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Class 9 · Mathematics

Chapter 10: How Quantities Combine: Understanding Data

Revision notes, worked problems, a question bank, assertion and reason questions and answers to the NCERT exercises. Tap a group to open it; opening one closes the others.

10.1Averages that combineWeighted mean

Average of averages

  • Wrong: average of 165.5 and 149.33 (seniors, juniors) = 157.4. It treats 8 seniors and 3 juniors as equal.
  • Right: (165.5 × 8 + 149.33 × 3) ÷ 11 = 1772 ÷ 11 = 161.09.
  • For collections of sizes n and m with averages a and b: combined average = (an + bm) ÷ (n + m).
  • If the sizes are equal (Jaspreet’s 5 days × 3 weeks), simply average the averages: (a + b + c) ÷ 3.

Weighted mean

  • For values x₁, x₂, …, xₙ with weights w₁, w₂, …, wₙ: x̄ = (w₁x₁ + w₂x₂ + … + wₙxₙ) ÷ (w₁ + w₂ + … + wₙ).
  • Weights may be counts, quantities, or importance (ratio 3 : 2 : 5).
  • Brahmagupta (c. 628 CE) used it for the mean depth of a pit; Śrīdhara (c. 750 CE) for the purity of gold alloys (varṇa; 16 varṇa = 24 karat).
  • Doubling all weights leaves the weighted mean unchanged.
10.2MixturesConcentration of a mixture

Concentration

0%10%20%30%500 mL, 10%200 mL, 20%≈ 12.9% (closer to 10%)
Example 4: the mixture lies between 10% and 20%, closer to the end with more lemonade.
  • Concentration = quantity of the substance ÷ quantity of the mixture.
  • Equal quantities: 10% and 20% give 15%, midway.
  • Unequal: 500 mL at 10% and 200 mL at 20%: (500 × 0.1 + 200 × 0.2) ÷ 700 = 90 ÷ 700 ≈ 12.9%.
  • The mixture always lies between the lowest and highest concentrations, nearer the one with more quantity. Hence you can never get a value outside that range by mixing.

Worked example

  • Brass: 200 kg at 70% copper, 120 kg at 50%, y kg at 45%; the mixture is 55% copper.
  • 0.55(320 + y) = 140 + 60 + 0.45y gives 0.1y = 24, so y = 240 kg.
10.3Custom weightsWeighting by importance

Marks in ratio 3 : 2 : 5

  • Rehmat: 60%, 64%, 73%. Equal weights give 65.6%, which is wrong for this scheme.
  • With weights 3 : 2 : 5: (60 × 3 + 64 × 2 + 73 × 5) ÷ 10 = 67.3%.
  • For marks out of different totals, convert each to a percentage first (35/50 = 70%).
  • Rating of an eatery: food 5, service 3, ambience 4 with weights 4 : 3 : 2 gives (20 + 9 + 8) ÷ 9 = 4.11.

Adding one more value

  • New mean after one more value v: (old mean × n + v) ÷ (n + 1).
  • Stork: 20 days at 44.5 km, day 21 is 55 km: (890 + 55) ÷ 21 = 45 km. The new value barely moves a mean built from many values.
10.4Stacked barsTotals and components

Stacked bar chart

Family A19401700128012001770Family B17501546150012801210Family C950170015401400130002000400060008000HousingFoodEducationTransportHealthcareRecreation
Fig. 10.2: stacked bars: the full length is each family’s total (A 8425, B 7286, C 7040).
  • Cluster-column charts compare parts; a stacked bar joins the parts so the full length shows the total.
  • Use it when totals matter and you also want to see the components.
  • Weakness: apart from the first segment, bars do not start from 0, so comparing individual segments is harder.

100% stacked bar

Family A23%20%15%14%21%Family B24%21%21%18%17%Family C13%24%22%20%18%0%25%50%75%100%HousingFoodEducationTransportHealthcareRecreation
Fig. 10.4: a 100% stacked bar: every bar has the same length, so only shares are compared.
  • Every bar has the same length (100%), so shares are compared, not amounts. It is like a pie chart but lengths are easier to compare than angles.
  • From a stacked bar chart you can build the 100% chart, but not the other way round (totals are lost).
  • Electricity 2005 (total 1000): 36%, 30%, 12%, 22%; 2025 (total 2000): 11%, 40%, 23%, 26%.

What can we infer?

Fatima50%30%20%Naveen40%25%35%0%25%50%75%100%SummerMonsoonWinter
Example 8: shares only. Totals are unknown.
Fatima1056342Naveen483042050100150200SummerMonsoonWinter
Case 1: Fatima 210 flowers, Naveen 120. Same 100% bars as before.
Fatima905436Naveen966084050100150200250SummerMonsoonWinter
Case 2: Fatima 180 flowers, Naveen 240. Naveen now has more summer blooms.
  • Within one bar: compare shares (Fatima had more blooms in summer than monsoon).
  • Across bars: cannot compare numbers (Case 1: Fatima has more summer blooms; Case 2: Naveen has more) and cannot tell which total is bigger.
  • A single bar can be read both as a stacked and as a 100% stacked bar. Averages hide differences, so split data (for example by age group) to see patterns.