NEB Class 12 • Mathematics • Statistics • Concept Guide
Karl Pearson & Spearman Correlation: NEB Class 12 Maths Guide
Master Karl Pearson and Spearman Correlation through clear concepts, representations, a reliable answer method and exam-focused practice.
Core concept
What Karl Pearson and Spearman Correlation means physically
Correlation quantifies association, not causation. Pearson measures linear association between numerical variables, while Spearman measures monotonic association through ranks and is less tied to linear scale.
Pearson r=Σ[(x−x̄)(y−ȳ)]/√[Σ(x−x̄)²Σ(y−ȳ)²]. Without ties, Spearman ρ=1−6Σd²/[n(n²−1)].
The institutional reference gives the wider physical model; the CDC curriculum determines the NEB boundary.
Worked checkpoint with interpretation
If two rankings of four students differ by squared-rank differences totaling 2, ρ=1−12/60=0.8.
Do not stop at the number. State what the sign, ratio, spacing, frequency or direction means. A common error is Claiming correlation proves cause, using Pearson for a strongly nonlinear pattern, mishandling tied ranks, or interpreting r=0 as no relationship of any kind.
NEB answer method
Model → evidence → equation → check
First identify the system and what the question asks. Label the diagram, apparatus or reaction with SI quantities, then state the principle before selecting an equation. Solve symbolically where possible and check units, limiting cases and chemical or physical meaning.
| Stage | Question | Evidence |
|---|---|---|
| Model | What is idealised? | Assumption stated |
| Representation | Which diagram fits? | Labels or balanced equation |
| Calculation | Which relation follows? | Symbols then SI values |
| Evaluation | Does it make sense? | Unit, sign and trend check |
Make the idea concrete in Nepal
Connect the model to a school laboratory, household technology, health, environment, energy or local material. The example should clarify the science rather than merely mention a place. Compare a prediction with an observation and record uncertainty.
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Frequently asked questions
Questions students ask about Karl Pearson and Spearman Correlation
Correlation quantifies association, not causation. Pearson measures linear association between numerical variables, while Spearman measures monotonic association through ranks and is less tied to linear scale.
Pearson r=Σ[(x−x̄)(y−ȳ)]/√[Σ(x−x̄)²Σ(y−ȳ)²]. Without ties, Spearman ρ=1−6Σd²/[n(n²−1)].
Draw the situation, list known quantities in SI units, choose the governing relation symbolically, substitute once and finish with a unit and reasonableness check.
Claiming correlation proves cause, using Pearson for a strongly nonlinear pattern, mishandling tied ranks, or interpreting r=0 as no relationship of any kind.
Alternate one concept explanation, one diagram and two numericals. Revisit errors after a day instead of only rereading the solution.
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References and next steps
Scope checked against CDC Nepal; concept support from an institutional reference and OpenStax Science. Continue with the Karl Pearson and Spearman Correlation cluster.
Ask about online or physical tuition
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