AS WJEC Statistics: Practical Assessment Key Points | AS WJEC 统计：实验/实践考核要点

📚 AS WJEC Statistics: Practical Assessment Key Points | AS WJEC 统计：实验/实践考核要点

The AS WJEC Statistics practical assessment is a crucial component of the course, requiring you to plan, carry out, and report on a statistical investigation from start to finish. It assesses your ability to apply statistical methods in a real-world context, demonstrating skills in data collection, analysis, and critical evaluation. Success hinges on understanding the key assessment criteria and avoiding common pitfalls.

AS WJEC 统计实践考核是该课程的关键组成部分，要求你从头到尾规划、执行并报告一项统计调查。它考察你在真实情境中应用统计方法的能力，展示数据收集、分析和批判性评估的技能。成功取决于对关键评分标准的理解并避免常见错误。

---

1. Understanding the Purpose of the Practical Investigation | 理解实践调查的目的

A statistical investigation is not just about number crunching: it must have a clear aim that drives every subsequent decision. You need to identify a real problem or area of interest that can be explored through data, ensuring the scope is manageable for the AS level timeframe.

统计调查不仅仅是数字运算：它必须有一个清晰的目标来推动后续的每一个决策。你需要确定一个可以通过数据探索的真实问题或感兴趣的领域，并确保其范围在 AS 级别的时间框架内是可行的。

WJEC examiners look for evidence that you have framed the investigation appropriately, defining the population and the variables to be measured before any data is gathered. An ill-defined purpose often leads to irrelevant data and a weak analysis section.

WJEC 考官会寻找证据证明你已经恰当地框定了调查，在收集任何数据之前就明确了总体和待测量的变量。目标不明确通常会导致无关数据和薄弱分析。

---

2. Formulating a Research Question or Hypothesis | 提出研究问题或假设

Your investigation must be guided by a precise research question or a testable hypothesis. A hypothesis usually takes the form of a null (H₀) and an alternative (H₁), such as ‘H₀: μ = 50’ versus ‘H₁: μ ≠ 50’. If a hypothesis test is not performed, you still need a clear comparative question like ‘Is there a difference between …?’

你的调查必须由一个精确的研究问题或可检验的假设来指导。假设通常采用零假设 (H₀) 和备择假设 (H₁) 的形式，例如 ‘H₀: μ = 50’ 与 ‘H₁: μ ≠ 50’。如果不进行假设检验，你仍然需要一个清晰的比较性问题，比如“……之间是否存在差异？”

The hypothesis or question should directly link to the data you intend to collect and allow for a meaningful conclusion. Avoid overly broad statements; instead, be specific about the variables and the direction you expect to see.

假设或问题应与你打算收集的数据直接关联，并允许得出有意义的结论。避免过于宽泛的陈述；相反，要具体说明变量和你预期看到的方向。

---

3. Planning and Designing Data Collection | 规划与设计数据收集

A robust plan outlines whether you will use primary data (collected by you) or secondary data (existing sources). Primary data collection methods include surveys, experiments, and observations. The plan must address practical issues such as time, resources, and ethical considerations, especially when dealing with people.

一个稳健的计划概述了你将使用一手数据（自己收集）还是二手数据（现有来源）。一手数据收集方法包括调查、实验和观察。计划必须解决实际问题，如时间、资源和伦理考量，尤其是在涉及人员时。

In any experimental design, state clearly how you will control variables, randomise subjects, and replicate measurements to increase reliability. For surveys, the number of participants and how they will be approached must be justified.

在任何实验设计中，要清楚地说明你将如何控制变量、随机分配被试以及重复测量以提高可靠性。对于调查，必须说明参与者数量以及接触他们的方式，并给出理由。

---

4. Sampling Methods and Their Justification | 抽样方法及其合理性

Choosing an appropriate sampling method is one of the most heavily weighted aspects of the assessment. You must name the method (e.g., simple random, stratified, systematic, quota, or opportunity sampling) and provide a justification linked to the target population and practical constraints.

选择合适的抽样方法是评估中权重最重的方面之一。你必须命名方法（例如简单随机、分层、系统、配额或便利抽样），并结合目标总体和实际限制提供理由。

Method | 方法	Key Feature | 关键特点	Justification Example | 理由示例
Simple Random | 简单随机	Every member has equal chance; unbiased | 每个成员机会均等；无偏	Used when population is homogeneous and a sampling frame is available | 当总体同质且拥有抽样框时使用
Stratified | 分层	Population divided into groups; then random sample from each | 总体分群；再从各群随机抽样	Ensures representation of key subgroups (e.g., year groups) and reduces variability | 确保关键子群（如年级）的代表性，减少变异性
Systematic | 系统	Select every k-th item from a list | 从列表中每 k 个抽取一个	Quick and spread across the population, used when a complete list is available and no hidden pattern | 快速且遍布总体，当有完整名单且无隐藏模式时使用

Never simply say ‘I used random sampling because it is easy’; explain why the method suits the investigation. Also discuss potential sampling bias and how you tried to minimise it, as this directly links to the evaluation criterion.

永远不要简单地说“我使用随机抽样因为它简单”；要解释为什么该方法适合调查。还要讨论潜在的抽样偏差以及你如何努力将其最小化，因为这直接与评估标准相关。

---

5. Data Collection Instruments: Questionnaires & Experiments | 数据收集工具：问卷与实验

If you design a questionnaire, each question must serve a purpose. Use a mix of closed questions (yielding numerical or categorical data) and open questions where appropriate, but be aware that open questions are harder to analyse. Pilot your questionnaire to detect ambiguous wording.

如果你设计了一份问卷，每个问题都必须有目的。适当混合使用封闭式问题（产生数值或分类数据）和开放式问题，但要注意开放式问题分析起来更困难。对你的问卷进行预调查，以检测模棱两可的措辞。

For experiments, clearly describe the apparatus, the levels of the independent variable, and how the dependent variable is measured. Random allocation to treatment groups is essential to reduce confounding effects. Record the procedure in sufficient detail so that another person could replicate it.

对于实验，要清楚描述仪器、自变量的水平以及因变量如何测量。随机分配到处理组对减少混杂效应至关重要。记录程序要足够详细，以便他人可以复制。

In all cases, ensure your data collection sheet is well-structured, with space for dates, participant codes and raw measurements, making data entry straightforward.

在所有情况下，确保你的数据收集表结构良好，有日期、参与者代码和原始测量值的空间，使数据录入变得简单。

---

6. Organising and Presenting Raw Data | 整理与展示原始数据

Before analysis, raw data must be cleaned and organised. Present your data in properly labelled tables, including frequencies, cumulative frequencies, or grouped intervals if necessary. In WJEC practical reports, you are expected to include the raw data in an appendix, with summary tables in the main body.

在分析之前，必须清理和组织原始数据。将你的数据呈现在标注恰当的表格中，包括频数、累积频数或必要时的分组区间。在 WJEC 实践报告中，你应该将原始数据放在附录中，在正文中使用汇总表。

A common mistake is to present a table without units or clear titles. Every table should be numbered and have a descriptive title that tells the reader what the data represents without referring back to the text.

一个常见的错误是呈现表格时缺少单位或清晰的标题。每个表格都应该编号并有一个描述性标题，告诉读者数据代表什么，而无需回看正文。

---

7. Data Analysis: Descriptive Statistics & Graphs | 数据分析：描述统计与图表

Calculate appropriate measures of central tendency (mean, median, mode) and dispersion (range, interquartile range, standard deviation). For AS WJEC, you must be able to compute the sample standard deviation s using the formula:

计算适当的集中趋势量数（平均值、中位数、众数）和离散量数（极差、四分位距、标准差）。对于 AS WJEC，你必须能够使用公式计算样本标准差 s：

s = √( Σ(x – x̄)² / (n − 1) )

Choosing the correct graph is vital. Use box plots to compare distributions, histograms for continuous data (with frequency density on the vertical axis when class widths are unequal), and scatter diagrams to show relationships. Always label axes and include a key where needed.

选择正确的图表至关重要。使用箱线图比较分布，使用直方图处理连续数据（当组距不等时，垂直轴使用频率密度），使用散点图展示关系。始终标记坐标轴，并在需要时包含图例。

Statistical software or spreadsheets can be used, but you must show that you understand the output, not just copy-paste. Explain why you chose a particular graphical representation and what patterns you observe.

可以使用统计软件或电子表格，但你必须表明你理解输出结果，而不仅仅是复制粘贴。解释你为什么选择特定的图形表示以及你观察到了什么模式。

---

8. Inferential Statistics (if applicable) | 推论统计（如适用）

If your investigation involves testing a hypothesis, state the null and alternative clearly, select a significance level (commonly 5%), and identify the appropriate test. AS level often includes the chi-squared test for association or goodness-of-fit, and the product moment correlation coefficient (PMCC) for linear association.

如果你的调查涉及检验假设，要清楚地陈述零假设和备择假设，选择一个显著性水平（通常是 5%），并确定适当的检验。AS 级别通常包括用于关联性或拟合优度的卡方检验，以及用于线性关联的积矩相关系数 (PMCC)。

When using PMCC, comment on its value and the critical value from tables. For χ², combine classes if expected frequencies are less than 5. Always state your conclusion in context: ‘There is sufficient evidence at the 5% level to reject H₀, suggesting that …’ Never say ‘prove’.

使用 PMCC 时，要评论其数值和表中的临界值。对于 χ²，如果期望频数小于 5，要合并类别。始终在上下文中陈述你的结论：“在 5% 的水平上有足够证据拒绝 H₀，表明……”。永远不要说“证明”。

---

9. Interpreting Results and Drawing Conclusions | 解释结果并得出结论

This section bridges the analysis and the original purpose. Summarise your findings in words, referring back to the research question or hypothesis. If a correlation was found, discuss its strength and direction, but do not automatically imply causation unless an experiment was conducted with proper controls.

这一部分连接了分析和最初的目的。用语言总结你的发现，并回溯到研究问题或假设。如果发现了相关性，讨论其强度和方向，但不要自动暗示因果关系，除非进行了有适当对照的实验。

Highlight what the statistics actually mean in the real-world context. For example, a significant difference in test scores might be linked to teaching methods, but you must acknowledge other factors that could have influenced the result.

强调统计数据在现实世界背景下的实际意义。例如，考试成绩的显著差异可能与教学方法有关，但你必须承认可能影响结果的其他因素。

---

10. Evaluating the Investigation: Limitations and Improvements | 评估调查：局限性与改进

A high-scoring evaluation does not simply list everything that went wrong; it analyses the impact of limitations on the reliability and validity of the conclusions. Discuss sampling errors (arising from the choice and size of the sample) and non-sampling errors (measurement bias, questionnaire design, non-response).

高分的评估不是简单地列出所有出错之处；而是分析局限性对结论可靠性和有效性的影响。讨论抽样误差（由样本选择和样本量引起）和非抽样误差（测量偏差、问卷设计、无回应）。

Suggest specific, realistic improvements. For instance, ‘A larger, stratified random sample with proportional allocation by age group would reduce sampling bias and allow more precise estimates.’ Avoid vague phrases like ‘do it more carefully’.

提出具体、现实的改进建议。例如，“一个更大的、按年龄组按比例分配的分层随机抽样将减少抽样偏差，并允许更精确的估计。”避免使用诸如“更仔细地做”之类的模糊措辞。

---

11. Report Writing and Communication | 报告撰写与沟通

Your practical assessment is ultimately assessed through a written report. Structure it with clear sections: Introduction, Methodology, Data Presentation, Analysis, Conclusion, and Evaluation. Use headings, but ensure the narrative flows logically.

你的实践评估最终是通过书面报告来评分的。以清晰的部分来组织结构：引言、方法、数据展示、分析、结论和评估。使用标题，但要确保叙述逻辑连贯。

Write in a formal, precise style. Define all technical terms the first time you use them. Cross-reference tables and graphs in the text (e.g., ‘As shown in Figure 3…’) and number them consistently. Proofread for spelling and grammar, as poor presentation can obscure your statistical thinking.

以正式、精确的风格写作。首次使用时定义所有技术术语。在正文中交叉引用表格和图表（例如，“如图 3 所示……”）并进行一致的编号。检查拼写和语法，因为糟糕的表达会掩盖你的统计思维。

---

12. Common Errors to Avoid | 需避免的常见错误

• Selecting a graph that does not suit the data type, such as a bar chart for continuous data when a histogram is needed.

  选择不适合数据类型的图表，例如在需要直方图时用条形图表示连续数据。

• Confusing the sample standard deviation with the population standard deviation; always use n − 1 for a sample.

  混淆样本标准差与总体标准差；计算样本时始终使用 n − 1。

• Using the word ‘prove’ in a hypothesis test conclusion – statistical tests only provide evidence against H₀.

  在假设检验结论中使用“证明”一词——统计检验仅提供反对 H₀ 的证据。

• Ignoring outliers without comment; outliers should be identified and their impact discussed.

  忽略离群值而不加评论；应识别离群值并讨论其影响。

• Writing a conclusion that does not refer back to the initial research question, leaving the investigation feeling unfinished.

  撰写的结论未回溯到最初的研究问题，使调查显得未完成。

• Failing to include units in tables and axes, making interpretation impossible for the reader.

  表格和坐标轴中缺少单位，导致读者无法进行解释。

---

Published by TutorHao | Statistics Revision Series | aleveler.com

更多咨询请联系16621398022（同微信）