9780691258775 - Statistics by Simulation: A Synthetic Data Approach di Dormann, Carsten F.; Ellison, Aaron M. (29 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: New. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking. Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine. Includes R code for all examples, with data and code freely available online. Offers bullet-point outlines and summaries of each chapter. Minimizes the use of jargon and requires only basic statistical background and skills.

Paperback or Softback. Condizione: New. Statistics by Simulation: A Synthetic Data Approach. Book.

Condizione: new.

Condizione: New.

Condizione: NEW.

Condizione: New.

Paperback. Condizione: New. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking. Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine. Includes R code for all examples, with data and code freely available online. Offers bullet-point outlines and summaries of each chapter. Minimizes the use of jargon and requires only basic statistical background and skills.

Condizione: New.

Paperback. Condizione: new. Paperback. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine Includes R code for all examples, with data and code freely available online Offers bullet-point outlines and summaries of each chapter Minimizes the use of jargon and requires only basic statistical background and skills Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

paperback. Condizione: New.

Condizione: New.

Condizione: New. In.

Condizione: As New. Unread book in perfect condition.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New.

Condizione: NEW.

Paperback. Condizione: Brand New. 400 pages. 10.00x7.00x10.00 inches. In Stock.

Paperback. Condizione: new. Paperback. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplines.Real-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualisation. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods.Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checkingProvides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicineIncludes R code for all examples, with data and code freely available onlineOffers bullet-point outlines and summaries of each chapterMinimises the use of jargon and requires only basic statistical background and skills Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condizione: New.

Paperback. Condizione: New. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking. Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine. Includes R code for all examples, with data and code freely available online. Offers bullet-point outlines and summaries of each chapter. Minimizes the use of jargon and requires only basic statistical background and skills.

Taschenbuch. Condizione: Neu. Neuware - An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. ¿ Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking¿ Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine¿ Includes R code for all examples, with data and code freely available online¿ Offers bullet-point outlines and summaries of each chapter¿ Minimizes the use of jargon and requires only basic statistical background and skills.

Paperback. Condizione: new. Paperback. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplines.Real-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualisation. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods.Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checkingProvides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicineIncludes R code for all examples, with data and code freely available onlineOffers bullet-point outlines and summaries of each chapterMinimises the use of jargon and requires only basic statistical background and skills Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condizione: New. An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking. Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine. Includes R code for all examples, with data and code freely available online. Offers bullet-point outlines and summaries of each chapter. Minimizes the use of jargon and requires only basic statistical background and skills.

Taschenbuch. Condizione: Neu. Statistics by Simulation | A Synthetic Data Approach | Aaron M. Ellison (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Princeton University Press | EAN 9780691258775 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Paperback. Condizione: Brand New. 400 pages. 10.00x7.00x10.00 inches. In Stock. This item is printed on demand.