Organise raw observations with tallies and frequencies
Count each observation once, keep labelled categories including zeros, and check a frequency table against the original list.
Exam scope and assessment notes
The first six lessons are shared Foundation work inherited by Higher; the last four are additional Higher histograms and cumulative-frequency work. Construct actual labelled diagrams with their scales, units and keys. Unequal continuous intervals need frequency density and area; partial-class and straight-guide readings are estimates, and a flat inverse can be an interval. Numerical agreement does not award marks or establish mastery; written explanations need human review. Statistical measures and probability remain separate. Linear November 2026/June 2027 entries and regional-centre eligibility differ from modular awards. Publisher map/contents are navigation only: F6.1Aii is a modular subpart, not the whole linear F6.1A row. Book1 Handling Data3 map398–428 differs from proof397/summary426/next428; Book2 Handling Data6 map208–222 differs from proof207/summary221/next222. Relevant chapter and Hub bodies remain unavailable; specialist and formal-assessment approval remain pending.
Before you begin
- Count a finite list systematically.
- Group whole numbers in fives and interpret a zero count.
- Distinguish a category label from a numerical frequency.
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
A table lists categories L, M and N. No observation belongs to M. What should its row contain?
What you will learn
- Choose clear category labels and assign each observation to exactly one row.
- Record readable tally groups of five and convert them to frequencies, retaining stated zero categories.
- Check the total and explain how the table supplies a labelled frequency display.
The complete raw list is B, A, C, D, C, A, B, C, A, D, C, B, A, C, D, B, C, A, B, C, A, D, C, B, A, C. Construct a table with columns Category, Tally and Frequency, using rows A, B, C, D in that order. Retain every stated category, check the total, and explain how the table would supply a correctly labelled bar chart.
Choose your representation, enter its actual categories, counts, geometry and labels, and explicitly record it. No table margin, scale, missing sector, density, cumulative point or reading trace is filled for you.
Original supplied data
Only literal data are supplied. A missing entry is displayed as not supplied; requested totals, frequencies, angles, density calibration, cumulative constructions and read-off traces are not generated on this board.
All metric panels in this board share one camera and equal Cartesian drawing units. Equal full widths, heights and pie radii therefore stay visibly comparable; no individual panel is independently fitted. Histogram numerical frequency density is its entered vertical calibration. Tables and tally strokes are symbolic displays.
No requested target representation has been supplied or recorded. Construct your own actual table, icons, bars, sectors, cumulative guide or reading trace.
Blue is supplied geometry, amber is my actual work, purple is dirty retained work and green is a separately gated reference. Rendering never repairs a wrong count, overlap, radius, calibration, cumulative decrease or read-off elbow. Tool coordinates are bounded to±1000000; finite unsupported portions are not silently clamped. Up to1000 explicit pictogram pieces and100 tally bundles per displayed row are rendered. Screen size is not physical instrument calibration. Readiness and fixed numerical comparison do not mark reasoning, award marks, prove mastery or provide teacher/specialist/formal-assessment approval.
Observed and whole-class counts stay distinct from within-class histogram or cumulative-guide estimates. A zero-frequency plateau can give an interval of inverse readings. No median, quartile, midpoint-mean or probability teaching credit is supplied by this display.
My complete labelled tally and frequency table
No actual representation is recorded for this action.
The board places only the coordinates you explicitly choose into the selected slot. It generates no other corner, bar, sector or reading elbow. Interval-area bounds are two measurements, not a planar point.
My quantities, conclusions and explanation
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Enter an exact fraction or finite decimal, with the precision and quantity unit explicitly requested in the question.
Explain the actual construction and its conditions. Text presence does not establish a correct argument.
These original fixed cases support self-checking. They do not mark proofs or written explanations, award marks or mastery, certify instrument accuracy, or provide specialist or formal assessment approval. Within-class histogram and cumulative-guide readings are estimates, while supplied whole-class counts remain exact. A plateau may give an interval rather than one inverse reading.
Choose rows before counting
A raw list records the observations one at a time. A category tells you what was observed; its frequency tells you how often it occurred. First write the stated categories as separate row labels. If the categories are ordered values, keep that order so a reader can distinguish an absent observation from an absent label.
Each observation must belong to exactly one category in this table. Read the list systematically, marking your place after each entry, rather than trying to recognise a whole cluster at a glance. A category that was specified but never occurs still needs a row with frequency zero. Do not quietly discard it or replace it by a blank meaning unknown.
Make the counting visible
Add one tally stroke to the appropriate row for every observation. Bundle each completed set of five so it can be recognised without recounting all the strokes. For a frequency f, the number of complete groups is the whole-number quotient on division by five, and the remaining strokes record the remainder.
Put the numerical frequency in its own column after checking the tallies. A tally bundle is a counting aid, not a different unit: one complete group still means five observations. Label the columns Category, Tally and Frequency. If a row is zero, write 0 in the frequency column and leave its tally area empty rather than drawing a fictitious mark.
Reconcile the table with the list
Add the frequencies and compare their sum with the number of original observations. Agreement is necessary, but it does not prove every category is right: moving one item to a wrong row can preserve the total. Recheck the category assignments as well as the addition, especially where similar labels or repeated values occur.
The checked table becomes a clear source for a later bar chart. Its row labels go along the category axis and its frequencies determine the bar tops on a uniformly calibrated count axis. A zero row remains a labelled category. Here the task is to organise and interpret the observations; a total or a neat table does not establish any average or probability calculation.
Sources for this lesson
- Pearson Mathematics A linear specification · Issue 2 · Foundation printed 24 / physical 30; Higher printed 39 / physical 45; inheritance printed 27 / physical 33
- Pearson 2026/2027 entry manual · centre regions physical 3; Mathematics A physical 25
- Pearson second-edition modular book/Hub map · literal navigation only · physical 7, 9, 11
Pause and explain
A row contains three complete tally groups of five and two further strokes. What is its frequency?
Worked example
The complete raw list is B, A, C, D, C, A, B, C, A, D, C, B, A, C, D, B, C, A, B, C, A, D, C, B, A, C. Construct a table with columns Category, Tally and Frequency, using rows A, B, C, D in that order. Retain every stated category, check the total, and explain how the table would supply a correctly labelled bar chart.
Show the worked solution
- Write one row for each stated category and scan the list once, adding each observation to its own row. Recounting by category gives A: 7; B: 6; C: 9; D: 4.
- Group the tally strokes in fives: A has 1 complete group of five and 2 extra strokes; B has 1 complete group of five and 1 extra stroke; C has 1 complete group of five and 4 extra strokes; D has 0 complete groups of five and 4 extra strokes. A zero row has no strokes and the frequency label 0.
- Add the numerical frequencies: 7 + 6 + 9 + 4=26, matching the 26 listed observations. Recheck the assignments as well as the sum so a swap between rows is not hidden by a matching total.
- Keep category labels A, B, C, D in the table. They would become the bar-chart categories, with frequencies 7, 6, 9, 4 on a consistently calibrated axis labelled Frequency; the table does not require an average or probability calculation.
Answer Frequencies in the stated order: A: 7; B: 6; C: 9; D: 4; total 26. Tally bundles are A: 1×5+2; B: 1×5+1; C: 1×5+4; D: 0×5+4. Retain every zero row. The checked labels and frequencies supply the categories and heights of a later bar chart.
Try a topic test
Choose Easy, Normal or Difficult. Save your answers and open worked review after finishing.
Test this topic →From guided practice to a new situation
Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.
The complete raw list is red, blue, green, red, blue, red, green, blue, red, red, blue, green, red, blue, green, red, blue, red, green, blue, red, red, green, blue. Construct a table with columns Category, Tally and Frequency, using rows red, blue, green in that order. Retain every stated category, check the total, and explain how the table would supply a correctly labelled bar chart.
Give me a hint
Mark each observation as you allocate it; a row can be present even when its final frequency is zero.
Compare my reasoning
- Write one row for each stated category and scan the list once, adding each observation to its own row. Recounting by category gives red: 10; blue: 8; green: 6.
- Group the tally strokes in fives: red has 2 complete groups of five and 0 extra strokes; blue has 1 complete group of five and 3 extra strokes; green has 1 complete group of five and 1 extra stroke. A zero row has no strokes and the frequency label 0.
- Add the numerical frequencies: 10 + 8 + 6=24, matching the 24 listed observations. Recheck the assignments as well as the sum so a swap between rows is not hidden by a matching total.
- Keep category labels red, blue, green in the table. They would become the bar-chart categories, with frequencies 10, 8, 6 on a consistently calibrated axis labelled Frequency; the table does not require an average or probability calculation.
Frequencies in the stated order: red: 10; blue: 8; green: 6; total 24. Tally bundles are red: 2×5+0; blue: 1×5+3; green: 1×5+1. Retain every zero row. The checked labels and frequencies supply the categories and heights of a later bar chart.
Look for these in your work
- Record every original observation once in the correctly labelled row.
- Show readable groups of five, numerical frequencies and any zero row.
- Check the original-list total and explain the category-to-bar connection.
The complete raw list is 2, 0, 1, 4, 2, 1, 0, 2, 4, 1, 2, 0, 1, 4, 2, 2, 1, 0, 4, 1, 2, 0, 1, 2. Construct a table with columns Category, Tally and Frequency, using rows 0, 1, 2, 3, 4 in that order. Retain every stated category, check the total, and explain how the table would supply a correctly labelled bar chart.
Give me a hint
Mark each observation as you allocate it; a row can be present even when its final frequency is zero.
Compare my reasoning
- Write one row for each stated category and scan the list once, adding each observation to its own row. Recounting by category gives 0: 5; 1: 7; 2: 8; 3: 0; 4: 4.
- Group the tally strokes in fives: 0 has 1 complete group of five and 0 extra strokes; 1 has 1 complete group of five and 2 extra strokes; 2 has 1 complete group of five and 3 extra strokes; 3 has 0 complete groups of five and 0 extra strokes; 4 has 0 complete groups of five and 4 extra strokes. A zero row has no strokes and the frequency label 0.
- Add the numerical frequencies: 5 + 7 + 8 + 0 + 4=24, matching the 24 listed observations. Recheck the assignments as well as the sum so a swap between rows is not hidden by a matching total.
- Keep category labels 0, 1, 2, 3, 4 in the table. They would become the bar-chart categories, with frequencies 5, 7, 8, 0, 4 on a consistently calibrated axis labelled Frequency; the table does not require an average or probability calculation.
Frequencies in the stated order: 0: 5; 1: 7; 2: 8; 3: 0; 4: 4; total 24. Tally bundles are 0: 1×5+0; 1: 1×5+2; 2: 1×5+3; 3: 0×5+0; 4: 0×5+4. Retain every zero row. The checked labels and frequencies supply the categories and heights of a later bar chart.
Look for these in your work
- Record every original observation once in the correctly labelled row.
- Show readable groups of five, numerical frequencies and any zero row.
- Check the original-list total and explain the category-to-bar connection.
The complete raw list is 0, 2, 1, 4, 2, 2, 0, 1, 4, 1, 2, 0, 4, 2, 1, 0, 2, 4, 1, 2. Construct a table with columns Category, Tally and Frequency, using rows 0, 1, 2, 3, 4 in that order. Retain every stated category, check the total, and explain how the table would supply a correctly labelled bar chart.
Give me a hint
Mark each observation as you allocate it; a row can be present even when its final frequency is zero.
Compare my reasoning
- Write one row for each stated category and scan the list once, adding each observation to its own row. Recounting by category gives 0: 4; 1: 5; 2: 7; 3: 0; 4: 4.
- Group the tally strokes in fives: 0 has 0 complete groups of five and 4 extra strokes; 1 has 1 complete group of five and 0 extra strokes; 2 has 1 complete group of five and 2 extra strokes; 3 has 0 complete groups of five and 0 extra strokes; 4 has 0 complete groups of five and 4 extra strokes. A zero row has no strokes and the frequency label 0.
- Add the numerical frequencies: 4 + 5 + 7 + 0 + 4=20, matching the 20 listed observations. Recheck the assignments as well as the sum so a swap between rows is not hidden by a matching total.
- Keep category labels 0, 1, 2, 3, 4 in the table. They would become the bar-chart categories, with frequencies 4, 5, 7, 0, 4 on a consistently calibrated axis labelled Frequency; the table does not require an average or probability calculation.
Frequencies in the stated order: 0: 4; 1: 5; 2: 7; 3: 0; 4: 4; total 20. Tally bundles are 0: 0×5+4; 1: 1×5+0; 2: 1×5+2; 3: 0×5+0; 4: 0×5+4. Retain every zero row. The checked labels and frequencies supply the categories and heights of a later bar chart.
Look for these in your work
- Record every original observation once in the correctly labelled row.
- Show readable groups of five, numerical frequencies and any zero row.
- Check the original-list total and explain the category-to-bar connection.
Common mistakes
- Dropping a stated category because its frequency is zero.
- Treating a group of five tally marks as one observation.
- Trusting a matching grand total without checking which row received each observation.
What can you explain now?
Why is a matching frequency total useful but insufficient to establish that every row is correct?
Compare with the explanation
It checks the number of observations, but two misclassified observations can leave the same total. The category assignments must also be checked.
The total detects losses or double counting in aggregate; it does not by itself verify which label received each item.
After trying it yourself, choose your next review. This is your self-assessment.
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Make it stick
Describe how you would check a raw list, tally column, zero row and frequency total before using the table to draw a bar chart.
If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.