Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three-part text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks.
Part I, Talking Probability explains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learning unknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions.
Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners, while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Mu Zhu is Professor in the Department of Statistics & Actuarial Science at the University of Waterloo, and Fellow of the American Statistical Association. He received his AB magna cum laude in applied mathematics from Harvard University, and his PhD in statistics from Stanford University. He is currently Director of the Graduate Data Science Program at Waterloo.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Hardcover. Etat : Brand New. 176 pages. 9.37x6.30x0.55 inches. In Stock. N° de réf. du vendeur __0192867733
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 45038419-n
Quantité disponible : Plus de 20 disponibles
Vendeur : INDOO, Avenel, NJ, Etats-Unis
Etat : New. N° de réf. du vendeur 9780192867735
Quantité disponible : 20 disponible(s)
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three-part text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks. Part I, Talking Probabilityexplains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learningunknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions. Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners,while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text. Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program in data science without knowing enough statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780192867735
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 45038419
Quantité disponible : Plus de 20 disponibles
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Hardcover. Etat : Brand New. 176 pages. 9.37x6.30x0.55 inches. In Stock. N° de réf. du vendeur x-0192867733
Quantité disponible : 2 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Über den AutorMu Zhu is Professor in the Department of Statistics & Actuarial Science at the University of Waterloo, and Fellow of the American Statistical Association. He received his AB magna cum laude in applied mathematics from . N° de réf. du vendeur 753992208
Quantité disponible : Plus de 20 disponibles
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Neuware - Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three-part text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks. Part I, Talking Probability explains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learning unknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions.Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners, while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text. N° de réf. du vendeur 9780192867735
Quantité disponible : 2 disponible(s)