Every district leader already knows which students are struggling. The problem isn't instinct — it's that instinct doesn't scale, and by the time report cards confirm it, the window to act has closed.
Policy by the Numbers hands education leaders a real, working predictive model — built entirely from data districts already collect — that flags at-risk students while there's still time to help them. No data science team required, no black-box software, no jargon you can't repeat to a school board.
The book follows Sagebrush Valley, a composite district, from a three-week data-cleanup sprint to a fully funded, board-approved intervention, then follows that same discipline outward: scaling to an entire state without letting a healthy average hide a struggling school, holding up under a genuine second-year validation check, and surviving contact with federal reporting requirements without losing its original purpose.
At the center of the model is the Support Coefficient — a mechanism that turns "we should help this group of students" into a specific, fundable, measurable target, making equity a quantifiable part of the math rather than an afterthought bolted on. A dedicated chapter makes the case for why this particular approach — plain logistic regression, not a fancier algorithm — is the right tool for a decision this consequential, and a full statistical formalization gives a data team everything it needs to verify the math for themselves.
The book doesn't stop at building the model. It covers what happens when a prediction misses, who's accountable when the model flags a real student, and what a model should never be allowed to decide alone.
Written by an author who has spent a career moving between particle physics research and statewide education policy, Policy by the Numbers is for superintendents, principals, curriculum directors, and state agency staff who want a tool that respects both the rigor of the math and the judgment of the educator making the final call. Diagnostic, not deterministic — this model finds where the system needs to show up. It never decides where a student ends up.
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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. Every district leader already knows which students are struggling. The problem isn't instinct - it's that instinct doesn't scale, and by the time report cards confirm it, the window to act has closed.Policy by the Numbers hands education leaders a real, working predictive model - built entirely from data districts already collect - that flags at-risk students while there's still time to help them. No data science team required, no black-box software, no jargon you can't repeat to a school board.The book follows Sagebrush Valley, a composite district, from a three-week data-cleanup sprint to a fully funded, board-approved intervention, then follows that same discipline outward: scaling to an entire state without letting a healthy average hide a struggling school, holding up under a genuine second-year validation check, and surviving contact with federal reporting requirements without losing its original purpose.At the center of the model is the Support Coefficient - a mechanism that turns "we should help this group of students" into a specific, fundable, measurable target, making equity a quantifiable part of the math rather than an afterthought bolted on. A dedicated chapter makes the case for why this particular approach - plain logistic regression, not a fancier algorithm - is the right tool for a decision this consequential, and a full statistical formalization gives a data team everything it needs to verify the math for themselves.The book doesn't stop at building the model. It covers what happens when a prediction misses, who's accountable when the model flags a real student, and what a model should never be allowed to decide alone.Written by an author who has spent a career moving between particle physics research and statewide education policy, Policy by the Numbers is for superintendents, principals, curriculum directors, and state agency staff who want a tool that respects both the rigor of the math and the judgment of the educator making the final call. Diagnostic, not deterministic - this model finds where the system needs to show up. It never decides where a student ends up. Transform intuition into action with a practical predictive framework that identifies vulnerable learners before they fall behind. This guide empowers administrators to turn raw data into meaningful, equitable interventions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798952051003
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Every district leader already knows which students are struggling. The problem isn't instinct - it's that instinct doesn't scale, and by the time report cards confirm it, the window to act has closed.Policy by the Numbers hands education leaders a real, working predictive model - built entirely from data districts already collect - that flags at-risk students while there's still time to help them. No data science team required, no black-box software, no jargon you can't repeat to a school board.The book follows Sagebrush Valley, a composite district, from a three-week data-cleanup sprint to a fully funded, board-approved intervention, then follows that same discipline outward: scaling to an entire state without letting a healthy average hide a struggling school, holding up under a genuine second-year validation check, and surviving contact with federal reporting requirements without losing its original purpose.At the center of the model is the Support Coefficient - a mechanism that turns 'we should help this group of students' into a specific, fundable, measurable target, making equity a quantifiable part of the math rather than an afterthought bolted on. A dedicated chapter makes the case for why this particular approach - plain logistic regression, not a fancier algorithm - is the right tool for a decision this consequential, and a full statistical formalization gives a data team everything it needs to verify the math for themselves.The book doesn't stop at building the model. It covers what happens when a prediction misses, who's accountable when the model flags a real student, and what a model should never be allowed to decide alone.Written by an author who has spent a career moving between particle physics research and statewide education policy, Policy by the Numbers is for superintendents, principals, curriculum directors, and state agency staff who want a tool that respects both the rigor of the math and the judgment of the educator making the final call. Diagnostic, not deterministic - this model finds where the system needs to show up. It never decides where a student ends up. Seller Inventory # 9798952051003
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Seller: AussieBookSeller, Truganina, VIC, Australia
Paperback. Condition: new. Paperback. Every district leader already knows which students are struggling. The problem isn't instinct - it's that instinct doesn't scale, and by the time report cards confirm it, the window to act has closed.Policy by the Numbers hands education leaders a real, working predictive model - built entirely from data districts already collect - that flags at-risk students while there's still time to help them. No data science team required, no black-box software, no jargon you can't repeat to a school board.The book follows Sagebrush Valley, a composite district, from a three-week data-cleanup sprint to a fully funded, board-approved intervention, then follows that same discipline outward: scaling to an entire state without letting a healthy average hide a struggling school, holding up under a genuine second-year validation check, and surviving contact with federal reporting requirements without losing its original purpose.At the center of the model is the Support Coefficient - a mechanism that turns "we should help this group of students" into a specific, fundable, measurable target, making equity a quantifiable part of the math rather than an afterthought bolted on. A dedicated chapter makes the case for why this particular approach - plain logistic regression, not a fancier algorithm - is the right tool for a decision this consequential, and a full statistical formalization gives a data team everything it needs to verify the math for themselves.The book doesn't stop at building the model. It covers what happens when a prediction misses, who's accountable when the model flags a real student, and what a model should never be allowed to decide alone.Written by an author who has spent a career moving between particle physics research and statewide education policy, Policy by the Numbers is for superintendents, principals, curriculum directors, and state agency staff who want a tool that respects both the rigor of the math and the judgment of the educator making the final call. Diagnostic, not deterministic - this model finds where the system needs to show up. It never decides where a student ends up. Transform intuition into action with a practical predictive framework that identifies vulnerable learners before they fall behind. This guide empowers administrators to turn raw data into meaningful, equitable interventions. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798952051003
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Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: new. Paperback. Every district leader already knows which students are struggling. The problem isn't instinct - it's that instinct doesn't scale, and by the time report cards confirm it, the window to act has closed.Policy by the Numbers hands education leaders a real, working predictive model - built entirely from data districts already collect - that flags at-risk students while there's still time to help them. No data science team required, no black-box software, no jargon you can't repeat to a school board.The book follows Sagebrush Valley, a composite district, from a three-week data-cleanup sprint to a fully funded, board-approved intervention, then follows that same discipline outward: scaling to an entire state without letting a healthy average hide a struggling school, holding up under a genuine second-year validation check, and surviving contact with federal reporting requirements without losing its original purpose.At the center of the model is the Support Coefficient - a mechanism that turns "we should help this group of students" into a specific, fundable, measurable target, making equity a quantifiable part of the math rather than an afterthought bolted on. A dedicated chapter makes the case for why this particular approach - plain logistic regression, not a fancier algorithm - is the right tool for a decision this consequential, and a full statistical formalization gives a data team everything it needs to verify the math for themselves.The book doesn't stop at building the model. It covers what happens when a prediction misses, who's accountable when the model flags a real student, and what a model should never be allowed to decide alone.Written by an author who has spent a career moving between particle physics research and statewide education policy, Policy by the Numbers is for superintendents, principals, curriculum directors, and state agency staff who want a tool that respects both the rigor of the math and the judgment of the educator making the final call. Diagnostic, not deterministic - this model finds where the system needs to show up. It never decides where a student ends up. Transform intuition into action with a practical predictive framework that identifies vulnerable learners before they fall behind. This guide empowers administrators to turn raw data into meaningful, equitable interventions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798952051003
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Seller: Rarewaves.com UK, London, United Kingdom
Paperback. Condition: New. Seller Inventory # LU-9798952051003
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