Year 7 OCR Statistics: Experimental and Practical Assessment Key Points | Year 7 OCR 统计：实验/实践考核要点

📚 Year 7 OCR Statistics: Experimental and Practical Assessment Key Points | Year 7 OCR 统计：实验/实践考核要点

In Year 7 OCR Statistics, experimental and practical tasks are a key way to apply what you learn. You might be asked to design a survey, carry out a simple probability experiment, or collect real data from your classmates. Understanding the process from start to finish is essential for getting top marks. This guide walks you through the key points of experimental assessment, covering planning, data collection, presentation, analysis, and evaluation.

在 Year 7 OCR 统计中，实验和实践任务是应用所学知识的重要方式。你可能会被要求设计一项调查、进行一个简单的概率实验，或者从同学那里收集真实数据。从头到尾了解整个过程对于获取高分至关重要。本指南将带你梳理实验考核的关键要点，涵盖计划、数据收集、数据展示、分析和评价。

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1. The Statistical Enquiry Cycle | 统计探究循环

The statistical enquiry cycle provides a framework for any practical investigation. It typically includes: pose a question, plan and collect data, process and present data, interpret and discuss results, and evaluate the process. OCR assessments expect you to demonstrate understanding of this whole cycle.

统计探究循环为任何实践调查提供了一个框架。它通常包括：提出问题、计划和收集数据、处理与展示数据、解释与讨论结果，以及评价整个过程。OCR 考核要求你展示对整个循环的理解。

When you work on an experiment, always keep this cycle in mind. Each step must be carefully considered because marks are awarded for your planning and reflection, not just the final answer.

当你在做一个实验时，时刻牢记这个循环。每一步都需要认真考虑，因为评分标准会关注你的计划和反思，而不仅仅是最终的答案。

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2. Posing a Clear Question | 提出清晰的问题

Every practical investigation begins with a statistical question that can be answered with data. A good question is specific and measurable. For example, instead of asking ‘How tall are students?’, you could ask ‘What is the typical height of Year 7 students in our class?’

每项实践调查都始于一个可以用数据回答的统计问题。一个好的问题是具体且可量化的。例如，不要问“学生们有多高？”，你可以问“我们班 Year 7 学生的典型身高是多少？”。

Avoid questions that are too vague or that lead to opinions without numbers. In a probability experiment, you might ask: ‘If I roll a fair six-sided dice 60 times, how often will I get a six?’ This is a testable statistical question.

避免问题过于模糊或导致没有数字的主观意见。在概率实验中，你可以这样问：“如果我将一枚公平的六面骰子投掷 60 次，出现六点的频率会是多少？”这是一个可检验的统计问题。

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3. Planning Data Collection | 计划数据收集

Before you start collecting data, you need a clear plan. Decide what data you need, how you will collect it, and what tools or equipment you will use. For a survey, design a simple data collection sheet or tally chart. For an experiment, list the steps you will follow.

在开始收集数据之前，你需要一个清晰的计划。确定你需要哪些数据，如何收集，以及将使用哪些工具或设备。对于调查，设计一个简单的数据收集表或计数表。对于实验，列出你将遵循的步骤。

It is important to think about sample size. Will you survey the whole class or just a few people? In probability experiments, decide how many trials you will carry out. A larger number of trials usually gives more reliable results.

样本量也很重要。你打算调查全班还是只调查几个人？在概率实验中，决定要进行多少次试验。通常，更多的试验次数会得到更可靠的结果。

You should also consider how to keep your data fair and unbiased. For example, if you are measuring reaction times, make sure everyone does the test under the same conditions.

你还需要考虑如何保持数据的公平和无偏。例如，如果你在测量反应时间，确保每个人在相同条件下进行测试。

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4. Carrying Out the Experiment and Recording Data | 进行实验与记录数据

When you carry out your experiment or survey, record the data neatly and accurately as you go. Use tally marks for counting frequencies, and then convert tallies into numbers. Always label your data clearly, including units where necessary.

当你进行实验或调查时，要一边操作一边整齐、准确地记录数据。使用计数符号（正字）来记录频数，然后将计数转换为数字。一定要清楚地标记数据，必要时包括单位。

For a dice-rolling experiment, you might create a table with outcomes 1 to 6 and use tally marks to record each roll. After 60 rolls, you count the tallies to get frequencies. This raw data is your starting point for analysis.

对于掷骰子实验，你可以创建一个结果 1 到 6 的表格，并用计数符号记录每次投掷。在 60 次投掷后，数出计数得到频数。这些原始数据是你分析的起点。

Avoid altering results to match your expectations. Honest recording is a key skill, and examiners will check whether your conclusions are based on the data you actually collected.

不要为了符合期望而篡改结果。如实记录是一项关键技能，考官会检查你的结论是否基于实际收集的数据。

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5. Organising and Sorting Data | 组织与整理数据

Once you have raw data, you need to organise it so it becomes easier to understand. For categorical data (like favourite colours), you can create a frequency table. For numerical data (like heights or test scores), you might need to group the data into intervals.

拿到原始数据后，你需要将其整理得更容易理解。对于分类数据（如最喜欢的颜色），可以创建一个频数表。对于数值数据（如身高或测试分数），可能需要将数据分组为区间。

When grouping continuous data, choose equal class intervals and make sure there are no gaps or overlaps. For example, heights could be grouped as 140–149 cm, 150–159 cm, and so on. The intervals should cover the full range of your data.

在分组连续数据时，选择相等的组距，并确保没有间隔或重叠。例如，身高可以分组为 140–149 厘米、150–159 厘米等。这些区间应当覆盖数据的整个范围。

Organised data can then be used to draw charts and calculate summary statistics. Practise creating frequency tables from a list of raw numbers; this is a common task in practical assessments.

整理好的数据随后可以用来绘制图表和计算汇总统计量。练习根据原始数字列表创建频数表；这是实践考核中的常见任务。

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6. Visualising Data: Charts and Graphs | 可视化数据：图表

Visual displays help you and others see patterns in the data quickly. In Year 7, you are expected to draw and interpret bar charts, pictograms, line graphs, and possibly pie charts. Choose the right type of graph for your data.

数据可视化能帮助你快速发现数据中的模式。在 Year 7，你需要会绘制和解读条形图、象形图、折线图，可能还有饼图。为你的数据选择正确的图表类型。

Bar charts are used for categorical or discrete data. The bars should be of equal width and separated by gaps. Remember to label both axes and give the chart a title. For continuous data, you might draw a line graph to show trends over time or a frequency diagram for grouped data.

条形图用于分类或离散数据。条形的宽度应相等，并留有间隙。记得给两个轴标注并给图表加一个标题。对于连续数据，你可以绘制折线图来展示随时间变化的趋势，或者为分组数据绘制频数图。

If you are asked to draw a pie chart, you need to calculate the angle for each category using the formula: angle =

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