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Year 11 · ICT · Autumn 2 · Paper 2 practice: documents, databases, presentations

Charts, proofing and evidence

Exam practicePresent ▶

What this lesson covers

16.2 Label and format a chart

Cambridge IGCSE ICT 0417 · Topic 16: Graphs and charts

15.2 Verification and proofreading

Cambridge IGCSE ICT 0417 · Topic 15: Proofing

11.1 Manage files effectively

Cambridge IGCSE ICT 0417 · Topic 11: File management

You will learn to

  • Add a chart title, axis titles, category labels, data labels and a legend, as instructed.
  • Identify consistency errors in a document: spacing, fonts, alignment and blank pages.
  • Create an evidence document where every screenshot is readable and labelled.
  • Correct a set of near-miss answers so each would earn the mark.

Success criteria

  • I can check a chart against a list and find what is missing.
  • I can fix every near-miss in the set.
  • I can show evidence screenshots that are cropped, readable and labelled.
The syllabus points for these sections
  • Add a chart title, legend, axis titles and category labels.
  • Add data labels as values or percentages.
  • Format numbers with decimal places and currency.
  • Set axis minimum, maximum and increments.
  • Describe visual verification and double data entry.
  • Spot transposition, spelling, spacing and case errors.
  • Explain the difference between validation and verification.
  • Proofread layout: spacing, blank pages, widows and orphans, split tables and lists.
  • Locate, open and import files of different types.
  • Save files in a planned folder structure with meaningful file names.
  • Save and export in application formats and generic formats.
  • Describe what each common file format is for.
  • Explain why generic file formats are needed.

Key words

Say each word, then read what it means. Every one is in the glossary too.

Chart
A picture of data, such as bars, lines or slices, that makes patterns easy to see.
Pie chart
A circle split into slices, each showing a part of the whole.
Bar chart
Bars of different lengths for comparing categories; vertical bars are also called a column chart.
Line graph
Points joined by lines to show change over time.
Data series
One set of values plotted on a chart.
Legend
The key that says what each colour or pattern on a chart means.
Axis title
Text naming what an axis measures, with its units.
Category labels
The names along the category axis, such as months or products.
Data label
A value or percentage shown on a bar, point or slice.
Axis minimum / maximum
The lowest and highest values shown on the value axis.
Increment (major unit)
The step between values on an axis, such as every 10.
Proofing
Checking work for errors before it is used or printed.
Spell check
A tool that compares words with a stored dictionary and flags unknown ones.
Validation
An automatic check by the computer that data is sensible and follows set rules.
Verification
A check that data has been copied accurately from its source.
Visual verification
A person compares entered data with the source document by eye.
Double data entry
Data is typed twice and the computer compares the two versions.
Source document
The original document the data is taken from, such as a paper form.
Transposition error
Two characters swapped round, such as 54 typed as 45.
Range check
Validation that a value lies between a lowest and highest value.
Presence check
Validation that a field has not been left empty.
Format check
Validation that data matches a set pattern, such as DD/MM/YYYY.
Check digit
An extra digit calculated from the other digits, used to detect input errors.
Widow
The last line of a paragraph left alone at the top of a new page.
Orphan
The first line of a paragraph left alone at the bottom of a page.
Proofreading
Reading a document carefully to find errors in text and layout.
File
A named block of data stored on a disk, such as a document or photo.
Folder
A container that holds files and other folders.
File extension
The letters after the dot in a file name, showing the file type.
Import
Bring data from a file of one type into another application.
Export
Save a copy of a file in a different format.
Folder structure
The planned arrangement of folders inside each other.
Application-specific format
A file format made for one type of software, keeping all its features.
Generic format
A file format that many different programs can open.
CSV
Comma separated values: table data stored as plain text with commas between fields.
RTF
Rich text format: text with basic formatting that most word processors can open.
PDF
Portable document format: a fixed-layout document that looks the same on any device.
Compression
Making a file smaller by storing its data more efficiently.
Archive
A single file, such as .zip or .rar, holding one or more compressed files.
Lossless compression
Compression where no data is lost, so the original is restored exactly.
Lossy compression
Compression that removes some data permanently to make the file much smaller.

The explanation

Read it here, or open the study page below to go one step at a time with things to try.

What good evidence looks like

Evidence is how you prove your work. It is often screenshots in an evidence document.

  • One screenshot for each thing the paper asks for.
  • Crop it so the important setting is large enough to read.
  • Label it with the task and step number.
  • Show the whole setting: every field type, every query criterion, every style setting.
!Watch out

If the examiner cannot read it, it cannot earn a mark. Zoom in or crop before you paste.

The final check routine

Run this check before you save for the last time.

ItemCheck
ChartsTitle, axis titles, category labels, and a legend only if the task asks for one.
DocumentsSame spacing and fonts throughout. No blank pages. No widows, orphans or split tables.
ReportsOnly the fields asked for, in the order asked for. Every value fully visible.
PrintoutsYour name, centre number and candidate number on every one.
FilesSaved with the exact names and formats asked for.
★Remember

Most practical marks are lost to small slips, not hard skills. A checklist catches them.

16.2 Label and format a chart

Titles, axis titles and labels

Chart title: says what the chart shows. Type it exactly as the task gives it.

Axis titles: name what each axis measures, with units, such as "Number of hires" or "Price (€)".

Category labels (axis labels): the names along the axis, such as Road, Mountain, Electric. All must be fully visible.

e.g.Example
Vertical bar chart: Title: Bike Hire in May Category axis title: Bike type Value axis title: Number of hires Category labels: Road, Mountain, Electric
!Watch out

Category labels that are cut off or overlap lose the mark. Make the chart wider or rotate the labels so every word shows in full.

Legend: show it or hide it

A legend is the key that says what each colour means.

With one data series in a bar chart, a legend adds nothing, so tasks often say "do not display a legend".

With two or more series, or in a pie chart without category labels on the slices, the legend is needed.

?Why?

Every item on a chart should help the reader. A legend that says only "Series1" confuses.

!Watch out

A legend showing "Series1" means the data was selected without its header. Reselect including the header cell, or rename the series.

Data labels: values and percentages

Data labels show the number on each bar or slice.

A task may say "show the values" or "show the percentages". On a pie chart you can show the category name and the percentage on each slice.

Values are the raw numbers. Percentages are each value as a share of the total.

e.g.Example
Task: Display the percentage and category name for each segment. Result on slices: Road 30%, Mountain 20%, Electric 50%.
!Watch out

Showing values when the task said percentages, or both when it said one, loses the mark.

Number format, axis scale and increments

Format value axis numbers as asked: decimal places, or currency, such as €0.00.

The axis minimum and maximum set where the value axis starts and ends. The increment (major unit) is the step between gridlines, such as every 10.

A typical task: "Set the value axis from 0 to 200 with increments of 25."

e.g.Example
Hires range from 60 to 150. Task: minimum 0, maximum 160, increment 20. Axis reads 0, 20, 40, 60, 80, 100, 120, 140, 160. Check: 160 ÷ 20 = 8 steps, so 9 labels.
?Why?

Starting the axis at 0 shows differences fairly. Starting at 50 would make 60 look tiny next to 150, which misleads the reader.

!Watch out

The software picks automatic values. If the task gives numbers, you must type them in. The automatic value is almost never what Cambridge asks for.

15.2 Verification and proofreading

Verification: is it the same as the source?

Verification checks that data has been copied or typed accurately from the source document. The source is the original, such as a paper form.

There are two methods. Visual verification: a person compares the entered data with the source by eye. Double data entry: the data is typed twice, and the computer compares the two versions.

If the two versions differ, the computer flags the item so a person can check it.

e.g.Example
Double data entry of a phone number: First entry: 612 345 678 Second entry: 612 354 678 The computer finds a mismatch, so the operator checks the paper form and corrects it.
?Why?

Validation cannot know what the source said. Only comparing with the source, by eye or by a second typing, can catch a sensible but wrong value.

!Watch out

Double data entry does not mean typing it twice and seeing if it "looks right". The computer compares the two entries character by character.

Errors to look for in a visual check

Transposition: two characters swapped, such as 1945 typed as 1954, or "form" for "from".

Spelling: a letter missing, added or wrong.

Consistent spacing: one space between words, the same gap after every full stop.

Consistent case: capital letters exactly as in the source, such as "Madrid" not "madrid".

e.g.Example
Source: Order 4521, Calle de Alcalá 28, MADRID Typed: Order 4512, Calle de alcalá 28, MADRID Errors: 4521 → 4512 (transposition), alcalá (case), two spaces before MADRID (spacing).
?Why?

These are exactly the slips a spell check and validation both miss. A careful eye finds them.

Try it: verify or validate?

Use the toy. In part 1, fix the second entry so the double entry check passes. In part 2, tap each field on screen that is different from the paper form.

In part 3, type marks and see the range check. Notice which errors each method catches.

Look for a value that passes validation but is still wrong, such as 76 typed for 67.

?Why?

Seeing a wrong but sensible value pass validation is the best way to remember why both checks are needed.

There is something to try for this step in the IGCSE library.

Validation vs verification

Validation asks: is this data reasonable? It is done by the computer, using rules.

Verification asks: is this data the same as the source? It compares with the original.

A system uses both. Neither one proves the data is true. A form filled in wrongly by the customer passes both.

ValidationVerification
Question it answersIs the data sensible and allowed?Was the data copied accurately?
Who or what does itThe computer, automaticallyA person (visual) or the computer comparing two entries
MethodsRange, length, type, format, presence, check digitVisual check, double data entry
CatchesImpossible values, wrong format, empty fieldsTyping errors, transpositions
MissesWrong but sensible valuesErrors already on the source document
!Watch out

Saying "validation checks the data is correct" loses the mark. Use the word sensible or reasonable for validation and accurately copied for verification.

Proofread the layout

Open print preview and check every page.

Consistent line spacing and paragraph spacing throughout. No blank pages, often caused by extra Enters or a stray page break at the end.

No widows or orphans. A widow is the last line of a paragraph alone at the top of a page. An orphan is the first line of a paragraph alone at the bottom of a page.

Tables and lists not split across pages, unless they are too long to fit on one page.

?Why?

Widows, orphans and split tables break the reader's flow and look careless. Cambridge mark schemes give a mark for a layout free of them.

!Watch out

Turn on widow and orphan control in the paragraph settings. Use keep with next for a heading, so it never sits alone at the bottom of a page above its text.

A proofing routine for the practical exam

1. Run spell check with English (UK). Judge each suggestion. Keep names from the source.

2. Compare every piece of text you typed with the question paper, word by word.

3. Turn on formatting marks. Look for double spaces and extra blank lines.

4. Print preview every page: spacing, blank pages, widows and orphans, split tables, header and footer on every page.

!Watch out

How candidates lose marks: accepting a wrong spell-check suggestion for a name; a transposed number in a table; a blank last page; a heading stranded at the bottom of a page; a table or bulleted list split over two pages; extra blank lines between some paragraphs only.

11.1 Manage files effectively

Files, folders and file extensions

A file is a named block of data stored on a disk: a document, a photo, a spreadsheet.

A folder (directory) is a container that holds files and other folders.

A file extension is the short code after the dot in a file name, such as .docx or .jpg. It tells the computer which kind of data the file holds and which software opens it.

e.g.Example
File name: Y10_Trip_Letter.docx Name part: Y10_Trip_Letter Extension: .docx (a word-processed document)
!Watch out

Many computers hide extensions by default. In the exam you often need to see them, so switch on 'show file extensions' in the file manager before you start.

Locate, open and import files

In the exam, Cambridge supplies source files, for example a .csv of data, a .txt of text and some images.

Open a file to work on it in its own application, such as a spreadsheet opening a .xlsx file.

Import means bringing data from one file type into another application, such as importing a .csv file into a database table, or placing a .png image into a document.

When importing a .csv, check the field names come from the first row and the data types are correct.

e.g.Example
Task: 'Import the file STOCK.CSV into a new database table. Use the first row as field names.' Steps in most databases: External data → Text file → choose STOCK.CSV → delimited by commas → tick 'first row contains field names' → set data types → finish.
!Watch out

Do not open a source file and retype the data. Importing is quicker and avoids typing errors that lose accuracy marks.

A planned folder structure

A folder structure is the way folders are arranged inside each other, like branches on a tree.

Plan folders by subject, project or date so related files are kept together.

A clear structure makes files quick to find, easy to back up and easy to share.

e.g.Example
Exam work for one candidate: P2_Candidate_0417 Evidence Database Document Presentation Source_files (originals, not edited)
?Why?

If everything sits in one folder, it takes longer to find files, and it is easy to overwrite the wrong one.

Meaningful file names

A meaningful file name tells you what is inside without opening the file.

Good names are short but clear and may include a date or version number. Avoid spaces or symbols that some systems do not accept. Use _ or - instead.

In the exam, use exactly the file name the question asks for. If it says 'save as JOURNAL', the file must be named JOURNAL.

Poor nameBetter nameWhy it is better
doc1.docxY10_Trip_Letter_v2.docxSays what it is and which version
final final NEW.xlsxBudget_2026-11.xlsxClear content and date; no spaces
IMG_4821.jpgScience_Fair_Stand.jpgDescribes the picture
!Watch out

Saving with the wrong name, or in the wrong place, means the examiner may not find or credit your work.

Application formats and generic formats

An application-specific format (proprietary format) is designed for one type of software. It keeps every feature: formulas, styles, layout, macros. Examples: .docx, .xlsx, .pptx, .accdb.

A generic format can be opened by many different programs on any operating system. It may lose some features. Examples: .csv, .txt, .rtf, .pdf, .htm, .css, .jpg, .png, .gif, .zip.

Save keeps the work in the application's own format. Export (or 'Save as' another type) writes a copy in a different format.

e.g.Example
Try the toy. For each extension, choose what it is for, then say if it is generic or application-specific. Hint: .rtf, .csv and .pdf are generic. .xlsx and .accdb are application-specific.
?Why?

Generic formats matter because the person receiving the file may not have the same software. A .csv from any spreadsheet can be read by every database. A .pdf looks the same on any device.

There is something to try for this step in the IGCSE library.

Generic file formats you must know

Cambridge lists these generic formats. Learn what each one is for.

Text-type formats come first, then web formats, then images, then compressed files.

ExtensionFull nameWhat it is and when to use it
.csvComma separated valuesTable data as plain text, one record per line, fields separated by commas. Moves data between spreadsheets and databases. No formatting or formulas.
.txtTextPlain text only: letters, numbers, spaces. No fonts, bold or images. Opens on any computer.
.rtfRich text formatText with basic formatting: fonts, bold, italic, sizes, alignment. Opens in almost any word processor.
.pdfPortable document formatA fixed page that looks the same on any device and printer. Hard to edit. Good for final documents, forms and printing.
.htm / .htmlHypertext markup languageA web page. Opened by any web browser.
.cssCascading stylesheetStyle rules (colours, fonts, layout) for web pages. Linked from .htm files.
.jpg / .jpegJoint Photographic Experts GroupPhotos. Lossy compression gives small files with millions of colours. Some quality is lost.
.pngPortable network graphicsImages with lossless compression and transparent backgrounds. Good for logos, diagrams and screenshots.
.gifGraphics interchange formatSimple images and short animations. Only 256 colours. Supports transparency.
.zipZip (compressed archive)One or more files compressed into one smaller file, for storing or sending.

Application-specific formats

These keep everything the software can do, so you use them while working on a file.

In the exam, save in the application format when told to, so the work can be edited later.

ExtensionSoftware typeWhat it keeps
.docxWord processorStyles, headers and footers, tables, images, page layout
.xlsxSpreadsheetFormulas, functions, several sheets, formatting, charts
.accdbDatabaseTables, relationships, queries, forms, reports
.pptxPresentationSlides, master slide, transitions, animations, speaker notes
.odt / .ods / .odpFree office software (OpenDocument)The same features for open-source office programs
!Watch out

Saving a spreadsheet as .csv keeps only the values of the current sheet. All formulas, formatting and other sheets are lost. Keep a .xlsx copy too.

Choosing the right format

Ask three questions: who will open it, will they need to edit it, and what must be kept?

Use a generic format when the reader's software is unknown. Use an application format when you, or someone with the same software, will keep editing.

SituationBest formatReason
Send a final newsletter that must look identical everywhere.pdfFixed layout; opens on any device; hard to change
Move a list of members from a spreadsheet to a database.csvPlain table data any database can import
Logo with a transparent background for a website.pngLossless and supports transparency
Holiday photo for a website.jpgSmall file size, good enough quality for photos
Letter someone else will edit in a different word processor.rtfKeeps basic formatting and opens in most word processors
Spreadsheet you are still building.xlsxKeeps formulas and formatting

Study it

Open the study page and go one step at a time.

Check yourself

One question at a time. The reason shows after each answer.

Saved on this device.