supports it or not, and suggest possible reasons for the outcome. This shows higher-level thinking and is often rewarded with evaluation marks.
将发现与最初的假设联系起来。说明证据是否支持假设，并推测导致该结果的可能原因。这能展现高阶思维能力，通常能拿到评价分。
10. Evaluating and Reflecting on Your Work | 评估和反思你的工作
No investigation is perfect. In your evaluation, discuss limitations such as a small sample size, potential bias in how participants were selected, or difficulties in measuring accurately. Suggest how you would improve the investigation if you did it again.
任何调查都无法做到完美。在评估中，要讨论局限性，例如样本量较小、参与者选取方式可能带来的偏见，或测量精确度方面的困难。提出如果再做一次，你会如何改进。
For example, ‘If I repeated this experiment, I would increase the sample size to 100 students and use a random number generator to select names from the register to reduce sampling bias.’
例如，“如果重做这个实验，我会把样本量增加到 100 名学生，并使用随机数生成器从名册中选名字，以减少抽样偏差。”
Also, reflect on any problems you encountered during data collection, like missing responses or unclear survey questions, and explain how you addressed them. This honest reflection demonstrates a mature approach to statistical investigation.
同时，反思数据收集中遇到的任何问题，如回答缺失或调查问题不清晰，并解释你是如何处理的。这种诚实的反思展现了统计探究中的成熟思考。
Published by TutorHao | Statistics Revision Series | aleveler.com
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