Inverse square proportion and original exclusions
An inverse-square law retains a denominator exclusion and can recover opposite input signs. Keep those two facts separate when calibrating, solving and applying a model.
Exam scope and assessment notes
Original eight-family variation expansion: eight lessons,32 original cases and every Worked,Guided,Independent and application stage for each enumerated direct/inverse linear,square,cube and principal-root form. Together with the original general variation introduction,all nine complete same-record teaching/worked/practice bundles are required for one structural4Glink. Calibrate from original observations using actual reversible coefficient-equation operations;retain signed coefficients,the complete natural and stated domain,exact rational/simple-root predictions,all distinct admitted recoveries and their original-law returns,changed input and baseline values,ratio availability and coefficient dimensions. Both learner working and separately entered final answers begin blank;neither repairs the other. Edits,removed rows,withdrawal,reset and source/session/stage/revision changes revoke previous comparisons and references. A complete wrong attempt can study its explanation without passing. These construction cases use identified nonzero rational coefficients and nonzero rational calibration bases;origin ambiguity and zero-coefficient distinctions are taught explicitly,while more general symbolic forms need review. Software bounds are not syllabus exclusions. Written formulas,derivations,whole-domain arguments,unit prose and empirical model validity need human review. All14Functions source rows have reviewed structural teaching/practice links;other Mathematics B source gaps remain explicit in the current course map. The wider Pearson curriculum remains incomplete. Automated controls and initial/completed rendering are checked;fresh mounted-browser and hosted four-stage interaction remain unverified. ISBN9780435044107 is metadata only;no full book body,chapter or Hub mapping is verified. Single Higher-tier linear4MB1,entry context2026/27only;no MathematicsA,Foundation,modular or later-series inheritance. No official marks,mastery,specialist approval or formal assessment readiness.
Before you begin
- The original general variation-law introduction
- Signed rational arithmetic,integer powers and the required real root
- Original domain,interval endpoints and dependent/input units
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
Has the proportional family been stipulated before its coefficient is calibrated?
What you will learn
- Derive the stipulated reciprocal-square model from an admitted original observation using explicit equation operations.
- Use the original natural and stated domain for exact predictions and complete real recoveries.
- Check each recovered input in the original proportional basis and keep the coefficient dimensions.
- Distinguish a valid numerical change ratio,an excluded original input change and an unavailable zero baseline.
Inverse square: y = k/x²: Worked
This is an abstract real-variable law on its natural domain; no additional practical restriction is imposed. The stipulated law is inverse square proportion with unknown coefficient k: y=k*(1/x^2). The observation x=4 gives y=3. Prediction inputs: 2, 0, -4. Recover original inputs for outputs 12, 0, -3. Multiply the original input 4 by -1/2. Evaluate the proportional basis at the observed input, write the substituted coefficient equation and show each reversible operation. Then complete every exact prediction, full recovery list, original-law return check and change-ratio decision before entering separate answers.
Stipulated family: Inverse square: y = k/x². Original observations: input 4 gives output 3.
Stated restriction: (-inf,inf). Retain the original denominator and principal-root restrictions too.
Predict outputs at 2, 0, -4. Recover all allowed inputs for outputs 12, 0, -3. Multiply original input 4 by -1/2. Input unit: none; output unit: none.
How to enter my mathematical working
Use k for the coefficient and * for multiplication. Begin calibration with the original substituted equation, then add each equation operation. Enter exact fractions, sqrt(...) or cbrt(...) rather than rounded values. Write sets as (-inf,inf), [0,2), or intervals joined by U. Use none for an empty set, unavailable value or absent unit. Add one finite recovery row per candidate; zero rows means no candidates.
Coefficient dimensions use the output unit multiplied by the input unit to your entered exponent. A change ratio needs two admitted inputs and a nonzero initial output. The working and separate-answer panels stay independent.
My actual working
Current entries need recording.
My separate final answer
My separate final answer
Current entries need recording.
Record your current original calibration,domain,predictions,recoveries and change working.
Scope of this self-check
All mathematical fields and equation/candidate rows begin blank. The task supplies only original observations,requested inputs/outputs,units,restrictions and a stipulated family.
The student’s actual coefficient-equation steps,original domain,predictions,complete recovery candidates and original-rule returns,change working and coefficient dimensions are checked separately from independent answers.
Edits,row removal,withdrawal,reset,stage changes and original-source/session/generation/revision changes withhold earlier comparisons and explained references. Removed dependent row contents are discarded.
A complete incorrect attempt can study its explained reference without passing. These fixed comparisons do not approve written formulas,derivations,whole-domain arguments,unit prose,empirical validity,marks,mastery,specialist review or formal assessment readiness.
Read the denominator and the coefficient sign
Write y=k/x^2 with x different from zero. The squared basis 1/x^2 is positive at every admitted real input, so the output has the sign of k. The square does not make the denominator-zero input valid.
On the unrestricted abstract domain, opposite nonzero inputs give the same output. A physical distance model may use only the positive branch, but that is a separately stated restriction.
Find k from the whole squared input
For observation a,b, substitute b=k/a^2 and multiply both sides by a^2. Equivalently, divide b by the original nonzero reciprocal-square basis. Evaluate the square before applying a negative coefficient or observation sign.
A zero input cannot be used as an original calibration. Keep the denominator condition after rearranging x^2y=k or simplifying any algebraic expression. A rearranged equation does not silently define a new original function.
Recover all real candidates, then filter
With nonzero k and requested output b, b=0 has no recovery. Otherwise form x^2=k/b. A positive quotient gives two real candidates, zero would require special coefficient assumptions absent here, and a negative quotient gives no real candidate.
Return both real candidates through the original rule and apply its stated interval. The positive signal-distance model keeps only admitted positive inputs up to six units. The examples are invented calibrations, not evidence for a real measured inverse-square law.
Use the inverse-square change rule only on an allowed journey
For an admitted nonzero multiplier a, the output factor is 1/a^2. Negative a can preserve the abstract formula domain but can violate a positive practical restriction. If a=0, the changed input is excluded and there is no original-model change ratio.
The coefficient dimension is output-unit times input-unit squared. A matching unit pattern and calibration do not establish experimental validity or permission to extrapolate outside the operating interval.
Sources for this lesson
Pause and explain
Can an algebraic rearrangement or a correct separate answer replace the original-domain and actual-work checks?
Worked example
This is an abstract real-variable law on its natural domain; no additional practical restriction is imposed. The stipulated law is inverse square proportion with unknown coefficient k: y=k*(1/x^2). The observation x=4 gives y=3. Prediction inputs: 2, 0, -4. Recover original inputs for outputs 12, 0, -3. Multiply the original input 4 by -1/2. Evaluate the proportional basis at the observed input, write the substituted coefficient equation and show each reversible operation. Then complete every exact prediction, full recovery list, original-law return check and change-ratio decision before entering separate answers.
Show the worked solution
- Use y=k*(1/x^2) on (-inf,0) U (0,inf). The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions.
- At x=4, the proportional basis is 1/16. The observation gives 3=k*(1/16). Divide both sides by the nonzero basis 1/16 to obtain k=48.
- Thus y=(48)*(1/x^2) on that original domain. Changing the original domain would change the task.
- Prediction at x=2: y=12.
- Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it.
- Prediction at x=-4: y=3.
- For y=12, real algebraic candidates are -2, 2; the complete original-domain recovery set is -2, 2. Check each retained candidate in the original rule.
- Original-law return at x=-2: its proportional basis is 1/4, so y=(48)*(1/4)=12. This input satisfies every original natural and stated restriction.
- Original-law return at x=2: its proportional basis is 1/4, so y=(48)*(1/4)=12. This input satisfies every original natural and stated restriction.
- For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- For y=-3, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- Changing x from 4 to -2 changes the original outputs from 3 to 12. The exact numerical output ratio is 4.
- The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Both variables are dimensionless in this abstract task.
Answer Use y=k*(1/x^2) on (-inf,0) U (0,inf). The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions. At x=4, the proportional basis is 1/16. The observation gives 3=k*(1/16). Divide both sides by the nonzero basis 1/16 to obtain k=48. Thus y=(48)*(1/x^2) on that original domain. Changing the original domain would change the task. Prediction at x=2: y=12. Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it. Prediction at x=-4: y=3. For y=12, real algebraic candidates are -2, 2; the complete original-domain recovery set is -2, 2. Check each retained candidate in the original rule. Original-law return at x=-2: its proportional basis is 1/4, so y=(48)*(1/4)=12. This input satisfies every original natural and stated restriction. Original-law return at x=2: its proportional basis is 1/4, so y=(48)*(1/4)=12. This input satisfies every original natural and stated restriction. For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. For y=-3, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. Changing x from 4 to -2 changes the original outputs from 3 to 12. The exact numerical output ratio is 4. The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Both variables are dimensionless in this abstract task. The law, coefficient, original domain, exact predictions, complete recoveries, input change and coefficient dimensions describe different parts of this same original model. Written derivation,whole-domain reasoning,unit prose and empirical validity require human review. No marks,mastery,specialist or formal assessment approval is inferred.
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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.
This is an abstract real-variable law on its natural domain; no additional practical restriction is imposed. The stipulated law is inverse square proportion with unknown coefficient k: y=k*(1/x^2). The observation x=-3 gives y=-2. Prediction inputs: -6, 0, 3. Recover original inputs for outputs -2, 0, 2. Multiply the original input -3 by -2. First state the original real input set. Compute your observed basis and show the coefficient equation operations. For each recovery, check every sign or root against the original rule. Complete the change and coefficient-unit fields yourself; no numerical answer is supplied.
Give me a hint
Use the family’s stated proportional basis. Evaluate it at the original observation,show each reversible coefficient operation,retain natural and stated domains,then check every recovery and the numerical ratio conditions.
Compare my reasoning
- Use y=k*(1/x^2) on (-inf,0) U (0,inf). The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions.
- At x=-3, the proportional basis is 1/9. The observation gives -2=k*(1/9). Divide both sides by the nonzero basis 1/9 to obtain k=-18.
- Thus y=(-18)*(1/x^2) on that original domain. Changing the original domain would change the task.
- Prediction at x=-6: y=-1/2.
- Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it.
- Prediction at x=3: y=-2.
- For y=-2, real algebraic candidates are -3, 3; the complete original-domain recovery set is -3, 3. Check each retained candidate in the original rule.
- Original-law return at x=-3: its proportional basis is 1/9, so y=(-18)*(1/9)=-2. This input satisfies every original natural and stated restriction.
- Original-law return at x=3: its proportional basis is 1/9, so y=(-18)*(1/9)=-2. This input satisfies every original natural and stated restriction.
- For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- For y=2, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- Changing x from -3 to 6 changes the original outputs from -2 to -1/2. The exact numerical output ratio is 1/4.
- The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Both variables are dimensionless in this abstract task.
Use y=k*(1/x^2) on (-inf,0) U (0,inf). The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions. At x=-3, the proportional basis is 1/9. The observation gives -2=k*(1/9). Divide both sides by the nonzero basis 1/9 to obtain k=-18. Thus y=(-18)*(1/x^2) on that original domain. Changing the original domain would change the task. Prediction at x=-6: y=-1/2. Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it. Prediction at x=3: y=-2. For y=-2, real algebraic candidates are -3, 3; the complete original-domain recovery set is -3, 3. Check each retained candidate in the original rule. Original-law return at x=-3: its proportional basis is 1/9, so y=(-18)*(1/9)=-2. This input satisfies every original natural and stated restriction. Original-law return at x=3: its proportional basis is 1/9, so y=(-18)*(1/9)=-2. This input satisfies every original natural and stated restriction. For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. For y=2, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. Changing x from -3 to 6 changes the original outputs from -2 to -1/2. The exact numerical output ratio is 1/4. The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Both variables are dimensionless in this abstract task. The law, coefficient, original domain, exact predictions, complete recoveries, input change and coefficient dimensions describe different parts of this same original model. Written derivation,whole-domain reasoning,unit prose and empirical validity require human review. No marks,mastery,specialist or formal assessment approval is inferred.
Look for these in your work
- My original observation,basis and actual coefficient-equation operations are explicit.
- I retain the complete original domain and every permitted exact recovery,with return checks.
- My change uses both original inputs and distinguishes an excluded journey from a zero baseline.
- My coefficient dimensions use the original input and output units.
- My independent final values cannot repair incorrect own working;written arguments and model validity remain for human review.
This is an abstract real-variable law on its natural domain; no additional practical restriction is imposed. The stipulated law is inverse square proportion with unknown coefficient k: y=k*(1/x^2). The observation x=5 gives y=1/2. Prediction inputs: 1/2, 0, -5. Recover original inputs for outputs 25/4, 0, -1. Multiply the original input 5 by 0. Derive the model and original domain, then calculate every named exact prediction, complete recovery set and change ratio with its actual working. Enter the final formula, values, domains and coefficient dimensions independently.
Give me a hint
Use the family’s stated proportional basis. Evaluate it at the original observation,show each reversible coefficient operation,retain natural and stated domains,then check every recovery and the numerical ratio conditions.
Compare my reasoning
- Use y=k*(1/x^2) on (-inf,0) U (0,inf). The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions.
- At x=5, the proportional basis is 1/25. The observation gives 1/2=k*(1/25). Divide both sides by the nonzero basis 1/25 to obtain k=25/2.
- Thus y=(25/2)*(1/x^2) on that original domain. Changing the original domain would change the task.
- Prediction at x=1/2: y=50.
- Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it.
- Prediction at x=-5: y=1/2.
- For y=25/4, real algebraic candidates are (-1)*sqrt(2), (1)*sqrt(2); the complete original-domain recovery set is (-1)*sqrt(2), (1)*sqrt(2). Check each retained candidate in the original rule.
- Original-law return at x=(-1)*sqrt(2): its proportional basis is 1/2, so y=(25/2)*(1/2)=25/4. This input satisfies every original natural and stated restriction.
- Original-law return at x=(1)*sqrt(2): its proportional basis is 1/2, so y=(25/2)*(1/2)=25/4. This input satisfies every original natural and stated restriction.
- For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- For y=-1, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- Changing x from 5 to 0 changes the original outputs from 1/2 to not assigned. No numerical output ratio is available: outside-original-domain.
- The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Both variables are dimensionless in this abstract task.
Use y=k*(1/x^2) on (-inf,0) U (0,inf). The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions. At x=5, the proportional basis is 1/25. The observation gives 1/2=k*(1/25). Divide both sides by the nonzero basis 1/25 to obtain k=25/2. Thus y=(25/2)*(1/x^2) on that original domain. Changing the original domain would change the task. Prediction at x=1/2: y=50. Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it. Prediction at x=-5: y=1/2. For y=25/4, real algebraic candidates are (-1)*sqrt(2), (1)*sqrt(2); the complete original-domain recovery set is (-1)*sqrt(2), (1)*sqrt(2). Check each retained candidate in the original rule. Original-law return at x=(-1)*sqrt(2): its proportional basis is 1/2, so y=(25/2)*(1/2)=25/4. This input satisfies every original natural and stated restriction. Original-law return at x=(1)*sqrt(2): its proportional basis is 1/2, so y=(25/2)*(1/2)=25/4. This input satisfies every original natural and stated restriction. For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. For y=-1, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. Changing x from 5 to 0 changes the original outputs from 1/2 to not assigned. No numerical output ratio is available: outside-original-domain. The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Both variables are dimensionless in this abstract task. The law, coefficient, original domain, exact predictions, complete recoveries, input change and coefficient dimensions describe different parts of this same original model. Written derivation,whole-domain reasoning,unit prose and empirical validity require human review. No marks,mastery,specialist or formal assessment approval is inferred.
Look for these in your work
- My original observation,basis and actual coefficient-equation operations are explicit.
- I retain the complete original domain and every permitted exact recovery,with return checks.
- My change uses both original inputs and distinguishes an excluded journey from a zero baseline.
- My coefficient dimensions use the original input and output units.
- My independent final values cannot repair incorrect own working;written arguments and model validity remain for human review.
An invented signal calibration stipulates an inverse-square response at positive distance settings up to six units. No measured device law is being claimed. The stipulated law is inverse square proportion with unknown coefficient k: y=k*(1/x^2). The observation x=3 gives y=8. Prediction inputs: 2, 0, 8. Recover original inputs for outputs 18, 0, -2. Multiply the original input 3 by 2. Retain the stipulated operating interval as well as the natural reciprocal or principal-root conditions. Derive the coefficient with units and distinguish excluded model inputs from non-real expressions. Complete original predictions, all permitted recoveries and the stated change; explain the model limits.
Give me a hint
Use the family’s stated proportional basis. Evaluate it at the original observation,show each reversible coefficient operation,retain natural and stated domains,then check every recovery and the numerical ratio conditions.
Compare my reasoning
- Use y=k*(1/x^2) on (0,6]. The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions.
- At x=3, the proportional basis is 1/9. The observation gives 8=k*(1/9). Divide both sides by the nonzero basis 1/9 to obtain k=72.
- Thus y=(72)*(1/x^2) on that original domain. Changing the original domain would change the task.
- Prediction at x=2: y=18.
- Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it.
- Prediction at x=8: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it.
- For y=18, real algebraic candidates are -2, 2; the complete original-domain recovery set is 2. Check each retained candidate in the original rule.
- Original-law return at x=2: its proportional basis is 1/4, so y=(72)*(1/4)=18. This input satisfies every original natural and stated restriction.
- For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- For y=-2, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule.
- Changing x from 3 to 6 changes the original outputs from 8 to 2. The exact numerical output ratio is 1/4.
- The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Original units are signal units and distance units.
- The operating interval is a model assumption. A correct calibration or numerical fit does not establish a real device,price,staffing or experimental law. Keep the physical interpretation and any continuous-versus-discrete assumption explicit.
Use y=k*(1/x^2) on (0,6]. The original domain includes the stipulated restriction as well as natural reciprocal or principal-root conditions. At x=3, the proportional basis is 1/9. The observation gives 8=k*(1/9). Divide both sides by the nonzero basis 1/9 to obtain k=72. Thus y=(72)*(1/x^2) on that original domain. Changing the original domain would change the task. Prediction at x=2: y=18. Prediction at x=0: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it. Prediction at x=8: no value is assigned by the original allowed model. This input is excluded by a natural reciprocal/principal-root condition or the stated original model restriction;an algebraic extension does not authorise it. For y=18, real algebraic candidates are -2, 2; the complete original-domain recovery set is 2. Check each retained candidate in the original rule. Original-law return at x=2: its proportional basis is 1/4, so y=(72)*(1/4)=18. This input satisfies every original natural and stated restriction. For y=0, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. For y=-2, real algebraic candidates are none; the complete original-domain recovery set is empty. Check each retained candidate in the original rule. Changing x from 3 to 6 changes the original outputs from 8 to 2. The exact numerical output ratio is 1/4. The coefficient dimension is the output unit multiplied by the input unit to exponent 2. Original units are signal units and distance units. The operating interval is a model assumption. A correct calibration or numerical fit does not establish a real device,price,staffing or experimental law. Keep the physical interpretation and any continuous-versus-discrete assumption explicit. The law, coefficient, original domain, exact predictions, complete recoveries, input change and coefficient dimensions describe different parts of this same original model. Written derivation,whole-domain reasoning,unit prose and empirical validity require human review. No marks,mastery,specialist or formal assessment approval is inferred.
Look for these in your work
- My original observation,basis and actual coefficient-equation operations are explicit.
- I retain the complete original domain and every permitted exact recovery,with return checks.
- My change uses both original inputs and distinguishes an excluded journey from a zero baseline.
- My coefficient dimensions use the original input and output units.
- My independent final values cannot repair incorrect own working;written arguments and model validity remain for human review.
Common mistakes
- Treating a squared denominator as allowing input zero.
- Using only the principal positive recovery on an unrestricted domain.
- Assuming an abstract output must be positive when k is negative.
- Assigning an infinite numerical ratio to a forbidden zero-input change.
What can you explain now?
Can an algebraic rearrangement or a correct separate answer replace the original-domain and actual-work checks?
Compare with the explanation
No.
Retain the original law and every stated restriction;independent answers do not supply the learner’s missing or incorrect construction.
After trying it yourself, choose your next review. This is your self-assessment.
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Make it stick
State this family’s original input domain,derive its calibration equation,explain its complete recovery rule and give its allowed change factor. Keep actual units and numerical-ratio conditions separate. Fixed checks do not establish marks,mastery,empirical validity,specialist review or formal assessment readiness.
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.