Comparing UK University Entry Requirements | 英国大学申请要求对照

📚 Comparing UK University Entry Requirements | 英国大学申请要求对照

When planning to apply to UK universities, students often look at entry requirements expressed as A-level grades or UCAS tariff points. But how can we compare these requirements in a meaningful way? This article uses statistical skills from the Year 9 CCEA Statistics syllabus to analyse and contrast the entry demands of different courses and universities, helping you make data-informed decisions.

在准备申请英国大学时，学生们通常会查看以A-level成绩或UCAS分数表示的入学要求。然而，我们如何才能有意义地比较这些要求呢？本文将运用Year 9 CCEA统计学大纲中的统计技能，分析并对照不同课程和大学的入学门槛，帮助你做出以数据为依据的决策。

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1. Introduction to Statistical Comparison | 统计比较简介

Statistical comparison involves collecting numerical data and using averages, measures of spread, and graphs to highlight differences and similarities. In the context of university applications, we can treat minimum UCAS tariff points as our variable and compare groups such as Russell Group versus non-Russell Group universities, or science versus arts courses.

统计比较涉及收集数值数据，并利用平均数、离散量度和图表来突显差异与相似之处。在大学申请的背景下，我们可以将最低UCAS分数作为变量，并比较不同组别，例如罗素集团与非罗素集团大学，或理科与文科课程。

CCEA Statistics encourages students to plan a statistical enquiry by setting a hypothesis. A simple hypothesis could be: ‘Russell Group universities have higher average UCAS tariff entry requirements than non-Russell Group universities.’ We test this using the collected data.

CCEA统计学鼓励学生通过设定假设来规划统计调查。一个简单的假设可以是：“罗素集团大学的平均UCAS入学分数高于非罗素集团大学。”我们利用收集到的数据进行检验。

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2. Collecting Data from University Websites | 从大学官网收集数据

To compare entry requirements, we need reliable secondary data. The best sources are university prospectuses, the UCAS course search tool, and official university websites. For each course, we record the required A-level grades and convert them into UCAS tariff points using the official tariff table.

为了比较入学要求，我们需要可靠的二手数据。最佳来源是大学招生简章、UCAS课程搜索工具以及大学官方网站。对于每门课程，我们记录所需的A-level成绩，并使用官方UCAS分数换算表将其转换为 tariff points。

• Visit the UCAS website or individual university pages.
• 访问UCAS网站或各大学页面。
• Choose a range of courses across different subject areas.
• 选择不同学科领域的课程范围。
• Note the minimum required grades (e.g. A*AA, BBB).
• 记录最低要求成绩（例如A*AA、BBB）。
• Apply the tariff: A* = 56, A = 48, B = 40, C = 32, D = 24, E = 16.
• 应用换算标准：A* = 56, A = 48, B = 40, C = 32, D = 24, E = 16。

Always collect data ethically and cite your sources. This aligns with CCEA’s emphasis on understanding how data is generated and used responsibly.

务必合乎道德地收集数据并注明来源。这与CCEA强调理解数据如何产生并负责任地使用的要求一致。

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3. Building a Data Table | 构建数据表格

We record our findings in a structured table. It should include the university name, course, grade requirements, calculated tariff points, and university group (e.g. Russell Group or other). Here is a sample dataset we will use for the rest of the article:

我们将调查结果记录在结构化的表格中。它应包含大学名称、课程、成绩要求、计算出的tariff points以及大学组别（例如罗素集团或其他）。以下是本文后续部分将使用的样本数据集：

University	Course	A-level grades	Tariff points	Group
Oxford	Mathematics	A*A*A	160	Russell
Oxford	History	AAA	144	Russell
Cambridge	Natural Sciences	A*A*A	160	Russell
Imperial	Mechanical Eng	A*A*A	160	Russell
UCL	Law	A*AA	152	Russell
LSE	Economics	A*AA	152	Russell
Bristol	Engineering	A*AA	152	Russell
Warwick	Maths and Stats	A*A*A	160	Russell
Durham	English	A*AA	152	Russell
Manchester	Physics	A*A*A	160	Russell
Leeds	Chemistry	ABB	128	Russell
Sheffield	Biology	AAB	136	Russell
Liverpool	Psychology	ABB	128	Russell
Cardiff	Medicine	AAA	144	Russell
Queen’s Belfast	Nursing	BCC	104	Russell
Aberdeen	Business	BBB	120	Non-Russell
Brighton	Hospitality	BCC	104	Non-Russell
Lincoln	Education	BBC	112	Non-Russell

Each row is a statistical unit. Our variable of interest is the tariff points, a discrete numerical variable.

每一行是一个统计单元。我们关注的变量是tariff points，这是一个离散数值变量。

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4. Calculating Averages (Mean, Median, Mode) | 计算平均值（均值、中位数、众数）

The mean (average) tariff points provide a single figure to represent the typical entry requirement. Using our data, we sum all 18 tariff values and divide by 18.

均值（平均数）提供一个代表典型入学要求的单一数值。利用我们的数据，将所有18个tariff values相加并除以18。

mean = Σx / n = 2528 / 18 ≈ 140.4 tariff points

To find the median, we sort the data: 104, 104, 112, 120, 128, 128, 136, 144, 144, 152, 152, 152, 152, 160, 160, 160, 160, 160. Since n = 18 (even), the median is the mean of the 9th and 10th values.

要找到中位数，我们将数据排序：104, 104, 112, 120, 128, 128, 136, 144, 144, 152, 152, 152, 152, 160, 160, 160, 160, 160。由于n = 18（偶数），中位数为第9个和第10个值的平均数。

median = (144 + 152) / 2 = 148 tariff points

The mode is the most frequent value. Here, 160 appears five times, making it the mode. This tells us that many competitive courses require A*A*A.

众数是出现频率最高的数值。在这里，160出现了五次，成为众数。这表明许多竞争激烈的课程要求A*A*A。

The median (148) is higher than the mean (140.4), revealing that the data is slightly skewed to the left because of a few lower requirements pulling the mean down.

中位数（148）高于均值（140.4），这表明由于少数较低要求拉低了均值，数据略呈左偏态分布。

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5. Measures of Spread: Range and Quartiles | 离散度量：极差和四分位数

Spread tells us how varied the entry requirements are. The simplest measure is the range.

离散度告诉我们入学要求的差异有多大。最简单的量度是极差。

range = maximum – minimum = 160 – 104 = 56 tariff points

To understand the middle 50% of the data, we calculate the lower quartile (Q₁) and upper quartile (Q₃). Using the ordered list with n=18, position of Q₁ = (18+1)/4 = 4.75, so Q₁ lies between the 4th (120) and 5th (128) values: Q₁ = 120 + 0.75 × 8 = 126.

为了解数据的中间50%，我们计算下四分位数（Q₁）和上四分位数（Q₃）。使用有序列表且n=18，Q₁的位置 = (18+1)/4 = 4.75，因此Q₁位于第4个（120）和第5个（128）值之间：Q₁ = 120 + 0.75 × 8 = 126。

Q₃ position = 3(18+1)/4 = 14.25. Q₃ = 152 + 0.25 × (160 – 152) = 154.

Q₃的位置 = 3(18+1)/4 = 14.25。Q₃ = 152 + 0.25 × (160 – 152) = 154。

The interquartile range (IQR) = Q₃ – Q₁ = 154 – 126 = 28 tariff points. This shows that the middle half of courses have entry requirements spanning 28 points.

四分位距（IQR）= Q₃ – Q₁ = 154 – 126 = 28 tariff points。这表明中间一半课程的入学要求跨度为28分。

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