📚 Year 7 WJEC Statistics: Key Points for Experimental and Practical Assessment | Year 7 WJEC 统计：实验/实践考核要点
In Year 7 WJEC Statistics, the experimental and practical assessment is not just about crunching numbers—it is about showing you can think like a statistician. You will be asked to design simple investigations, collect data carefully, present your findings clearly, and draw sensible conclusions. This article walks through the key points that examiners expect to see in your practical work, from planning an investigation to evaluating your results.
在 Year 7 WJEC 统计课程中，实验和实践考核不只是计算数字，而是展示你能否像统计学家一样思考。你需要设计简单的调查、仔细收集数据、清晰地展示你的发现，并得出合理的结论。本文梳理了考官在你的实践作业中期望看到的关键要点，从规划调查到评估结果逐一说明。
1. Understanding the Purpose of Practical Work | 理解实践工作的目的
Practical tasks in statistics give you a chance to apply what you have learned in the classroom to real-life situations. Instead of just answering textbook questions, you will be designing your own mini-investigations, making decisions about what data to collect, and interpreting the meaning behind the numbers.
统计实践任务让你有机会将课堂所学应用到现实生活中。你不是只回答教科书上的问题，而是设计自己的小型调查，决定收集哪些数据，并解读数字背后的含义。
The examiner wants to see that you understand why you are doing each step, not just that you can follow instructions. Every choice you make—from the type of data you collect to the chart you draw—should have a clear reason behind it.
考官希望看到你理解每一步操作的原因，而不仅仅是会按照指令执行。你做的每一个选择——从收集的数据类型到绘制的图表——都应该有明确的理由。
Practical assessments also test important skills like organisation, accuracy, and communication. You need to show that you can work systematically, keep your data tidy, and explain your methods clearly enough for someone else to follow.
实践考核还测试组织能力、准确性和沟通能力等重要技能。你需要展示自己能有条理地工作、保持数据整洁，并清晰解释你的方法，让他人也能够理解。
2. Planning Your Investigation | 规划你的调查
Every good investigation starts with a clear question. Your question should be specific enough that you know exactly what to measure, but broad enough to produce interesting results. For example, ‘Do boys in our class have bigger hand spans than girls?’ is a clear, testable question.
每项好的调查都从一个清晰的问题开始。你的问题应该足够具体，让你确切知道要测量什么，但也要足够广泛，能产生有趣的结果。例如，‘我们班男生的手掌跨度比女生大吗？’就是一个清晰、可测试的问题。
Once you have a question, you need to write a hypothesis. A hypothesis is a prediction about what you think you will find. It does not matter if your hypothesis turns out to be wrong—what matters is that you have thought about what might happen and can test it.
一旦确定了问题，你需要写出一个假设。假设是对你认为会发现什么的预测。假设最终被证明是错的也没关系——重要的是你思考过可能发生的情况，并且能够进行检验。
Your plan should also describe what data you will collect, how you will collect it, and what equipment you might need. Make sure you consider whether your data will be discrete or continuous, as this will affect the types of charts you can use later.
你的计划还应说明你将收集什么数据、如何收集以及可能需要哪些工具。确保你考虑数据是离散的还是连续的，因为这将影响你稍后可以使用的图表类型。
3. Collecting Data Fairly and Accurately | 公平准确地收集数据
Fair data collection is one of the most important principles in statistics. You must avoid bias by giving every member of your target group an equal chance of being included. If you only ask your friends, your results will not represent the whole class or year group.
公平收集数据是统计学中最重要的原则之一。你必须避免偏差，让目标群体中的每个成员都有平等的机会被纳入。如果你只问你的朋友，你的结果就不能代表整个班级或年级。
Accuracy matters just as much as fairness. If you are measuring hand spans, make sure everyone uses the same ruler and follows the same procedure. Small errors can add up and affect your conclusions.
准确性和公平性同样重要。如果你在测量手掌跨度，确保每个人都使用同样的尺子并遵循相同的步骤。小错误可能会累积起来，影响你的结论。
Think about sample size too. A sample that is too small might give misleading results. While you cannot always survey hundreds of people in a classroom investigation, try to include as many data points as is practical to make your findings more reliable.
还要考虑样本量。太小的样本可能会产生误导性的结果。虽然在课堂调查中你不可能总是调查数百人，但尽量包含尽可能多的数据点，使你的发现更加可靠。
4. Types of Data: Discrete and Continuous | 数据类型：离散与连续
Understanding the difference between discrete and continuous data is fundamental. Discrete data can only take certain values, usually whole numbers—like the number of siblings someone has or the score on a dice. Continuous data can take any value within a range, like height, weight, or time.
理解离散数据与连续数据的区别是基础。离散数据只能取特定的值，通常是整数——比如某人的兄弟姐妹数量或掷骰子的点数。连续数据可以取某个范围内的任何值，比如身高、体重或时间。
Identifying your data type correctly matters because it determines how you organise and display your data. Discrete data often works well in bar charts and pictograms, while continuous data usually needs grouped frequency tables and histograms.
正确识别数据类型很重要，因为它决定了你如何组织和展示数据。离散数据通常适合用条形图和象形图表示，而连续数据通常需要分组频数表和直方图。
In practical assessments, examiners often check that you have chosen appropriate methods for the type of data you collected. Getting this right shows that you understand the theory behind the practice.
在实践考核中，考官经常会检查你是否为所收集的数据类型选择了合适的方法。做对这一点表明你理解了实践背后的理论。
5. Organising Data with Tally Charts and Frequency Tables | 用记数表和频数表整理数据
Before you can do anything useful with raw data, you need to organise it. Tally charts are a simple and effective way to record data as you collect it. Each tally mark represents one observation, and grouping them in fives makes counting totals quick and accurate.
在你能对原始数据做任何有用的处理之前，你需要整理数据。记数表是在收集数据时记录数据的一种简单有效的方法。每条记数线代表一个观测值，五个一组的方式可以使计数快速且准确。
A frequency table takes the tally chart a step further by presenting the totals in a clear, structured format. For discrete data, your frequency table should have a column for each possible value and its frequency. For continuous data, you will need to group the data into class intervals.
频数表通过以清晰、结构化的格式呈现总数，让记数表更进一步。对于离散数据，你的频数表应该有一列列出每个可能的值及其频数。对于连续数据，你需要将数据分组到组距中。
Always double-check that the sum of your frequencies matches the total number of data points you collected. A mismatch is a clear sign of a recording error and will lose you marks in an assessment.
始终仔细检查频数总和是否与你收集的数据点总数一致。不一致是明显的记录错误迹象，会在考核中失分。
6. Choosing and Drawing the Right Chart | 选择并绘制正确的图表
Different types of data and different investigation questions call for different charts. Bar charts are excellent for comparing the frequencies of discrete categories. Pictograms make data visually engaging and are especially good for younger audiences. Pie charts show proportions clearly, but only when you have a small number of categories.
不同数据类型和不同的调查问题需要不同的图表。条形图非常适合比较离散类别的频数。象形图让数据在视觉上引人入胜，特别适合低龄受众。饼图能清楚地显示比例，但仅适用于类别数量较少的情况。
For continuous data, you will often use histograms, where the area of each bar represents frequency. Line graphs are useful for showing changes over time, and scatter graphs help you explore relationships between two sets of data.
对于连续数据，你通常会使用直方图，其中每个条形的面积代表频数。折线图适合显示随时间的变化，散点图帮助你探索两组数据之间的关系。
Whichever chart you choose, label your axes clearly, give your chart a descriptive title, and make sure your scale is consistent. Omitting labels is one of the most common mistakes in practical assessments.
无论你选择哪种图表，都要清楚地标注坐标轴，给图表一个描述性的标题，并确保刻度一致。遗漏标签是实践考核中最常见的错误之一。
7. Averages and Measures of Central Tendency | 平均数与集中趋势的度量
The three main measures of average are the mode, median, and mean. Each one tells you something different about your data, and knowing when to use which one is a key skill. The mode is the most frequent value—quick to find and useful for non-numerical data too.
三种主要的平均数度量是众数、中位数和均数。每种度量告诉你数据中不同的信息，知道何时使用哪一种是一项关键技能。众数是最常出现的值——找到它很快，对非数值数据也很有用。
The median is the middle value when data is ordered. It is not affected by extreme values, which makes it a better choice than the mean when your data includes outliers. For example, if one person in your class is much taller than everyone else, the median height gives a better sense of the typical height.
中位数是数据排序后的中间值。它不受极值影响，这使它在数据包含异常值时比均数更好的选择。例如，如果班里有一个人的身高比其他人都高得多，身高中位数更能体现典型身高。
The mean is what most people think of as the average—add all the values and divide by how many there are. It uses every piece of data, which is both its strength and its weakness. Show your working clearly when calculating the mean, as method marks are often awarded even if the final answer is slightly off.
均数是大多数人所说的平均数——把所有数值加起来再除以个数。它使用了每一个数据，这既是它的优点也是缺点。计算均数时要清楚地展示你的计算过程，因为即使最终答案略有偏差，也常常能获得方法分。
8. Understanding Spread: Range | 理解离散程度：极差
The range is the simplest measure of spread and is calculated by subtracting the smallest value from the largest value. It tells you how spread out your data is. A small range means the data is fairly consistent, while a large range shows more variation.
极差是最简单的离散度量，通过最大值减去最小值来计算。它告诉你数据的分散程度。极差小意味着数据相当一致，而极差大则表示变动更大。
Always identify the highest and lowest values in your dataset before calculating the range. Write them down clearly so the examiner can follow your logic. A common mistake is to include a zero that is not actually in the data—for instance, thinking the minimum is zero when you have not collected any zeros.
在计算极差之前，始终先找出数据集中的最大值和最小值。清楚地写下来，以便考官能跟上你的逻辑。一个常见错误是包含一个实际上不在数据中的零——例如，在你没有收集到任何零的情况下，认为最小值是零。
The range is a useful starting point for describing variation, but it does not give the full picture because it only considers the two extreme values. In Year 7, you should be comfortable calculating and interpreting the range alongside measures of average.
极差是描述变动情况的一个有用的起点，但它并不能给出全貌，因为它只考虑了两个极端值。在 Year 7，你应该能熟练计算和解释极差，并结合平均数的度量。
9. Practical Probability Experiments | 实践概率实验
Probability experiments are a big part of practical statistics. You might toss coins, roll dice, or spin spinners to see how often different outcomes occur. The key idea is to compare your experimental probability with the theoretical probability you can work out from equally likely outcomes.
概率实验是实践统计的重要组成部分。你可能会抛硬币、掷骰子或旋转转盘，看看不同结果发生的频率。关键是将你的实验概率与从等可能结果中得出的理论概率进行比较。
For a fair coin, the theoretical probability of heads is ½. But if you toss a coin ten times, you might not get exactly five heads. That is normal—experimental results approach theoretical probability as the number of trials increases. This is called the law of large numbers.
对于一枚公平的硬币，正面的理论概率是½。但如果你抛硬币十次，可能不会恰好得到五次正面。这很正常——随着试验次数的增加，实验结果会趋近于理论概率。这被称为大数定律。
Record your results carefully in a frequency table and use them to calculate relative frequency. The relative frequency of an outcome is the number of times it occurs divided by the total number of trials. Express it as a fraction, decimal, or percentage.
在频数表中仔细记录你的结果，并用它们计算相对频率。一个结果的相对频率是它发生的次数除以试验总次数。用分数、小数或百分比来表示它。
10. Writing Conclusions and Evaluating Your Findings | 撰写结论并评估你的发现
Your conclusion should refer back to your original question and hypothesis. Say clearly whether your data supports your hypothesis or not. You do not need to be right—you need to be honest and thoughtful about what your data actually shows.
你的结论应该回扣你最初的问题和假设。清楚地说明你的数据是否支持你的假设。你不需要是对的——你需要诚实且深思熟虑地对待你的数据实际显示的内容。
Support your conclusion with specific numbers from your analysis. Instead of saying ‘boys are taller’, say ‘the median height for boys was 148 cm compared to 145 cm for girls, which suggests a small difference’. Using precise figures adds credibility to your work.
用分析中的具体数字来支持你的结论。与其说‘男生更高’，不如说‘男生的中位身高为 148 厘米，而女生为 145 厘米，这表明存在细微差异’。使用精确的数字增强了你的作业的可信度。
Evaluation is about looking critically at your own work. Ask yourself: was my sample size large enough? Did I control for all the variables? Were there any sources of bias or error? Identifying weaknesses honestly shows the examiner that you understand the limitations of practical work.
评估是批判性地审视自己的工作。问问自己：我的样本量够大吗？我控制所有变量了吗？是否存在任何偏差或误差来源？诚实地找出不足向考官表明你理解实践工作的局限性。
11. Presenting Your Work Clearly | 清晰地展示你的作业
Good presentation matters in practical assessments. Use headings to separate sections, keep your tables and charts neatly drawn with a ruler, and write in full sentences when explaining your thinking. Messy or disorganised work makes it hard for the examiner to follow your reasoning.
良好的展示在实践考核中很重要。使用标题分隔各部分，用尺子整齐地绘制表格和图表，并在解释你的思路时使用完整的句子。杂乱或无条理的作业使考官难以理解你的推理。
Every chart and table should be clearly labelled and referenced in your writing. Do not just stick a bar chart in the middle of your report without explaining what it shows and why you included it.
每个图表和表格都应有清晰的标签，并在文字中被引用。不要只是在报告中间插入一个条形图，而不解释它显示什么以及为什么包含它。
If you are using a spreadsheet or online tool to generate charts, make sure you still understand how they were created. Being able to draw a chart by hand is a skill you will be tested on, so practise both methods during your revision.
如果你使用电子表格或在线工具生成图表，确保你仍然理解它们是如何创建的。能手工绘制图表是一项你会被测试的技能，所以在复习时两种方法都要练习。
12. Common Pitfalls and How to Avoid Them | 常见陷阱及如何避免
One common pitfall is confusing the mode, median, and mean. Practise calculating each one on small datasets until you can do so without mixing them up. Remember that the mean is the only one that involves adding and dividing, and it can produce values that are not in the original data.
一个常见的陷阱是混淆众数、中位数和均数。在小数据集上练习计算每一种，直到你能不混淆为止。记住均数是唯一涉及加法和除法的，它可以产生不在原始数据中的数值。
Another frequent error is drawing the wrong chart for the data type. A pie chart showing thirty different categories is unreadable. A line graph plotting discrete categories is misleading. Always pause before you start drawing and check whether your chart choice makes sense.
另一个常见错误是为数据类型绘制了错误的图表。显示三十个不同类别的饼图是不可读的。用折线图绘制离散类别是误导性的。在开始绘图之前，总是停下来检查你的图表选择是否合理。
Many students lose marks by not reading the assessment rubric carefully. If the task asks you to compare two groups, make sure you actually compare them—do not just describe each group separately. Use words like ‘higher than’, ‘lower than’, and ‘similar to’ in your comparisons.
许多学生因没有仔细阅读评估标准而失分。如果任务要求你比较两个组，确保你真的进行比较——不要只是分别描述每个组。在比较时使用‘高于’、‘低于’和‘类似于’这样的词。
Published by TutorHao | WJEC Statistics Revision Series | aleveler.com
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