📚 IGCSE WJEC Statistics: Case Study Practice in Action | IGCSE WJEC 统计：案例分析实战演练
This revision guide walks through a complete IGCSE WJEC Statistics case study. You will see how to move from a raw scenario to organised data, charts, summary statistics, correlation, regression, probability and critical evaluation. The same skills are tested in your written paper, so follow each step actively.
本复习指南将完整演练一个 IGCSE WJEC 统计案例。你将看到如何从原始情境过渡到整理数据、图表、汇总统计、相关性、回归、概率和批判性评价。这些技能在笔试中都会考查，请主动跟随每一步。
1. Understanding the Case Study Scenario | 理解案例背景
A school collects data from 12 students on the number of hours spent in front of a screen each day and their end-of-year mathematics test score as a percentage. The research question is: 'Is higher daily screen time associated with lower mathematics scores?'
某学校收集了 12 名学生的数据：每天屏幕使用时间（小时）和年末数学考试成绩（百分制）。研究问题是：'每天屏幕时间越长，数学成绩是否越低？'
In this case, screen time is the explanatory variable and test score is the response variable. The data are bivariate because each student gives a pair of values.
在本案例中，屏幕时间是解释变量，考试成绩是响应变量。数据是双变量的，因为每名学生提供一对数值。
| Student | A | B | C | D | E | F | G | H | I | J | K | L |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Screen time (h) | 2.1 | 3.5 | 4.2 | 5.0 | 2.8 | 3.1 | 6.5 | 7.2 | 1.8 | 4.8 | 5.6 | 3.9 |
| Test score (%) | 88 | 75 | 70 | 65 | 82 | 80 | 48 | 45 | 90 | 62 | 55 | 72 |
Always identify the variables and whether the data are univariate or bivariate before choosing a method.
在选择方法之前，务必先识别变量类型以及数据是单变量还是双变量。
2. Data Collection and Sampling Design | 数据收集与抽样设计
The 12 students are taken from one school using an opportunity sample. This is quick and convenient, but it may be biased because the students may not represent all IGCSE mathematics learners in the region.
这 12 名学生来自一所学校，采用的是便利抽样。这种方法快捷方便，但可能存在偏差，因为这些学生不一定能代表该地区所有 IGCSE 数学学习者。
A simple random sample would give every member of the target population an equal chance of selection. A larger sample would also reduce the effect of unusual values.
简单随机抽样可以让目标总体中的每个成员都有相等的被选中机会。更大的样本也会减少异常值的影响。
Screen time is quantitative continuous data because it can take any value on a scale. Test score is also treated as quantitative continuous in this analysis.
屏幕使用时间是定量连续数据，因为它可以在一定范围内取任意值。在本分析中，考试成绩也作为定量连续数据处理。
3. Organising Raw Data into Frequency Tables | 将原始数据整理为频数表
Before drawing graphs, organise raw screen times into a grouped frequency table. Use equal class widths of 2 hours.
在绘制图表之前，先把原始屏幕时间整理成分组频数表。使用相等的组距，每组宽度为 2 小时。
| Screen time, x (hours) | Frequency | Cumulative frequency |
|---|---|---|
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