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Collecting, analysing and communicating data - Computing Year 6

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Introduction

Turn a small dataset into an honest, useful explanation. You will ask a clear question, preserve raw records, resolve documented data problems, calculate a total and mean, and present a labelled chart with a conclusion that fits the evidence.

Your project: A short report on five invented daily rainfall readings. Use a teacher-approved spreadsheet or other suitable data tool, followed by a brief document or slide. No real pupil information or online account is needed. Paper calculations support understanding; digital data handling and chart creation require an actual saved artefact when assessed as practical work.

Starting question: In this fictional five-day record at one location, how much rain was recorded in total, what was the mean daily amount, and how did the readings vary? This question concerns the supplied record, not a whole country's climate or a forecast.

The Year 6 allocation is editorial within England's key stage 2 computing. You will connect data handling with mathematical reasoning and communication. A correct-looking formula cannot rescue an undefined question or silently corrupted data.

Ask a question and clean records with evidence

Define the fields before collecting or analysing. A record is one observation, such as one day's rainfall at the stated place. A field is one item within a record: day identifier, day label or rainfall amount. Use a consistent unit, millimetres, and identify each intended observation uniquely.

Our fictional notebook has five daily observation cards: D1 Monday 4 mm, D2 Tuesday 0 mm, D3 Wednesday 6 mm, D4 Thursday 8 mm and D5 Friday 2 mm. These are invented complete records for this exercise. They are the checking source for the deliberately untidy transcription below.

Record ID	Day	Transcribed rainfall in mm
D1	Monday	4
D2	Tuesday	0
D2	Tuesday	0
D3	Wednesday	six
D4	Thursday	missing
D5	Friday	2

Keep this raw table unchanged in a separate sheet or saved copy. Make a cleaned table and a change log rather than overwriting the only evidence of what arrived.

Resolve a problem using evidence

D2 appears twice with the same intended observation identifier. The fictional notebook contains only one D2 record, so the second transcription is a confirmed duplicate. Remove it from the analysis table and record why. Two different days with equal rainfall would not be duplicates merely because their numbers match.
D3 contains the word six instead of a numeric value. The notebook confirms 6 mm, so enter numeric 6 in the cleaned table. Do not assume all arbitrary words can be converted safely.
D4 is missing in the transcription. The notebook supplies 8 mm, so restore that documented reading and cite the checking source. Without that source, mark it missing and investigate; do not invent a value.

Zero is data, not absence. Tuesday's recorded 0 mm means no rain was recorded for that observation. A missing Thursday value would mean the amount is unknown. Replacing unknown with zero changes the meaning and can change the mean.

The cleaned table has exactly five unique IDs and five numeric values in the declared unit. Check for impossible negative rainfall, inconsistent units, unexpected dates and transcription errors before calculating. An unusual value is a reason to verify the source, not automatic permission to delete it.

Calculate and check a total and arithmetic mean

Calculate from the cleaned records and retain the unit. Arrange the following table with Day in spreadsheet cell A1 and Rainfall_mm in B1. Put the five labels in A2:A6 and the numeric readings in B2:B6. Do not type mm into those numeric cells; keep the unit in the heading.

Day	Rainfall_mm
Monday	4
Tuesday	0
Wednesday	6
Thursday	8
Friday	2

The total is $4 + 0 + 6 + 8 + 2 = 20$ mm across the five recorded days. The arithmetic mean divides the total by the number of daily observations: $20 / 5 = 4$ mm per day. Tuesday's zero is one of the five observations and belongs in the denominator.

Use a spreadsheet without losing the reasoning

In a tool using English function names, place =SUM(B2:B6) in a separate summary cell to calculate 20, and =AVERAGE(B2:B6) in another summary cell to calculate 4. The colon selects the inclusive range from B2 to B6. A formula starts with an equals sign. Your teacher can identify equivalent function names in a localised application.

Before trusting the displayed answer, check that all five intended cells contain numbers, that the range includes Tuesday's zero and that no summary row is included. These formulas are not data-quality checks. For example, AVERAGE in Excel ignores blank or text cells in a referenced range while including numeric zero. A missing observation can therefore disappear from the denominator rather than visibly announce itself.

Diagnostic comparison: If Tuesday's genuine zero is incorrectly omitted, the remaining total is still 20, but four observations produce mean 5. The unchanged total does not prove the mean is correct. If Thursday were unknown rather than restored from the notebook, the four known values would total 12 and average 3; that would describe only those four known observations, not a completed five-day record.

The mean does not mean it rained 4 mm every day. Only Monday equals 4; other readings are 0, 6, 8 and 2. A summary number compresses information, so keep the table or chart available to show variation.

See how an arithmetic mean is formed

Khan Academy's original introduction compares mean, median and mode. Focus first on the arithmetic mean: add values and divide by how many observations there are. Pause and explain why our zero still counts. Median and mode are optional extension topics here; do not substitute them for the mean requested by the project question.

Represent the five observations honestly

Choose a representation for the question. A table is useful for exact values. A line chart can show the sequence of five daily readings. A bar chart can also compare the daily amounts clearly. Neither chart type makes the data more reliable by itself.

For this project, make a simple line chart or bar chart from the five daily rows only. Keep the days in chronological order, even if sorting by rainfall would make a dramatic shape. Give it the title Fictional rainfall at one location over five days. Label the horizontal axis Day and the vertical axis Rainfall in mm.

Use an honest readable scale, such as 0 to 10 mm with equal 2 mm intervals. Plot Monday 4, Tuesday 0, Wednesday 6, Thursday 8 and Friday 2. On a line chart, joining the daily points helps follow the order; it does not add measured readings between the observations.

Keep summaries out of the daily series

The total 20 is not a sixth day's rainfall. The mean 4 is not another day either. Put summary figures in separate cells and exclude them from the selected daily chart range. Otherwise a large Total bar or an invented Mean day can mislead the reader about what was observed.

If the chart unexpectedly shows six or seven categories, inspect the selected range and category labels. If a day has vanished, check whether its value is stored as text or missing. If Tuesday appears as a gap rather than a zero-height bar or zero-level point, inspect how the tool handles the zero and the cell's actual content.

Fehler beim Erstellen des Vorschaubildes:

A generic bar chart illustrates categories, axes and a scale. It is not the five-day rainfall chart; compare its design features with the labelled chart you create.

Misleading-scale comparison: Imagine two bars of 6 and 8 mm. On an axis starting at zero, their heights represent those amounts. If the visible axis starts at 5, their visible lengths become 1 and 3 units above that starting point, making the difference look much more dramatic. For our simple amount comparison, keep a zero baseline. Other chart contexts may justify a nonzero scale, but the chosen scale must be clear and interpreted honestly.

Do not rely only on colour. Use written day labels and, where helpful, markers or value labels. Include the data table or a short textual summary so a reader who cannot inspect the chart still receives the important information. Decoration should not obscure the values or imply a precision the readings do not support.

Communicate conclusions within the evidence

A conclusion should answer the question at the scale of the evidence. A useful statement is: In this invented five-day record at one location, the total rainfall was 20 mm and the mean was 4 mm per recorded day. Thursday had the highest reading, 8 mm, and Tuesday the lowest, 0 mm.

The difference between the highest and lowest is $8 - 0 = 8$ mm. This range describes the spread of these five values, not measurement accuracy. The record does not establish a long-term climate pattern, explain the cause of the rain or predict the next day's reading.

Build an evidence-based report

State the precise question, location scope and five-day observation period. Identify the dataset as fictional.
Include the cleaned five-row table, retaining the raw transcription separately.
Explain the duplicate, word-to-number correction and restored missing value, with the provided notebook as evidence.
Show total and mean, units, count and the selected spreadsheet ranges.
Add a labelled chart of the five daily observations, excluding summary figures.
Write one supported conclusion and at least one limitation.

Keep the numerical analysis in a suitable data tool and present the result in a short document or slide for the intended audience. Check that the chart and report use the same cleaned version. If you change a reading in a copy for a transfer task, label the new version and update every related figure rather than mixing old and new results.

Transfer example: Suppose a separate corrected notebook version confirms Friday should be 7 instead of 2. In that explicitly changed dataset, total becomes 25 and mean becomes 5. The chart's Friday point or bar must change too. Do not silently replace the original exercise record; explain the new evidence and retain the earlier version.

Review the work as another reader

Ask a peer to answer: How many days are included? What does the unit mean? Is Tuesday zero or unknown? Which changes came from evidence? Does the mean describe each day? Can the conclusion be supported without a claim about future weather?

For a real collection project, agree on the question, observation method, unit and recording schedule with the teacher first. Avoid collecting personal data when it is unnecessary. A small convenient sample may not represent a wider population, and a measurement can contain error even when the spreadsheet accepts it as a number. This course's invented record demonstrates a method; it does not supply real meteorological evidence.

Evidence check: Save the analysis file and the report, reproduce one calculation independently and explain one chart choice. Knowledge activities support understanding; a practical data-handling claim also needs the actual digital artefacts and a check that their values agree.

Interactive Tasks

Quiz: Test Your Knowledge

Why define a question before analysing data? (It determines which observations and comparisons are relevant) (!It guarantees every available number is correct) (!It removes the need to state units) (!It makes the largest chart automatically the best)

What distinguishes Tuesday's recorded zero from a missing reading? (Zero records an amount of no rain; missing means the amount is unknown) (!They always have exactly the same meaning) (!A zero observation must be removed from the mean) (!Missing always proves the amount was zero)

Why can the second D2 row be removed in this exercise? (The checking notebook confirms that it repeats the same intended observation) (!Any two equal numeric values are always duplicates) (!Every zero is an accidental row) (!Removing rows always improves a chart)

What is the total of the cleaned readings 4, 0, 6, 8 and 2 mm? (20 mm) (!4 mm) (!5 mm) (!12 mm)

What is the mean daily amount for the five cleaned readings? (4 mm per recorded day) (!20 mm per recorded day) (!5 mm per recorded day) (!8 mm on every day)

What happens if Tuesday's genuine zero is incorrectly omitted from the mean? (The total stays 20 but dividing by four gives 5) (!The mean remains 4 because zero never counts) (!The total becomes 12 and the mean becomes 3) (!The dataset becomes a complete six-day record)

Which rows belong in the chart's daily observation series? (The five day rows without the total or mean summary cells) (!The five days plus an invented Total day) (!Only the day with the highest rainfall) (!The mean repeated as every day's measured amount)

Which conclusion is supported by this fictional record? (Thursday has the highest of the five supplied daily readings) (!It will certainly rain 8 mm next Thursday) (!The record proves a long-term national climate trend) (!Every day had exactly the mean amount)

What should you do if a missing value has no reliable checking source? (Retain it as missing and investigate or state the limitation) (!Invent a plausible value without saying so) (!Replace it with zero automatically) (!Copy the highest value to improve the result)

Why keep a clear zero baseline for the simple bar comparison in this project? (Visible bar lengths then represent the compared amounts without a truncated starting point) (!It makes all bars equal in height) (!It proves the observations are error-free) (!It removes the need for labels and units)

Memory Game

Record	One observation such as a single day's reading
Field	One item of information within a record
Raw data	The received observations preserved before cleaning
Mean	Total divided by the number of included observations
Unit	The measurement scale label such as millimetres
Limitation	A reason the evidence does not support a wider claim

Drag and Drop

Duplicate D2	Remove the repeated observation only after checking its identity
Word six	Use the notebook to enter the confirmed numeric value 6
Missing D4	Restore 8 only because the provided checking source confirms it
Recorded zero	Keep Tuesday as a valid observation in the count
Total summary	Place it outside the chart's five daily categories

Crossword Puzzle

MEAN	Total divided by the number of observations
AXIS	A labelled chart line with positions or values
RECORD	One observation stored as a row
SAMPLE	A selected set of observations rather than every possible one
UNIT	The label telling what a measured number represents
DUPLICATE	A repeated copy of the same intended observation

LearningApps

Optional extra practice. Choose an appropriate activity with your teacher. If the external collection is unavailable, use the native activities and independent tasks in this course.

Cloze Text

Open Tasks

Easy

Data fields and units: Name a record, a field and a unit in the rainfall table. Solution: Monday's observation is one record; rainfall amount is a field; millimetres are the measurement unit.
Zero versus missing data: Explain Tuesday's zero and Thursday's missing transcription. Solution: zero is a recorded amount, while missing is unknown until checked; Thursday can be restored to 8 only from the supplied notebook.
Rainfall total calculation: Add the cleaned five readings and retain the unit. Solution: 4 + 0 + 6 + 8 + 2 = 20 mm. Show the addition rather than only the answer.
Mean interpretation: Explain why mean 4 does not mean every day recorded 4. Solution: 4 is total 20 divided by five observations; the actual values vary from 0 to 8.

Standard

Evidence-based data cleaning: Create a cleaned table and a change log from the raw transcription. Solution: keep D1 4, one D2 0, D3 6, D4 8 and D5 2; explain the confirmed duplicate and both notebook-based corrections, retaining the original raw table.
Spreadsheet total and mean: Enter the cleaned data with headings in row 1 and numeric amounts in B2:B6. Use summary cells for total and mean, then check by hand. Expected: 20 and 4. Record the actual formulas and results from your approved tool; paper work alone leaves the digital part pending.
Honest daily chart: Make a line or bar chart of the five daily rows, with chronological labels, title and mm axis. Solution guide: values 4, 0, 6, 8, 2; use an appropriate clear scale such as 0 to 10; exclude total and mean as categories.
Supported rainfall conclusion: Write two supported observations and one limitation. Solution example: total 20 mm, Thursday highest at 8 mm; only five fictional days at one location are represented, so no long-term climate or future-weather claim follows.

Advanced

The omitted-zero mean error: Compare the correct mean with the mean after incorrectly removing Tuesday. Solution: total stays 20, but the correct five-observation mean is 4 and the four-observation calculation is 5. Explain why an unchanged total does not validate the denominator.
Unknown observation limitation: Without the notebook's Thursday reading, calculate the total and mean of the four known values and state the scope. Solution: 4, 0, 6 and 2 total 12 and average 3; this is only the known four-observation subset, not a completed five-day record.
Corrected-source transfer: In a separately labelled version, an authoritative exercise correction changes Friday from 2 to 7. Update the table, summaries, chart and conclusion. Solution: total 25, mean 5; Friday rises to 7 and Thursday remains highest at 8. Preserve the earlier version and log the reason.
Chart and analysis quality review: Ask a peer to inspect the saved data file and report. Check units, selected ranges, duplicate handling, zero, chart categories and claim limits. Solution guide: correct the first identified mismatch with evidence, update all linked outputs and distinguish verified changes from guesses.

Learning Check

Cleaning decisions assessment: Explain the three changes needed in the raw rainfall transcription and why they are justified.
Rainfall arithmetic assessment: Calculate total, mean and range for 4, 0, 6, 8, 2 with correct interpretation.
Missing and zero assessment: Explain the error caused by omitting the genuine zero, and why an unknown reading cannot simply become zero.
Chart choice assessment: Describe an appropriate chart and identify two misleading choices to avoid.
Digital report assessment: Submit the raw and cleaned records, change log, actual calculation file, chart and short evidence-based report.
Proportional conclusion assessment: Write one conclusion and two limits for the supplied dataset.

Worked checks and assessment guidance

Remove the second D2 because the notebook confirms one intended D2 observation; enter numeric 6 for D3 and restore 8 for D4 from that source. Keep the raw copy and log each change. Equal values on different observation IDs would not by themselves justify deletion.
Total 20 mm across five days; mean 20 divided by 5 = 4 mm per recorded day; range 8 minus 0 = 8 mm. The mean is not every individual reading and the range is not a measure of instrument accuracy.
Omitting Tuesday changes the count from five to four while total stays 20, yielding 5 instead of 4. Unknown rainfall has no confirmed amount; replacing it with zero invents an observation and changes the analysis.
Use five chronological daily observations in a labelled line or bar chart, with mm units and an honest scale. Avoid including total or mean as extra days, truncating the simple amount-comparison baseline to exaggerate differences, or dropping Tuesday's zero. Retain accessible labels or a table.
Check five unique IDs, five numeric values, consistent units, summary results 20 and 4, and matching chart/report versions. Require actual saved digital work for the practical objective; paper calculations show reasoning but do not alone establish tool use.
Thursday is highest among these five readings and Tuesday lowest; total is 20 mm. The data are fictional and cover only five days at one location, so they provide neither real meteorological evidence nor a long-term climate or next-day prediction.

Learning evidence

Knowledge: Explain record, field, unit, duplicate, zero versus missing, total, mean and a chart's scale.

Data product: Retain raw records and submit a cleaned five-row dataset with a justified change log.

Practical analysis: Save an actual calculation file with the stated data range and summary results; independently verify the arithmetic. Produce a labelled chart from the five observation rows only.

Communication: Present a short report with a supported conclusion, an accessible table or summary, and a limitation. Confirm that all artefacts use the same data version.

Completion distinction: Native quiz points and paper calculations support knowledge evidence. The digital objective additionally requires the actual data file, chart and report. No real pupil data or real-world weather claim is required.

OER and Wikipedia

Department for Education: Computing programmes of study, key stage 2. Collecting, analysing, evaluating and presenting data using suitable software inform this editorial Year 6 sequence. The rainfall notebook, transcription, corrections, chart brief and report examples are original fictional teaching data.

Software reference: The Document Foundation: SUM function and Microsoft Support: AVERAGE function. The latter documents the distinction between numeric zero and ignored blank/text cells in a referenced range. English function examples illustrate the workflow; use the approved tool's localised equivalent when needed. No paid product or account is required.

Diagrams, unmodified: Simple bar chart, Masur, public domain as declared on the file page; Bar chart, Cuvwb, CC BY-SA 4.0. Both are generic chart examples, not the course rainfall record.

Video: Statistics intro: Mean, median, and mode, Khan Academy, original publisher's YouTube embed. Focus on arithmetic mean; the other measures are optional extension. No film copy or adaptation is supplied.