Estimated means and modal classes for grouped data
Estimate a grouped mean from class midpoints and identify full modal intervals, retaining ties and the limits of grouped data.
Exam scope and assessment notes
The first four lessons are shared Foundation work inherited by Higher; the last four are additional Higher spread, quartile and cumulative-frequency reading work. Keep the actual repeated observations and frequencies, state units, and distinguish an average from spread. Grouped midpoint means and within-class graph readings are estimates. The chosen discrete quartile rule is median of each half, excluding the overall middle observation when the count is odd; it is not claimed as a universal Pearson algorithm. Draw the horizontal and vertical guides yourself, use each graph’s own total, and retain a full plateau interval when an inverse is not unique. Fixed numerical agreement does not mark reasoning or award marks or mastery. Specialist and formal-assessment approval remain pending. This is the Issue 2 linear 4MA1 scope: November 2026/June 2027 entries and regional-centre eligibility differ from modular awards. Literal second-edition Book2 Handling Data4/5/6 and Hub tags guide navigation only; no Book1 6.2 tag or verified chapter/Hub body is inferred. Handling Data6 map208–222 conflicts with proof chapter207/summary221/next222; Handling Data4 map39–60 extends beyond summary59 before next61. Graphical representation6.1 and probability6.3 remain separate.
Before you begin
- Read class interval boundaries.
- Calculate a weighted total from frequencies.
- Find halfway values and retain units.
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
What is the midpoint of the finite class 2 ≤ x < 8?
What you will learn
- Form class midpoints and weighted midpoint totals.
- State a grouped mean as an estimate with units.
- Identify every highest-frequency modal interval and explain the information lost through grouping.
Grouped minutes data have these classes and frequencies: 0 ≤ x < 10: 3; 10 ≤ x < 20: 7; 20 ≤ x < 30: 6; 30 ≤ x < 40: 4. Estimate the mean using class midpoints and identify every modal class. Explain why the original exact mean is not determined.
Enter your own actual observations, positions, products, operations and guide endpoints. No count, total, role, result, quartile, graph height, unit or precision is filled for you. Recording is an attempt, not a correctness result.
Original supplied observations and tables
- lower
- 0
- upper
- 10
- lowerIncluded
- true
- upperIncluded
- false
- lower
- 10
- upper
- 20
- lowerIncluded
- true
- upperIncluded
- false
- lower
- 20
- upper
- 30
- lowerIncluded
- true
- upperIncluded
- false
- lower
- 30
- upper
- 40
- lowerIncluded
- true
- upperIncluded
- false
| Supplied class interval | Supplied frequency |
|---|---|
| 3 |
| 7 |
| 6 |
| 4 |
Original rows only. No total, product, cumulative count, midpoint or summary is inserted.
Only literal observations, frequencies, intervals and supplied cumulative guides are shown initially. The display does not sort observations, compute a total, average, quartile, rank or recovered value, or prefill a learner operation.
Blue denotes literal supplied guides, amber actual entered work, purple dirty retained work, and green a separately gated reference. Wrong and partial values are never repaired. The drawing bound is±1,000,000 coordinates, with at most512 scalar entries and128 cumulative points; these are tool bounds, not mathematical laws. Native clipping does not clamp values. No completed target is silently substituted.
The selected median-of-halves convention excludes the overall middle observation for odd lists. Grouped means and guide read-offs remain estimates. A zero-frequency plateau can give an interval rather than a unique reading. Fixed guide comparisons use the separate canonical700×500 policy with each source total; the tolerance is not a current-screen pixel or official marking tolerance. Text presence, operation consistency and numerical self-check do not approve reasoning, statistical claims, marks, mastery, teacher/specialist or formal assessment. No probability or new boxplot teaching credit is granted.
Enter actual midpoint/product rows and every modal interval, including endpoint conventions
No actual work is recorded for this action.
This is symbolic or one-dimensional work. These controls do not turn observation positions, row indices, extremes or interval boundaries into Cartesian points.
My quantities, conclusions and explanation
For a numerical list, use comma-separated values with no brackets or one balanced enclosing pair, or type none when you mean no mode. State the actual unit and exact, estimate or one-decimal-place precision yourself.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
A written attempt needs actual reasoning; text presence does not approve the argument.
A written attempt needs actual reasoning; text presence does not approve the argument.
These are original fixed cases for self-checking, not automatic marking, mastery or teacher/specialist/formal-assessment approval. The stated median-of-halves convention is a chosen convention. Grouped midpoint means and within-class CF readings remain estimates; a plateau can give a full interval. A physical instrument and calibrated graph are separate from the screen. No probability credit follows.
What a grouped table does and does not say
A grouped table tells you how many observations lie in each stated interval, but usually hides their individual values. Read the boundary convention carefully so neighboring classes do not overlap. For example, a lower boundary included and an upper boundary excluded places a shared boundary value in the next interval, not in both classes.
To represent an interval by one number, the midpoint is halfway between its two finite boundaries. This is a chosen representative for every member of that class, not a claim that every observation actually equals it. An open-ended interval has no determined midpoint, so this method needs more information or an explicitly justified extra assumption.
Build an estimated total before dividing
Calculate midpoint × frequency for each class and add these products. Divide by the total frequency to estimate the mean. The denominator counts observations, not classes; averaging the midpoints alone would wrongly give the same weight to a class with few observations and a class containing many.
Keep exact midpoint values and products until the final division or requested rounding. A midpoint and an estimated mean retain the original measurement unit. Because the real within-class positions are unknown, the resulting mean is generally an estimate even if the arithmetic produces a terminating decimal. A neat decimal is not evidence that the original total is known.
Identify the interval and explain uncertainty
For the equal-width grouped tables used here, identify the modal class by the greatest frequency and give its full interval label. If two classes tie for that greatest frequency, report both. The modal interval is a range of possible values; its midpoint is a representative number and is not a replacement for the requested class.
A histogram with unequal widths introduces a different height scale: frequency density rather than frequency. Do not choose the tallest drawn bar as a highest-frequency class without reading its scale and width. These tasks supply frequencies directly. They establish grouped mean estimation and modal classes, while histogram construction remains a separate graphical skill.
Sources for this lesson
- Pearson Mathematics A linear specification · Issue 2 · Foundation printed24/physical30; Higher printed39/physical45; inheritance printed27/physical33
- Pearson 2026/2027 entry manual · centre regions physical3; Mathematics A physical25
- Pearson second-edition modular book/Hub map · literal navigation only · physical9,10,11
Pause and explain
Why is a mean calculated from grouped midpoints usually an estimate?
Worked example
Grouped minutes data have these classes and frequencies: 0 ≤ x < 10: 3; 10 ≤ x < 20: 7; 20 ≤ x < 30: 6; 30 ≤ x < 40: 4. Estimate the mean using class midpoints and identify every modal class. Explain why the original exact mean is not determined.
Show the worked solution
- The class midpoints are 5, 15, 25, 35 minutes; use each midpoint for every member of its class.
- The frequency total is 20 and the midpoint × frequency total is 410. Estimated mean = 410/20 = 41/2 minutes.
- The greatest frequency selects 10 ≤ x < 20, so report that complete modal interval. Individual readings may move within their classes without changing the table; their original exact mean is therefore not determined by this information.
Answer Estimated mean = 20.5 minutes; modal class: 10 ≤ x < 20 (x in minutes). The midpoint-weighted total is 410 across 20 observations. The exact original mean is not determined.
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.
Grouped grams data have these classes and frequencies: 0 ≤ x < 5: 2; 5 ≤ x < 10: 6; 10 ≤ x < 15: 8; 15 ≤ x < 20: 4. Estimate the mean using class midpoints and identify every modal class. Explain why the original exact mean is not determined.
Give me a hint
Calculate one midpoint for each finite interval and weight it by its own frequency.
Compare my reasoning
- The class midpoints are 5/2, 15/2, 25/2, 35/2 grams; use each midpoint for every member of its class.
- The frequency total is 20 and the midpoint × frequency total is 220. Estimated mean = 220/20 = 11 grams.
- The greatest frequency selects 10 ≤ x < 15, so report that complete modal interval. Individual readings may move within their classes without changing the table; their original exact mean is therefore not determined by this information.
Estimated mean = 11 grams; modal class: 10 ≤ x < 15 (x in grams). The midpoint-weighted total is 220 across 20 observations. The exact original mean is not determined.
Look for these in your work
- Use every frequency with its midpoint.
- State the result as an estimate with units.
- Give every highest-frequency interval, not just its midpoint.
Grouped degrees Celsius data have these classes and frequencies: -10 ≤ x < 0: 4; 0 ≤ x < 10: 7; 10 ≤ x < 20: 5. Estimate the mean using class midpoints and identify every modal class. Explain why the original exact mean is not determined.
Give me a hint
Keep the negative class midpoint and the shared-boundary convention straight.
Compare my reasoning
- The class midpoints are -5, 5, 15 degrees Celsius; use each midpoint for every member of its class.
- The frequency total is 16 and the midpoint × frequency total is 90. Estimated mean = 90/16 = 45/8 degrees Celsius.
- The greatest frequency selects 0 ≤ x < 10, so report that complete modal interval. Individual readings may move within their classes without changing the table; their original exact mean is therefore not determined by this information.
Estimated mean = 5.625 degrees Celsius; modal class: 0 ≤ x < 10 (x in degrees Celsius). The midpoint-weighted total is 90 across 16 observations. The exact original mean is not determined.
Look for these in your work
- Use every frequency with its midpoint.
- State the result as an estimate with units.
- Give every highest-frequency interval, not just its midpoint.
Grouped cm data have these classes and frequencies: 20 ≤ x < 30: 5; 30 ≤ x < 40: 9; 40 ≤ x < 50: 9; 50 ≤ x < 60: 2. Estimate the mean using class midpoints and identify every modal class. Explain why the original exact mean is not determined.
Give me a hint
Retain both highest-frequency intervals if they tie, and explain why the original exact mean is not recoverable.
Compare my reasoning
- The class midpoints are 25, 35, 45, 55 cm; use each midpoint for every member of its class.
- The frequency total is 25 and the midpoint × frequency total is 955. Estimated mean = 955/25 = 191/5 cm.
- The greatest frequency selects 30 ≤ x < 40 and 40 ≤ x < 50, so report both complete modal intervals. Individual readings may move within their classes without changing the table; their original exact mean is therefore not determined by this information.
Estimated mean = 38.2 cm; modal classes: 30 ≤ x < 40 and 40 ≤ x < 50 (x in cm). The midpoint-weighted total is 955 across 25 observations. The exact original mean is not determined.
Look for these in your work
- Use every frequency with its midpoint.
- State the result as an estimate with units.
- Give every highest-frequency interval, not just its midpoint.
Common mistakes
- Averaging class midpoints without their frequencies.
- Calling the midpoint estimate the exact mean of the hidden individual readings.
- Giving a midpoint instead of the modal interval or discarding a tie.
What can you explain now?
If two equal-width classes share the largest frequency, what should be reported as the modal class?
Compare with the explanation
Report both complete class intervals as tied modal classes.
A tie in frequency does not justify choosing the earlier interval or replacing the pair by an invented middle class.
After trying it yourself, choose your next review. This is your self-assessment.
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Make it stick
Explain the distinction between a boundary, midpoint, frequency, estimated mean and modal interval, including what grouping leaves unknown.
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.