📚 Year 10 SQA Statistics: Key Points for Experimental and Practical Assessments | SQA 统计学 Year 10：实验与实践考核要点
Practical investigations are at the heart of SQA Statistics. In Year 10, your ability to design a fair experiment, collect data correctly and interpret findings will be assessed through coursework or controlled assignments. This guide breaks down the essential skills examiners look for, from writing a clear hypothesis to presenting your data in charts and concluding with confidence.
实践调查是 SQA 统计课程的核心。在 Year 10，你设计公平实验、正确收集数据并解释结果的能力将通过课程作业或受控作业进行评估。本指南拆解了考官寻找的关键技能，从撰写清晰的假设到用图表展示数据并自信地得出结论。
1. Formulating a Research Question and Hypothesis | 制定研究问题与假设
Always start with a clear, focused question. Avoid vague topics like ‘Do people like sport?’. Instead, narrow it down: ‘Is there a relationship between hours of weekly exercise and resting heart rate in S4 pupils?’ This gives you a measurable outcome.
始终从一个清晰、聚焦的问题开始。避免模糊的话题，如“人们喜欢运动吗？”。应当缩小范围：“S4 学生每周锻炼的小时数与静息心率之间是否存在关系？”这样你就有了可测量的结果。
A hypothesis predicts what you think will happen. It should be testable and often follows the format: ‘There will be a positive correlation between X and Y’ or ‘Group A will have a higher mean than Group B’. Avoid stating it as a fact; use words like ‘will be’ or ‘is likely to’.
假设预测你认为会发生什么。它应当可检验，通常采用以下格式：“X 与 Y 之间将存在正相关”或“A 组的平均值将高于 B 组”。不要陈述为事实；使用“将”或“很可能”等措辞。
In SQA assessments, you may be asked to write null and alternative hypotheses for statistical tests. For a correlation, the null hypothesis might be ‘ρ = 0’ (no correlation) and the alternative ‘ρ ≠ 0’ (some correlation). Keep these precise.
在 SQA 评估中，你可能会被要求为统计检验撰写零假设和备择假设。对于相关性，零假设可能是“ρ = 0”（无相关），备择假设是“ρ ≠ 0”（存在相关）。要保持精确。
2. Understanding Populations and Samples | 理解总体与样本
The population is the entire group you want to draw conclusions about – for instance, all Year 10 students in your school. The sample is the smaller subset you actually measure or survey. You must define both clearly in your report.
总体是你想要得出结论的整个群体——例如，你所在学校的所有 Year 10 学生。样本是你实际测量或调查的较小子集。你必须在报告中清楚地定义两者。
A common pitfall is using a sample that is too small or biased. Even if you collect data from 30 pupils, explain why this sample size is manageable but still representative enough to make reasonable inferences.
一个常见的陷阱是使用了过小或存在偏差的样本。即使你从 30 名学生那里收集数据，也要解释为什么这个样本量是可操作的，同时仍具有足够的代表性以做出合理的推断。
Always state the sampling frame – the list from which you draw your sample. It might be the school register for S4. A clear sampling frame helps others replicate your study.
始终要说明抽样框——你从中抽取样本的名单。它可能是 S4 的学生花名册。清晰的抽样框有助于他人重复你的研究。
3. Sampling Methods and Avoiding Bias | 抽样方法与避免偏差
For practical assessments, you need to justify your choice of sampling method. Simple random sampling gives every member an equal chance and is the gold standard for avoiding bias. You might use a random number generator to select pupils from a list.
对于实践考核，你需要证明你抽样方法选择的合理性。简单随机抽样使每个成员有均等的机会，是避免偏差的黄金标准。你可以使用随机数生成器从名单中选取学生。
Stratified sampling divides the population into groups (strata) and samples proportionally from each. This is excellent if you suspect a characteristic like gender or year group could affect your results. For example, if your school has 60% boys and 40% girls, your sample should mirror that.
分层抽样将总体分成若干组（层）并从每组中按比例抽样。如果你怀疑性别或年级等特征可能影响结果，这种方法非常好。例如，如果你的学校有 60% 的男生和 40% 的女生，你的样本应该反映这一比例。
Systematic sampling selects every kth person from a list. It is quick but can introduce bias if there is a hidden pattern. Convenience sampling, such as asking your friends, is almost always biased and will lose marks unless you acknowledge its severe limitations and discuss why no feasible alternative existed.
系统抽样从名单中每隔 k 个人选取一人。它快捷，但如果存在隐藏模式，可能会引入偏差。便利抽样，比如询问你的朋友，几乎总是有偏差的，并且会扣分，除非你承认其严重局限性并讨论为何没有可行的替代方法。
4. Designing Data Collection Instruments | 设计数据收集工具
Whether you use a questionnaire or an observation sheet, your questions must be clear, unambiguous and free from leading language. For example, ‘How many hours of sport did you play last week?’ is better than ‘Do you agree that sport is healthy?’
无论你使用问卷还是观察记录表，你的问题都必须清晰、无歧义且不含诱导性语言。例如，“上周你进行了多少小时的体育运动？”比“你是否同意运动有益健康？”更好。
Use closed questions where possible to ease analysis. Tick boxes for ranges (0-2 hours, 3-5 hours) or numeric inputs are easier to summarise than open-ended text. If you must use open questions, explain how you will categorise the responses later.
尽可能使用封闭式问题以便于分析。带有范围勾选框（0-2 小时，3-5 小时）或数字输入框的问题比开放式文本更容易总结。如果必须使用开放式问题，要说明你之后将如何对回答进行分类。
Pilot your questionnaire on a few classmates before the actual collection. This helps you identify confusing wording or missing options. In your report, mention any changes you made after piloting, as it shows careful planning.
在实际收集前，先对几名同学进行问卷试点。这有助于你发现令人困惑的措辞或缺失的选项。在你的报告中，提及试点后所做的任何更改，因为这显示了周密的计划。
5. Experimental Design and Control Groups | 实验设计与对照组
If your investigation is an experiment rather than a survey, you must include a control group wherever possible and use random allocation to reduce bias. For instance, if testing whether a revision app improves test scores, one group uses the app (treatment) and another revises normally (control).
如果你的调查是实验而非调查问卷，你必须在可能的情况下包含对照组，并使用随机分配来减少偏差。例如，如果测试一个复习应用程序是否提高考试分数，一组使用该应用（实验组），另一组正常复习（对照组）。
Control all other variables (confounding variables) that could influence the outcome. If you cannot control them, acknowledge them as limitations. For example, pupils’ prior attainment or amount of sleep could confound results, so measure these as background variables.
控制所有可能影响结果的其他变量（混杂变量）。如果无法控制，则要承认它们是局限性。例如，学生先前的成绩或睡眠量可能会混淆结果，因此将这些作为背景变量进行测量。
Blinding is a powerful technique. Single-blind means participants do not know which group they are in; double-blind means neither participants nor the person administering the test knows. This prevents expectation bias. Describe how you applied blinding if possible.
盲法是一种有力的技术。单盲意味着参与者不知道自己在哪一组；双盲意味着参与者和施测人员都不知道。这可以防止期望偏差。如果可能，描述你如何应用盲法。
6. Data Types and Levels of Measurement | 数据类型与测量尺度
Know your data types because they determine which charts and statistics are valid. Qualitative data includes categorical (eye colour) and ordinal (rank, like ‘strongly agree’ to ‘strongly disagree’). Quantitative data is either discrete (number of siblings) or continuous (height, time).
了解你的数据类型，因为它们决定了哪些图表和统计量是有效的。定性数据包括分类数据（眼睛颜色）和有序数据（等级，如“非常同意”到“非常不同意”）。定量数据可以是离散的（兄弟姐妹数量）或连续的（身高，时间）。
Your report must identify whether your main variable is qualitative or quantitative. For continuous data, you will calculate means and standard deviations; for ordinal data, medians and interquartile ranges are more appropriate.
你的报告必须指明主要变量是定性的还是定量的。对于连续数据，你将计算平均值和标准差；对于有序数据，中位数和四分位距更为合适。
In SQA tasks, you often collect both types. One common task is to compare the distributions of a continuous variable between two groups. Correctly classifying data in your methodology section earns easy marks.
在 SQA 任务中，你经常会同时收集两种类型的数据。一项常见任务是比较两组之间一个连续变量的分布。在方法论部分正确地对数据进行分类能轻松拿到分数。
7. Presenting Data with Appropriate Charts | 用适当的图表展示数据
Select charts based on data type and purpose. For comparing frequencies among categories, use a bar chart or a Pareto chart. For proportions, use a pie chart (only if you have a small number of categories and the total is meaningful).
根据数据类型和目的选择图表。要比较类别之间的频数，使用条形图或帕累托图。要显示比例，使用饼图（仅当你只有少量类别且总数有意义时）。
To show the distribution of a single continuous variable, use a histogram or a dot plot. Boxplots are excellent for comparing distributions between two or more groups side by side, highlighting medians, quartiles and outliers.
要展示单个连续变量的分布，使用直方图或点图。箱线图非常适合并排比较两组或多组之间的分布，能突出中位数、四分位数和异常值。
For investigating relationships between two continuous variables, draw a scatter graph. Always label axes clearly with the variable name and units, and include a title. If you add a line of best fit, state whether it suggests positive, negative or no correlation.
要调查两个连续变量之间的关系，绘制散点图。务必清楚地用变量名和单位标记坐标轴，并包含标题。如果你添加最佳拟合线，说明它表示正相关、负相关还是无相关。
8. Calculating and Interpreting Descriptive Statistics | 计算与解释描述统计量
For central tendency, use the mean for symmetric distributions without outliers. Use the median when the data is skewed or contains outliers. The mode is useful for categorical data or to highlight the most frequent response.
对于集中趋势，在无异常值的对称分布中使用平均值。当数据偏斜或包含异常值时，使用中位数。众数对分类数据很有用，或用于突出最常见的反应。
Measures of spread are just as important. The range is quick but affected by extreme values. The interquartile range (IQR = Q₃ – Q₁) captures the middle 50% and is robust. Standard deviation tells you how data clusters around the mean; a smaller SD means less spread.
离散程度的度量同样重要。极差计算快，但受极端值影响。四分位距（IQR = Q₃ – Q₁）捕捉中间 50% 的数据，且稳健。标准差告诉你数据围绕平均值的聚集程度；较小的标准差意味着离散程度较低。
In your analysis, always compare summary statistics for different groups using the appropriate measure. Instead of just stating numbers, say what they imply: ‘The median screen time for boys (4.5 hours) is noticeably higher than for girls (3.2 hours), suggesting a real difference in behaviour.’
在你的分析中，始终使用适当的度量来比较不同组的摘要统计量。不要只是陈述数字，要说明它们的含义：“男孩屏幕时间的中位数（4.5 小时）明显高于女孩（3.2 小时），这表明行为存在真实差异。”
9. Identifying Patterns, Outliers and Anomalies | 识别模式、异常值与反常值
An outlier is a data value that lies well away from the main pattern. You can spot it on a dot plot or boxplot. Do not automatically delete outliers; investigate possible causes such as measurement error or a genuine unusual case, and discuss their impact on the mean.
异常值是远离主要模式的数据值。你可以在点图或箱线图上发现它。不要自动删除异常值；调查可能的原因，如测量误差或真实的非典型案例，并讨论它们对平均值的影响。
Look for patterns like clusters, trends, or gaps. In a scatter graph, a cluster of points might show a subgroup behaving differently. Mention any unusual patterns and try to explain them using the context of your investigation.
寻找数据簇、趋势或间隙等模式。在散点图中，一组点可能显示某个子群体的行为不同。提及任何不寻常的模式，并尝试用你的调查背景来解释它们。
In experimental data, an anomaly could be a participant who did not follow instructions. Record all anomalies in your raw data log and explain any decisions to exclude data in your report. Transparency is key.
在实验数据中，反常值可能是未遵循指示的参与者。在你的原始数据日志中记录所有反常值，并在报告中解释任何排除数据的决定。透明度是关键。
10. Drawing Conclusions and Evaluating the Process | 得出结论与评价过程
Your conclusion must directly answer the research question and state whether the hypothesis was supported. Use the statistical evidence you calculated: ‘The positive correlation coefficient of r = 0.72 supports the hypothesis; there is a moderately strong relationship.’
你的结论必须直接回答研究问题，并说明假设是否得到支持。使用你计算的统计证据：“相关系数 r = 0.72 支持了假设；存在中等强度的相关性。”
Never claim to ‘prove’ anything. Statisticians say the evidence ‘supports’ or ‘does not support’ the hypothesis. Also link findings back to the real-world context: what does this correlation mean for the school or individuals?
永远不要声称“证明”了任何事情。统计学家说证据“支持”或“不支持”假设。还要将发现与现实世界背景联系起来：这个相关性对学校或个人意味着什么？
An outstanding evaluation discusses limitations honestly. Did your sample size limit generalisability? Was there response bias? Could another variable explain the outcome? Suggest practical improvements, such as using a larger random sample or a longer data collection period.
出色的评价会诚实地讨论局限性。你的样本量是否限制了结论的可推广性？是否存在回答偏差？是否有另一个变量可以解释结果？提出实际的改进措施，如使用更大的随机样本或更长的数据收集期。
11. Practical Logistics and Record Keeping | 实践操作与记录保存
In a supervised assessment, you must keep a clear log of all raw data, dated and signed if required. Use a table with headings and units. Never alter raw data; if you spot an error, note it separately and explain your correction in the report.
在受监督的评估中，你必须清楚地记录所有原始数据，如需注明日期和签名。使用带标题和单位的表格。切勿修改原始数据；如果发现错误，单独注明并在报告中解释你的更正。
Plan your time carefully. Data collection often takes longer than expected. Have a backup plan in case a teacher or class is unavailable. Schedule time for data cleaning, calculations, graph drawing and writing up.
仔细规划你的时间。数据收集往往比预期的要长。制定一个备用计划，以防老师或班级无法参加。安排好数据清理、计算、图表绘制和撰写报告的时间。
Keep all your work organised in a project folder, either digital or physical. Examiners love to see neat, annotated graphs and clear evidence of statistical thinking. Use checklists to ensure you have addressed every part of the assessment criteria.
将你所有的作业整理在一个项目文件夹中，无论是数字形式还是实体形式。考官喜欢看到整洁、带有注释的图表和清晰的统计思维证据。使用检查表来确保你已经处理了评估标准的每一个部分。
12. Ethical Considerations and Data Protection | 伦理考量与数据保护
Any investigation involving people must respect confidentiality. Use participant codes instead of real names. Store completed questionnaires securely and destroy them after marking if your school policy requires. Mention in your report that you obtained consent.
任何涉及人的调查都必须尊重保密性。使用参与者代号而非真实姓名。安全地存储已完成的问卷，并根据学校政策的要求在评分后销毁。在你的报告中提及你已经获得同意。
Participants must be told they can withdraw at any time without giving a reason. Do not collect sensitive personal data like health records or political opinions unless absolutely necessary and with official approval.
必须告知参与者他们可以随时退出而无需给出理由。除非绝对必要并经过官方批准，否则不要收集敏感的个人数据，如健康记录或政治观点。
If your investigation involves experimental conditions, ensure there is no risk of physical or psychological harm. Debrief participants afterwards, explaining the true purpose and thanking them. Ethical rigour strengthens your project.
如果你的调查涉及实验条件，要确保没有身体或心理伤害的风险。之后向参与者进行事后说明，解释真实目的并感谢他们。伦理的严谨性会加强你的项目。
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