📚 Year 7 SQA Statistics: Interdisciplinary Problem-Solving Practice | 七年级 SQA 统计：跨学科综合题型训练
Statistics is not just about numbers in isolation. In Year 7 SQA courses, you will often see statistics combined with science experiments, geography surveys, health data, and even sports results. This article provides a series of interdisciplinary problem-solving tasks to help you apply your statistical skills in real-world contexts and prepare for the types of questions you might encounter in assessments.
统计学并不仅仅是孤立的数字。在七年级 SQA 课程中，你会经常看到统计与科学实验、地理调查、健康数据，甚至体育成绩结合在一起。本文提供一系列跨学科综合题型训练，帮助你在真实情境中运用统计技能，并为你在评估中可能遇到的题型做好准备。
1. Understanding the Role of Statistics Across Subjects | 理解统计在各学科中的作用
Every subject generates data. In Science, you record measurements like temperature or growth; in Geography, you compare population sizes or rainfall; in Health and Wellbeing, you collect survey responses about diet or sleep. A statistical toolkit – including averages, charts, and tables – helps you turn raw numbers into useful information. Recognising which tool to use in each context is the first step towards becoming a confident data handler.
每门学科都会产生数据。在科学中，你记录温度或生长等测量值；在地理中，你比较人口规模或降雨量；在健康与幸福课程中，你收集关于饮食或睡眠的调查回答。统计工具箱——包括平均数、图表和表格——能帮助你从原始数字中获得有用的信息。在每种情境中识别使用哪种工具，是成为自信数据处理者的第一步。
Look at this example: a geography teacher asks, ‘Which month had the highest rainfall in our town?’ To answer, you need to interpret a bar chart. A PE teacher says, ‘Find the typical long-jump distance in our class.’ That calls for the mean or median. Always think about what the question is really asking before you pick your statistical method.
看看这个例子：地理老师问“我们镇哪个月的降雨量最高？”要回答这个问题，你需要解读条形图。体育老师说“找出我们班跳远的典型距离。”这就要用到平均数或中位数。在你选择统计方法之前，始终想一想问题真正在问什么。
2. Collecting Data from Science Experiments | 从科学实验中收集数据
In a biology experiment, you measure the pulse rate (beats per minute) of five classmates before and after two minutes of stepping exercise. The results are recorded in a table. Creating a clear table is the foundation of good data analysis. Always include headings and units.
在一项生物实验中，你测量了五位同学在两分钟踏步练习前后的脉搏率（次/分钟）。结果记录在表格中。创建一个清晰的表格是良好数据分析的基础。始终要包含标题和单位。
| Student | Pulse Before (bpm) | Pulse After (bpm) |
| Anna | 68 | 108 |
| Ben | 70 | 115 |
| Chen | 75 | 110 |
| Dana | 72 | 105 |
| Eli | 74 | 112 |
Now, we want to find the mean increase in pulse rate. First, calculate each student’s increase: Anna 108 − 68 = 40, Ben 115 − 70 = 45, Chen 110 − 75 = 35, Dana 105 − 72 = 33, Eli 112 − 74 = 38. Next, add the increases: 40 + 45 + 35 + 33 + 38 = 191 bpm. Finally, divide by the number of students.
现在，我们想求脉搏率的平均增加。首先，计算每位学生的增加量：Anna 108 − 68 = 40，Ben 115 − 70 = 45，Chen 110 − 75 = 35，Dana 105 − 72 = 33，Eli 112 − 74 = 38。接着，把增加量加起来：40 + 45 + 35 + 33 + 38 = 191 bpm。最后，除以学生人数。
Mean increase = 191 ÷ 5 = 38.2 bpm
This tells us that, on average, the students’ pulse rates went up by 38.2 beats per minute after exercise. In your report, you would state the mean and perhaps compare it with the resting values. Science experiments often require you to present data in tables and calculate averages like this.
这告诉我们，这些学生的脉搏率在运动后平均每分钟增加了 38.2 次。在你的报告中，你要说明这个平均数，或许还要将其与静息值进行比较。科学实验常常要求你像这样用表格呈现数据并计算平均数。
3. Designing a Frequency Table for Geography Data | 为地理数据设计频率表
Imagine you are studying land use in a local area. A survey shows: Residential 50 hectares, Industrial 20 hectares, Green space 30 hectares, Commercial 10 hectares. To organise these, you can build a frequency table and add a percentage column.
想象一下你正在研究一个当地区域的土地利用。调查显示：住宅 50 公顷，工业 20 公顷，绿地 30 公顷，商业 10 公顷。为了整理这些数据，你可以构建一个频率表并添加百分比列。
First, calculate the total area: 50 + 20 + 30 + 10 = 110 hectares. Then work out each category’s percentage: Residential = (50 ÷ 110) × 100 ≈ 45.5%, Industrial ≈ 18.2%, Green space ≈ 27.3%, Commercial ≈ 9.1%. The table helps you see that residential use dominates, and green space is the second largest.
首先，计算总面积：50 + 20 + 30 + 10 = 110 公顷。然后算出每个类别的百分比：住宅 = (50 ÷ 110) × 100 ≈ 45.5%，工业 ≈ 18.2%，绿地 ≈ 27.3%，商业 ≈ 9.1%。这张表格帮助你看到住宅用途占主导，绿地是第二大。
This skill is directly transferable to Geography projects. You might be asked to draw a pie chart from such a table. Remember: a full pie chart represents 100%, so the residential slice would be about 45.5% of the circle. Always label each slice clearly.
这一技能可直接转移到地理项目中。你可能会被要求根据这样的表格绘制饼图。记住：整个饼图代表 100%，因此住宅部分的扇形约占圆圈的 45.5%。务必要清晰地标记每个扇形。
4. Using the Mean in Health and Wellbeing Surveys | 在健康调查中使用平均数
Health topics often rely on survey data. Suppose you ask five friends how many hours of sleep they got last night: 7, 8.5, 6, 7.5, 9 hours. To find the typical sleep duration, you can calculate the mean.
健康类话题常常依赖调查数据。假设你询问五位朋友昨晚睡了多长时间：7、8.5、6、7.5、9 小时。要找到典型的睡眠时长，你可以计算平均数。
Mean = (7 + 8.5 + 6 + 7.5 + 9) ÷ 5 = 38 ÷ 5 = 7.6 hours
However, the mean can be influenced by extreme values. If one person slept only 3 hours, the mean would drop noticeably. In such cases, the median might be a better measure of the ‘typical’ value. This is a key discussion point in Health and Wellbeing assignments: always ask whether the mean really represents the group.
然而，平均数可能会受极端值的影响。如果一个人只睡了 3 小时，平均数就会明显下降。在这种情况下，中位数可能是衡量“典型”值更好的度量。这是健康与幸福课程作业中的一个关键讨论点：始终要问一问平均数是否真正代表了该组数据。
You could also create a bar chart showing each friend’s sleep hours, with a horizontal line indicating the mean. This visual makes it easy to see who is above or below average. Health surveys often combine mean calculations with simple charts to communicate findings clearly.
你还可以创建一个条形图，显示每位朋友的睡眠时长，并用一条水平线标示平均数。这种视觉效果可以很容易看出谁高于或低于平均水平。健康调查常将平均数计算与简单图表结合起来，以清晰地传达结果。
5. Drawing and Reading Bar Charts in History | 历史中的条形图绘制与阅读
Even history topics can involve statistics. Imagine you are looking at population estimates for a town in different centuries: 1500 – 800 people, 1600 – 1200, 1700 – 2100, 1800 – 4500, 1900 – 8200. A bar chart is perfect for showing this growth over time.
即便是历史主题也会涉及统计。想象一下你正在查看一个城镇不同世纪的人口估计：1500 年 – 800 人，1600 年 – 1200 人，1700 年 – 2100 人，1800 年 – 4500 人，1900 年 – 8200 人。条形图非常适合展示这种随时间增长的情况。
When you draw the chart, put centuries on the horizontal axis and population on the vertical axis. Use a scale that goes up to 9000. Make sure all bars are of equal width and clearly separated. Then, you can answer questions like ‘Between which two centuries did the population increase the most?’ By reading the bar heights, you see the jump from 4500 to 8200 between 1800 and 1900 is the largest absolute increase.
当你绘制图表时，将世纪放在横轴，人口放在纵轴。使用最高到 9000 的刻度。确保所有条形宽度相等且清晰分开。然后，你可以回答诸如“哪两个世纪之间人口增长最多？”这样的问题。通过读取条形高度，你看到 1800 年到 1900 年间从 4500 增加到 8200，是最大的绝对增长。
History questions might also ask you to suggest reasons for the growth, linking the statistical evidence to events like the Industrial Revolution. Statistics thus supports your historical arguments.
历史问题还可能要求你提出增长的原因，将统计证据与工业革命等事件联系起来。因此，统计能支持你的历史论点。
6. Understanding Pie Charts in Economics and Budgeting | 理解经济学和预算中的饼图
In a basic economics task, you might analyse a family’s monthly budget. The data: Food 30%, Rent 25%, Transport 15%, Savings 20%, Entertainment 10%. A pie chart makes it easy to see the largest expense at a glance.
在基础经济学任务中，你可能会分析一个家庭的月度预算。数据：食品 30%，房租 25%，交通 15%，储蓄 20%，娱乐 10%。饼图能让你一眼看出最大的支出项。
Now, if the family’s total monthly income is £2400, how much money is spent on food? Use the percentage given. First, 30% of £2400 = 0.30 × 2400 = £720. Rent would be 25% of £2400 = £600. Often, questions require you to calculate actual amounts from percentages, a vital numeracy skill.
现在，如果该家庭每月总收入为 2400 英镑，食品支出是多少钱？使用给出的百分比。首先，£2400 的 30% = 0.30 × 2400 = £720。房租是 £2400 的 25% = £600。通常，题目会要求你从百分比计算具体金额，这是一项重要的计算技能。
You could also be asked to construct the pie chart. Each percentage translates to an angle: Food 30% of 360° = 108°, Rent 25% = 90°, Transport 15% = 54°, Savings 20% = 72°, Entertainment 10% = 36°. Always check that the angles sum to 360°. Interdisciplinary problems often combine percentage calculations, angle work, and real-life money contexts.
你还可能被要求绘制饼图。每个百分比对应一个角度：食品占 360° 的 30% = 108°，房租 25% = 90°，交通 15% = 54°，储蓄 20% = 72°，娱乐 10% = 36°。始终检查角度之和是否为 360°。跨学科问题常常将百分比计算、角度处理和现实中的金钱情境结合在一起。
7. Interpreting Line Graphs in Science Investigations | 解读科学探究中的折线图
A line graph is used to show continuous data, especially changes over time. In a science investigation, you record the temperature of a cooling liquid every two minutes. The data: 0 min − 80°C, 2 min − 72°C, 4 min − 65°C, 6 min − 59°C, 8 min − 54°C. Plot the points and connect them with line segments.
折线图用于展示连续数据，尤其是随时间的变化。在一项科学探究中，你每两分钟记录一次冷却液体的温度。数据：0 分钟 − 80°C，2 分钟 − 72°C，4 分钟 − 65°C，6 分钟 − 59°C，8 分钟 − 54°C。描点并用线段连接起来。
Once the graph is drawn, you can read key values: What was the temperature at 5 minutes? You might need to estimate – it sits between 65°C and 59°C, so around 62°C. You can also describe the trend: ‘The temperature decreased steadily over time.’ In an exam, you might be asked to predict the temperature at 10 minutes if the cooling pattern continues, testing your ability to extrapolate.
图表画好后，你可以读取关键值：5 分钟时的温度是多少？你可能需要进行估算——它位于 65°C 和 59°C 之间，所以大约为 62°C。你还可以描述趋势：“温度随时间的推移稳定下降。”在考试中，你可能会被问到如果冷却模式持续，10 分钟时的温度会是多少，这测试你的外推能力。
Science line graphs always need labelled axes (Time in minutes, Temperature in °C) and a title. This careful presentation is part of your statistical communication.
科学折线图始终需要带标签的坐标轴（时间/分钟，温度/°C）和标题。这种严谨的呈现方式是你统计交流的一部分。
8. Finding the Median and Mode in Sports Analytics | 体育分析中找中位数和众数
In PE, you could analyse the number of goals scored by a football team in their last 9 matches: 2, 0, 3, 1, 2, 4, 2, 1, 2. The mode is the most frequent value – here it is 2, because it appears four times. The median is the middle number once the data is ordered.
在体育中，你可以分析一支足球队过去 9 场比赛的进球数：2, 0, 3, 1, 2, 4, 2, 1, 2。众数是最频繁出现的值——这里是 2，因为出现了四次。中位数是将数据排序后中间的那个数。
First, order the data from smallest to largest: 0, 1, 1, 2, 2, 2, 2, 3, 4. With 9 values, the median is the 5th value, which is 2. So here the mean, median, and mode would all be close to 2, indicating a consistent performance. In sports, these measures help coaches assess whether a team tends to score low (skewed data) or has an extremely high-scoring match that pulls the mean up.
首先，将数据从小到大排序：0, 1, 1, 2, 2, 2, 2, 3, 4。有 9 个数据，中位数是第 5 个，即 2。因此在这里，平均数、中位数和众数都很接近 2，表明表现稳定。在体育中，这些衡量指标帮助教练评估球队是否通常得分较低（数据偏斜），还是有一场极高得分的比赛拉高了平均数。
Task: Calculate the mean for this dataset and compare it with the median. Is the mean affected by the 4?
任务：计算该数据集的平均数并与中位数比较。平均数是否受 4 的影响？
Sum = 0+1+1+2+2+2+2+3+4 = 17. Mean = 17 ÷ 9 ≈ 1.89. The mean (1.89) is slightly lower than the median (2) because of the low values 0 and 1. Comparing these statistics gives much richer insight than just one number.
总和 = 0+1+1+2+2+2+2+3+4 = 17。平均数 = 17 ÷ 9 ≈ 1.89。平均数（1.89）略低于中位数（2），因为存在 0 和 1 这样较低的值。比较这些统计量能提供比单个数字丰富得多的洞察。
9. Interpreting Mixed Charts in Cross-Curricular Projects | 解读跨学科项目中的混合图表
Sometimes a single task combines two types of charts. Consider a project linking Science and Geography: you are given a table of monthly average temperature and rainfall for a city, and you must create a climate graph. This involves drawing a line graph for temperature on one vertical axis and a bar chart for rainfall on the other, with months on the horizontal axis.
有时一项任务会结合两种图表类型。考虑一个连接科学与地理的项目：你拿到一张城市月平均气温和降雨量的表格，你需要创建一个气候图表。这涉及到在一个纵轴上为温度绘制折线图，在另一个纵轴上为降雨量绘制条形图，横轴为月份。
For example: Jan temp 5°C, rain 70 mm; Feb temp 6°C, rain 60 mm; Mar temp 9°C, rain 55 mm, etc. After drawing, answer questions like: ‘Which month is warmest and driest?’ You need to read both temperature and rainfall axes, combining information from the line and the bars. This type of question appears in many SQA interdisciplinary assessments.
例如：一月温度 5°C，降雨 70 毫米；二月温度 6°C，降雨 60 毫米；三月温度 9°C，降雨 55 毫米，等等。画好图表后，回答诸如“哪个月最热且最干燥？”这样的问题。你需要同时读取温度和降雨量轴，把来自折线和条形的信息结合起来。这类问题出现在许多 SQA 的跨学科评估中。
Practice by interpreting a given mixed chart first. Check the scales carefully – sometimes temperature is on the left, rainfall on the right, and they use different units. A common mistake is to read the wrong axis.
先通过解读给出的混合图表来练习。仔细检查刻度——有时温度在左边，降雨量在右边，它们使用不同的单位。一个常见的错误是读错了轴。
10. Putting It All Together: A Cross-Curricular Challenge | 综合挑战：跨学科综合任务
Here is a realistic task that combines several skills. Imagine you are investigating how physical activity affects concentration. You ask 6 volunteers to rate their concentration level on a scale from 1 to 10 after sitting still for 30 minutes, and then again after a 10-minute jog. The scores: Still: 5, 6, 4, 7, 6, 5; After jog: 8, 9, 7, 8, 10, 8. Your job is to: a) produce a dual bar chart comparing the two sets, b) calculate the mean and range for each set, and c) write a short conclusion using the statistics.
这是一个结合了多项技能的真实任务。想象你正在研究体育活动如何影响注意力。你请 6 位志愿者在静坐 30 分钟后，对自己的注意力水平从 1 到 10 进行评分；然后在慢跑 10 分钟后再次评分。分数如下：静坐时：5, 6, 4, 7, 6, 5；慢跑后：8, 9, 7, 8, 10, 8。你的任务是：a) 制作一个双重条形图，比较两组数据；b) 计算每组数据的平均数和全距；c) 运用统计量撰写一个简短的结论。
First, the means: Still set = (5+6+4+7+6+5) ÷ 6 = 33 ÷ 6 = 5.5. Jog set = (8+9+7+8+10+8) ÷ 6 = 50 ÷ 6 ≈ 8.33. The ranges: Still range = 7 − 4
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