Year 9 Edexcel Statistics: Case Study Practical Exercise | 九年级爱德思统计：案例分析实战演练

📚 Year 9 Edexcel Statistics: Case Study Practical Exercise | 九年级爱德思统计：案例分析实战演练

Welcome to this case study practical exercise designed to strengthen your understanding of key statistical concepts at Year 9 Edexcel level. We will explore a realistic school survey on daily screen time, applying skills in data collection, organisation, visualisation, summary statistics and basic probability. By working through this example, you will see how statistics is used to draw meaningful conclusions from real data.

欢迎来到这个案例分析实战演练，旨在巩固九年级爱德思统计核心概念的理解。我们将探讨一个真实的学校每日屏幕时间调查，运用数据收集、整理、可视化、汇总统计和基础概率等技能。通过这个示例，你将看到统计学如何从真实数据中得出有意义的结论。

1. Understanding the Scenario: A School Survey on Screen Time | 理解场景：学校屏幕时间调查

A secondary school wants to investigate how much time Year 9 students spend on screens (phones, tablets, computers, TV) for non-educational purposes each weekday. The school council conducted a survey asking 30 students to record their total screen time (in hours) on a typical school day. It was made clear that the survey only considered leisure screen time, not time spent on homework or online learning. Understanding the context helps us decide what data to collect and how to analyse it meaningfully.

一所中学想调查九年级学生每个上学日用于非学习目的的屏幕时间（手机、平板、电脑、电视）有多长。学生会进行了一项调查，要求30名学生记录他们在一个典型上学日的总屏幕时间（小时）。调查明确只考虑休闲屏幕时间，不包括家庭作业或在线学习时间。理解背景有助于我们决定收集什么数据以及如何有意义地进行分析。

2. Data Collection Methods | 数据收集方法

The data was collected using a short questionnaire handed out during form time. Each student wrote down their screen time rounded to the nearest half hour, along with their gender to allow for later comparison. This is primary data because it is collected firsthand for this specific purpose. Using a questionnaire allowed for quick, consistent collection, but we must consider possible bias: students might underestimate their screen time to appear more studious, or some may exaggerate. The use of self-reported data is a limitation we will evaluate later.

数据是通过在辅导时间发放的简短问卷收集的。每个学生写下了他们的屏幕时间，四舍五入到最接近的半小时，同时还写下了性别以便稍后进行比较。这是原始数据，因为是为此特定目的第一手收集的。使用问卷可以快速、一致地收集数据，但我们必须考虑可能的偏差：学生可能为了显得更勤奋而低估屏幕时间，或者有些人可能夸大。自我报告数据的使用是我们稍后将评估的一个局限。

3. Organising Raw Data into Frequency Tables | 将原始数据整理成频数表

The raw responses from the 30 students were: 2.5, 3.0, 1.5, 4.0, 2.0, 3.5, 3.0, 2.5, 1.0, 5.0, 2.0, 4.5, 3.0, 2.5, 1.5, 3.5, 4.0, 2.0, 3.0, 6.0, 2.5, 3.5, 1.0, 4.0, 3.0, 2.0, 5.5, 3.0, 2.5, 4.5. To make sense of this list, we construct a frequency table. Because the data values are recorded in half-hour steps, we can treat them as discrete categories and tally each occurrence.

30名学生的原始回答是：2.5, 3.0, 1.5, 4.0, 2.0, 3.5, 3.0, 2.5, 1.0, 5.0, 2.0, 4.5, 3.0, 2.5, 1.5, 3.5, 4.0, 2.0, 3.0, 6.0, 2.5, 3.5, 1.0, 4.0, 3.0, 2.0, 5.5, 3.0, 2.5, 4.5。为了理解这一串数字，我们构建一个频数表。由于数据值以半小时为步长记录，我们可以将它们视为离散类别，并为每次出现画记号。

First, list all distinct values in ascending order: 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0. Then go through the raw data, placing a tally mark next to the appropriate value. Finally, count the tally marks to obtain the frequency for each screen time.

首先，按升序列出所有不同值：1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0。然后遍历原始数据，在相应的值旁边画一个记号。最后统计记号，得到每个屏幕时间的频数。