Collecting and presenting numerical information — Cambridge OCR Key Skills Foundations for Learning Revision

    This element develops foundational skills in gathering straightforward numerical data, such as counts or measurements, from everyday contexts like surveys,

    Topic Synopsis

    This element develops foundational skills in gathering straightforward numerical data, such as counts or measurements, from everyday contexts like surveys, inventories, or observations. Learners will then present this information clearly using simple tables, charts, or graphs, enabling them to identify patterns or trends. These skills are essential for making informed decisions in daily life, from budgeting and shopping to monitoring progress in personal projects.

    Key Concepts & Core Principles

    Exam Tips & Revision Strategies

    Common Misconceptions & Mistakes to Avoid

    Examiner Marking Points

    Collecting and presenting numerical information

    CAMBRIDGE OCR
    vocational

    This element develops foundational skills in gathering straightforward numerical data, such as counts or measurements, from everyday contexts like surveys, inventories, or observations. Learners will then present this information clearly using simple tables, charts, or graphs, enabling them to identify patterns or trends. These skills are essential for making informed decisions in daily life, from budgeting and shopping to monitoring progress in personal projects.

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    Learning Outcomes
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    Assessment Guidance
    55
    Key Skills
    33
    Key Terms
    56
    Assessment Criteria

    Assessment criteria

    Cambridge OCR Entry Level Certificate in Life and Living Skills (Entry 3)
    Cambridge OCR Entry Level Award in Life and Living Skills (Entry 3)
    Cambridge OCR Entry Level Introductory Award in Life and Living Skills (Entry 1)
    Cambridge OCR Entry Level Award in Life and Living Skills (Entry 1)
    Cambridge OCR Entry Level Certificate in Life and Living Skills (Entry 1)
    Cambridge OCR Entry Level Extended Certificate in Life and Living Skills (Entry 2)
    Cambridge OCR Entry Level Extended Award in Life and Living Skills (Entry 1)
    Cambridge OCR Entry Level Extended Certificate in Life and Living Skills (Entry 3)
    Cambridge OCR Entry Level Extended Certificate in Life and Living Skills (Entry 1)
    Cambridge OCR Entry Level Introductory Award in Life and Living Skills (Entry 2)
    Cambridge OCR Entry Level Introductory Award in Life and Living Skills (Entry 3)
    Cambridge OCR Entry Level Award in Life and Living Skills (Entry 2)
    Cambridge OCR Entry Level Certificate in Life and Living Skills (Entry 2)
    Cambridge OCR Entry Level Diploma in Life and Living Skills (Entry 1)
    Cambridge OCR Entry Level Diploma in Life and Living Skills (Entry 2)
    Cambridge OCR Entry Level Diploma in Life and Living Skills (Entry 3)

    Topic Overview

    Foundations for Learning is a core component of the Cambridge OCR Entry Level Certificate in Life and Living Skills (Entry 3). This unit focuses on developing essential skills that underpin all other learning, such as communication, numeracy, and personal organisation. Students explore how to set simple goals, follow instructions, and reflect on their own progress, which builds confidence and independence in both academic and everyday contexts.

    The unit is structured around practical activities that encourage students to apply their skills in real-life situations. For example, learners might plan a short journey, create a shopping list within a budget, or complete a simple task like following a recipe. These activities are designed to be accessible and relevant, helping students see the direct link between classroom learning and their daily lives.

    Mastering Foundations for Learning is crucial because it provides the building blocks for further study and personal development. By the end of this unit, students should be able to work more independently, manage their time better, and communicate their needs clearly. This not only prepares them for other Entry Level qualifications but also equips them with life skills that are valued in the workplace and community.

    Key Concepts

    Core ideas you must understand for this topic

    • →Goal setting: Breaking down a larger task into smaller, achievable steps and setting a target to complete them.
    • →Following instructions: Understanding and carrying out a sequence of steps accurately, whether written or spoken.
    • →Basic numeracy for everyday life: Using numbers to manage money, measure ingredients, or tell time.
    • →Reflection: Thinking about what you have learned, what went well, and what you could improve next time.
    • →Personal organisation: Keeping track of belongings, managing time, and planning simple activities.

    Learning Objectives

    What you need to know and understand

    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Gather numerical data from at least two different sources, such as a tally count and a short questionnaire.
    • Record data accurately using a table with clear headings and units.
    • Construct a simple bar chart from given or collected data.
    • Identify the most frequent or highest value from the data presentation.
    • Compare two sets of data and state which is larger or smaller.
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Identify suitable methods for collecting simple numerical information in a given context
    • Use a tally system or checklist to accurately record data
    • Organise collected data into a basic table or chart
    • Present numerical information clearly using a simple bar chart or pictogram
    • Describe one key finding or trend from the presented data
    • Check data for obvious errors or inconsistencies
    • Collect numerical data using tally charts in a familiar context
    • Present collected data using a simple pictogram or block graph
    • Make a basic observation from presented data, such as identifying the most frequent item
    • Check data collection for accuracy by recounting
    • Record numerical information using simple tally methods.
    • Construct a basic bar chart or pictogram from collected data.
    • Describe what the data shows in simple terms.
    • Identify the category with the highest or lowest frequency.
    • Apply data collection skills to a real-life situation, such as a survey of classmates' favourite snacks.
    • Apply tallying methods to gather numerical information
    • Construct a bar chart and pictogram from given data
    • Interpret data to determine maximum and minimum values
    • State a conclusion based on the presented information

    Assessment Criteria

    Key criteria assessors look for in your portfolio

    • Award credit for demonstrating a systematic approach to data collection, such as using a tally chart to record frequencies accurately and in an organised manner.
    • Award credit for selecting an appropriate form of presentation (e.g., bar chart, pictogram, simple table) that suits the data type and labelling all key components like axes, titles, and units.
    • Award credit for making a logical observation about the findings, such as identifying the highest or lowest value, comparing categories, or noting a simple trend, and stating it clearly in a sentence.
    • Evidence of accurate data collection with no systematic errors.
    • Correct use of a tally chart to record frequencies.
    • Clear labelling of axes on a bar chart or pictogram.
    • Observation statement that correctly references the data presented.
    • Award credit for correctly using a simple recording method, such as tally marks or a prepared tick sheet, to collect numerical data with minimal inaccuracy.
    • Award credit for presenting the collected data in an appropriate visual format (e.g., a pictogram with one symbol representing one unit, a block graph) that includes clear labels or a key.
    • Award credit for making a valid observation directly linked to the data, such as 'more people chose apples than bananas', evidenced through a simple sentence or spoken explanation supported by the presented information.
    • Award credit for demonstrating the ability to collect data using a tally chart or simple checklist, with accurate counting and logical organisation.
    • Evidence must show successful presentation of the collected data in a clear format, such as a simple bar chart, pictogram, or ordered list, with appropriate labels or titles.
    • The learner is expected to make at least one straightforward, relevant observation based on the data (e.g., 'More items were sold on Monday than Tuesday' or 'Apples were the most common choice'), showing they can interpret their findings.
    • Award credit for demonstrating the accurate use of a tally chart to record collected data, with correct grouping and totals.
    • Award credit for presenting numerical information clearly in a simple bar chart, pictogram, or block graph, with appropriate labels and consistent spacing.
    • Award credit for making a valid observation about findings, such as identifying the most or least popular item, or comparing one value to another using language like ‘more than’ or ‘less than’.
    • Award credit for accurately tallying data from a given source with no more than one omission or miscount.
    • Award credit for selecting an appropriate visual format to present data (e.g., pictogram, simple bar chart) that matches the data type.
    • Award credit for making at least one clear observation about the data, such as identifying the most or least common item, supported by reference to the presented information.
    • Award credit for demonstrating the ability to collect data using a simple tally system or counting method accurately.
    • Credit should be given for presenting collected data clearly, e.g., in a pictogram, block graph, or simple table with correct labels.
    • Evidence of making at least one valid observation about the findings, such as 'most people chose red' or 'there were more apples than bananas', must be present.
    • Award credit for demonstrating the ability to collect numerical information using a structured approach (e.g., tallying scores, recording measurements).
    • Require evidence of presenting data clearly with appropriate labels or titles, such as on a bar chart or simple table.
    • Look for an observation that directly relates to the presented data, even if simple (e.g., 'More people prefer tea than coffee').
    • Award credit for demonstrating the use of a simple tally or counting method to collect numerical information from a given source or real-life scenario.
    • Award credit for accurately transferring collected data into a provided chart, graph, or table format, with correct labels or titles as appropriate.
    • Award credit for making at least one valid observation about the presented data, such as identifying which category has the highest or lowest frequency.
    • Award credit for demonstrating the ability to collect data using a clear, organised method (e.g., tally chart, simple table) with accurate recording of numbers or counts.
    • Credit should be given for selecting an appropriate format to present data (e.g., bar chart, pictogram, list) and including key elements like title, labels, and accurate representation of values.
    • Assessors should look for a simple, valid observation based on the data, such as identifying the most/least frequent item, comparing totals, or noting a trend (e.g., 'more people chose tea than coffee').
    • Evidence must show the learner can work independently or with minimal support to collect data from a small sample (e.g., 5-10 items or questions).
    • Award credit for demonstrating the ability to gather simple numerical data using a structured method such as a tally chart or recording sheet, with clearly defined categories.
    • Credit should be given for presenting data using an appropriate format (e.g., bar chart, pictogram, table) that includes a title, labelled axes or headings, and an accurate representation of the collected figures.
    • Learners should be credited for making at least one direct observation based on the presented data, such as identifying the most/least frequent item or a simple comparison between categories.
    • Evidence of checking consistency between collected data and final presentation (e.g., totals matching) should be rewarded as part of the process.
    • Award credit for demonstrating the ability to collect data using a structured method, such as a tally sheet, even if support is provided.
    • Give marks for presenting information clearly using a simple chart or list, with appropriate labels or a key where needed.
    • Recognize achievement when the learner can articulate at least one valid observation from their data, such as identifying the most or least frequent item.
    • Award credit for demonstrating a systematic approach to data collection (e.g. tally marks, structured sheet)
    • Mark for correctly labelling all parts of a chart or table (title, axes, categories)
    • Credit an observation that directly references the data presented, even if basic
    • Look for evidence of checking (e.g. totalling tallies, comparing to raw data)
    • Accept simple but appropriate visual presentation (neatness, correct scale)
    • Award credit for correctly using tally marks to count items, with every fifth mark drawn diagonally to group in fives
    • Credit for creating a clear and labelled pictogram or bar chart, including a title and labels for categories
    • Credit for stating an observation that directly relates to the data, e.g., 'There are more apples than bananas' or 'The red cars are the most common'
    • Assessors should look for accurate one-to-one correspondence when counting objects to ensure no items are missed or double-counted
    • Award one mark for each correctly recorded tally against the appropriate category.
    • Award credit for a chart that includes a title, labelled axes, and correctly plotted data.
    • Award credit for a simple written or verbal observation that correctly references the data (e.g., ‘Most people prefer tea’).
    • Ensure that the presentation method is appropriate for the type of data collected.
    • Award credit for demonstrating accurate use of tally marks to record data
    • Credit given for correctly labeling axes on a bar chart and using an appropriate scale
    • Recognising and stating the category with the highest frequency
    • Providing a clear, data-supported observation, such as noting the most popular choice

    Assessment Guidance

    Guidance for achieving higher grades

    • 💡Always begin by clearly defining what data you need to collect and how you will record it, e.g., using a prepared tally table with clear headings.
    • 💡When presenting, ensure your chart or table has a clear title and labelled axes; use a ruler for neatness and accuracy to avoid losing marks for presentation.
    • 💡After presenting the data, write a simple sentence or two summarising the key finding, using phrases like 'the most popular...', 'there is a decrease...', or 'X is larger than Y' to demonstrate understanding.
    • 💡Always check that the total of your tally matches the sum of your data.
    • 💡When making an observation, use comparing words like 'more than' or 'fewer than' supported by numbers.
    • 💡Practice converting raw data into a table before attempting a chart to ensure accuracy.
    • 💡Always present data in the simplest, clearest way possible so that anyone can understand your findings at a glance.
    • 💡Double-check that your observations are based only on the numbers you collected, using phrases like 'My chart shows...' to keep your commentary evidence-based.
    • 💡If you are asked to present data, use large symbols or thick lines in graphs to make your work accessible and easy for assessors to interpret.
    • 💡Double-check totals by recounting or using a different method, such as adding up the tallies, to ensure accuracy before finalising your presentation.
    • 💡Always label your chart or list clearly with a title and key, even for simple block graphs—this demonstrates an understanding of good practice.
    • 💡When making an observation, use comparative language (e.g., 'more', 'less', 'the same') and directly reference the numbers or categories shown, rather than guessing.
    • 💡Always double-check that the totals in your tally chart match the number of items you counted; a quick recount can prevent avoidable errors.
    • 💡When creating a presentation, use a ruler for straight lines and ensure each symbol in a pictogram represents one item to maintain clarity and accuracy.
    • 💡Phrase your observation as a simple, factual statement directly linked to the data, for example, ‘The most popular fruit was apples because more people chose apples than any other fruit.’
    • 💡Always double-check your tally counts by recounting or using a different method (e.g., crossing off items as you count) to avoid simple errors.
    • 💡Label all parts of your chart clearly, including a title, axis labels if appropriate, and a key for pictograms, to ensure the assessor can understand your presentation.
    • 💡When making an observation, be specific and refer directly to the data, e.g., 'There were more apples than bananas because the bar for apples is taller'.
    • 💡Always double-check tallies by counting in fives for speed and accuracy, and verify your total against the original data source.
    • 💡When presenting information, use a key if using symbols in a pictogram, and ensure each representation matches one unit of data.
    • 💡Phrase your observation using comparative language like 'more than', 'less than', or 'most/least' directly supported by your chart or table.
    • 💡In practical assessments, ensure your data collection method is appropriate and ethical (e.g., obtain permission before surveying).
    • 💡Use graph paper or digital tools to improve presentation clarity and neatness.
    • 💡State your observation in a full sentence linked directly to the data, avoiding vague statements.
    • 💡Always double-check your counting by re-tallying your data before creating your chart or graph to ensure accuracy.
    • 💡When presenting data, use the format suggested in the task and make sure to include a simple title and labels so your work is easy to understand.
    • 💡For the observation, stick to one clear and simple statement like 'More people chose apples than bananas' based only on your presented information.
    • 💡Always label your charts clearly and give them a title – even if the data is simple, presentation clarity is essential for achieving marks.
    • 💡When collecting data, double-check tally marks to ensure the total accurately matches the number of responses or items recorded.
    • 💡For observations, stick to what the numbers show; avoid adding opinions (e.g., say '5 people chose red' rather than 'red is popular').
    • 💡Practise with real-life scenarios, such as collecting classmates' favourite snacks, to build confidence and familiarity with the process.
    • 💡Always begin by planning how you will collect the data – decide on categories and a simple recording method (like a tally sheet) before you start gathering information.
    • 💡When presenting data, double-check that all tallies or values are transferred correctly to your chart or table, and ensure that the total number matches the original count.
    • 💡For your observation, stick to straightforward facts visible in the data, such as ‘Apples were the most popular fruit’ or ‘Tuesday had the fewest visitors’; avoid adding personal opinions.
    • 💡If using a computer to present data, still check the output for accuracy – software can make errors if data is entered incorrectly.
    • 💡Use real-life data collection activities (e.g., traffic survey, favourite snacks) to make the process meaningful and easier to recall during assessment.
    • 💡Always double-check your tallies by recounting, and ensure your chart matches the numbers exactly before final presentation.
    • 💡When making an observation, phrase it as a simple numerical statement like ‘more people chose apple than banana’ to directly show understanding.
    • 💡Always complete the data collection fully before starting the presentation; don't skip items.
    • 💡Use a pencil and ruler for any charts to keep presentation neat and clear.
    • 💡Double-check tally counts by crossing off each group as you total them.
    • 💡When making an observation, phrase it as 'I noticed that...' and link it directly to the numbers in your chart.
    • 💡If time allows, compare your presented data back to original records to catch any copying mistakes.
    • 💡Practice collecting data in real-life situations, like counting different coloured cars in a car park or types of fruit in a bowl, to build confidence
    • 💡Always use a sharp pencil and ruler when creating charts, and clearly label axes or pictures with what they represent
    • 💡Double-check your counting by recounting or having a peer verify your tally before finalizing your presentation
    • 💡When making an observation, use comparative language like 'more than', 'less than', or 'the same as' to clearly communicate your finding
    • 💡Begin by clearly stating what you are measuring and how you will record responses.
    • 💡Use simple templates or pre-drawn grids to ensure neat and accurate charts.
    • 💡Always check that your observation is directly linked to the numbers in your chart or table.
    • 💡Always double-check tally counts before transferring data to charts
    • 💡Use a ruler and clear, consistent spacing when drawing bar charts
    • 💡When making an observation, refer back to the data, using phrases like 'the highest number is...' or 'more people chose... than...'
    • 💡When setting a goal, make sure it is SMART: Specific, Measurable, Achievable, Relevant, and Time-bound. For example, 'I will complete my maths worksheet in 15 minutes' is better than 'I will do some maths.'
    • 💡In the reflection section, use the 'What? So what? Now what?' framework: describe what you did, explain why it matters, and state what you will do next. This shows deeper thinking.
    • 💡For tasks involving instructions, read all steps first before starting. This helps you anticipate materials needed and avoid missing a step.

    Common Mistakes

    Common errors to avoid in your coursework

    • Students often confuse tally marks, failing to group in fives correctly, leading to miscounts and inaccurate totals.
    • When creating a bar chart, they may omit axis labels, use inconsistent scales, or draw bars of unequal width, making the presentation misleading or unclear.
    • Making observations that are not directly supported by the data, such as assuming causation or overgeneralising from a small sample, rather than sticking to factual statements about the presented information.
    • Miscounting when using tally marks, especially crossing the fifth line incorrectly.
    • Confusing the purpose of different chart types, such as using a bar chart for continuous data.
    • Failing to include a title or units on a graph or table.
    • Incorrectly using tally marks, e.g., counting each stroke in a five-bar gate as a separate item rather than representing a count of five.
    • Forgetting to label axes or images on a chart, leaving assessors unclear about what the data represents.
    • Stating an observation that is not borne out by the data, such as claiming a majority when the numbers show an equal split, or introducing personal bias rather than reporting factual findings.
    • Miscounting tally marks, especially when crossing groups of five, leading to inaccurate data.
    • Forgetting to include a title or axis labels when creating a chart, making the presentation unclear.
    • Making observations that are not directly supported by the data, such as assuming trends or reasons without evidence.
    • Confusing rows and columns when transferring data from a collection sheet to a presentation format.
    • Confusing tally marks by recording four vertical lines with a diagonal instead of a proper five-bar gate structure, leading to counting errors.
    • Failing to label charts or axes, making the presented information ambiguous for the reader.
    • Making observations that are not directly supported by the data, such as assuming a pattern without evidence or overgeneralising from a small sample.
    • Miscounting tallies due to rushing or not grouping items systematically, leading to inaccurate frequency totals.
    • Mislabeling or omitting labels on a chart, such as missing titles, axis labels, or a key for pictograms, making the presentation unclear.
    • Confusing the purpose of a pictogram by using inconsistent symbols or failing to state what each symbol represents.
    • Miscounting items when recording data, leading to inaccurate totals or representations.
    • Omitting labels or a title when creating a chart, making the presentation unclear.
    • Making an observation that does not directly relate to the data collected, such as stating a preference rather than a factual trend.
    • Learners may confuse tally marks (e.g., using four strokes instead of five for a gate).
    • Presenting data without a clear scale or axis labels, leading to ambiguity.
    • Making an observation that is not supported by the data or misinterpreting the chart.
    • Miscounting data when transferring from raw collection to presentation, leading to inaccuracies in charts or tables.
    • Failing to label the axes, bars, or sections of a chart, making the presented information unclear or incomplete.
    • Making observations that are not directly supported by the data, such as personal opinions rather than factual statements from the findings.
    • Confusing tally marks (e.g., incorrect grouping into fives) leading to inaccurate counts and misinterpretation.
    • Omitting essential chart components such as axis labels or a title, making the presentation unclear and difficult to understand.
    • Making observations that are not directly supported by the data, like overgeneralising or adding personal assumptions instead of referring strictly to the numbers.
    • Using inappropriate scales or inconsistent spacing when drawing bar charts manually, which distorts the visual representation.
    • Failing to label the axes or provide a title when presenting data graphically, which makes the chart unclear to an observer.
    • Miscounting tallies, leading to discrepancies between collected data and presented totals.
    • Choosing an inappropriate chart type (e.g., a line graph for categorical data), resulting in a misleading presentation.
    • Making observations that are not supported by the data, such as speculating about why a result occurred or drawing conclusions beyond the scope of the simple findings.
    • Inconsistent use of scales when constructing bar charts, causing visual distortion of the data.
    • Learners may miscount or lose track during tallying, especially when marks are not crossed off in groups of five.
    • Presenting information without any title or labels, making the chart or list meaningless to others.
    • Making observations that are not based on the collected data, such as stating preferences instead of numerical findings.
    • Confusing tally marks with numbers (e.g. treating a group of five as '5' instead of gate)
    • Omitting a title or labels on a chart, making the presentation unclear
    • Drawing bars of unequal width or not starting the bar chart axis at zero
    • Making an observation that does not relate to the data (e.g. personal opinion)
    • Counting errors when transferring tallies to a total
    • Forgetting to draw the fifth tally mark as a diagonal cross, leading to difficulties in counting by fives
    • Misinterpreting the key or scale on a pictogram, such as thinking one picture represents more than one item when it only represents one
    • Counting items inaccurately by skipping or repeating, often due to rushing or lack of systematic approach
    • Making an observation that is not supported by the data, such as stating an item is most frequent when another appears more often
    • Incorrect grouping of tally marks: using four vertical lines and a diagonal for five but continuing beyond without grouping in fives.
    • Mislabeling chart axes or omitting a chart title entirely.
    • Making subjective statements not supported by the data, e.g., ‘Everyone likes chocolate’ when the data shows otherwise.
    • Confusing tally marks with other counting symbols, leading to inaccurate totals
    • Failing to include a title or axis labels on charts, making data unclear
    • Making subjective or unsupported observations that do not reflect the actual data
    • Misconception: 'Reflection is just saying if you liked an activity or not.' Correction: Reflection involves evaluating your performance, identifying what you learned, and considering how to apply that learning in the future. It's about growth, not just enjoyment.
    • Misconception: 'Following instructions means you can't ask questions.' Correction: It's fine to ask for clarification if you're unsure. Good instruction-following includes checking your understanding to avoid mistakes.
    • Misconception: 'Goal setting is only for big projects.' Correction: Goals can be small and short-term, like finishing a worksheet in 20 minutes. Setting small goals helps build confidence and momentum.

    Frequently Asked Questions

    Common questions students ask about this topic

    Before You Start

    Prior knowledge that will help with this topic

    • •Basic literacy skills: Ability to read simple sentences and write short phrases.
    • •Basic numeracy skills: Counting, simple addition and subtraction, and understanding of money up to £20.
    • •Familiarity with following simple two-step instructions (e.g., 'Take out your book and turn to page 5').

    Key Terminology

    Essential terms to know

    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Data collection methods
    • Organising information
    • Simple data presentation
    • Interpreting findings
    • Real-world numeracy skills
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Be able to collect simple numerical information, Be able to present numerical information, Be able to make an observation about the findings
    • Simple data collection techniques
    • Presenting data in charts and tables
    • Making observations from data
    • Real-life application of numerical skills
    • Practical data collection
    • Tallying and counting
    • Simple data representation
    • Interpreting findings
    • Everyday life contexts
    • Tallying and data collection
    • Creating charts and tables
    • Interpreting simple data
    • Practical applications of data
    • Data collection techniques
    • Visual data presentation
    • Basic data analysis
    • Everyday numeracy application

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