Jay Devore is Professor Emeritus of Statistics at California Polytechnic State University. He earned his undergraduate degree in Engineering Science from the University of California at Berkeley, spent a year at the University of Sheffield in England, and finished his Ph.D. in statistics at Stanford University. Jay previously taught at the University of Florida and at Oberlin College and has had visiting appointments at Stanford, Harvard, the University of Washington, New York University, and Columbia University. From 1998 to 2006, he served as Chair of the Cal Poly Statistics Department. In addition to this book, Jay has written several other widely used statistics texts for engineers and scientists and a book in applied mathematical statistics. He recently coauthored a text in probability and stochastic processes. He is the recipient of a distinguished teaching award from Cal Poly, is a Fellow of the American Statistical Association, and has served several terms as an Associate Editor of the “Journal of the American Statistical Association.” In his spare time, he enjoys reading, cooking and eating good food, tennis, and travel to faraway places. He is especially proud of his wife, Carol, a retired elementary school teacher, his daughter Allison, who has held several high-level positions in nonprofit organizations in Boston and New York City, and his daughter Teresa, a high school teacher in Brooklyn.

• 1. Panorama y estadística descriptiva. 2. Probabilidad. 3. Variables aleatorias discretas y probabilidad. 4. Variables aleatorias continuas y distribuciones de probabilidad. 5. Conjunto de distribuciones de probabilidad y muestras aleatorias. 6. Estimación puntual. 7. Intervalo estadístico basado en una muestra individual. 8. Pruebas de hipótesis basadas en una sola muestra. 9. Inferencias basadas en dos muestras. 10. Análisis de varianza. 11. Análisis de varianza multifactorial. 12. Regresión lineal simple y correlación. 13. No lineal y regresión múltiple. 14. Pruebas de bondad de ajuste y análisis de datos categóricos. 15. Procedimientos de libre distribución. 16. Métodos de control de calidad

Jay Devore is Professor Emeritus of Statistics at California Polytechnic State University. He earned his undergraduate degree in Engineering Science from the University of California at Berkeley, spent a year at the University of Sheffield in England, and finished his Ph.D. in statistics at Stanford University. Jay previously taught at the University of Florida and at Oberlin College and has had visiting appointments at Stanford, Harvard, the University of Washington, New York University, and Columbia University. From 1998 to 2006, he served as Chair of the Cal Poly Statistics Department. In addition to this book, Jay has written several other widely used statistics texts for engineers and scientists and a book in applied mathematical statistics. He recently coauthored a text in probability and stochastic processes. He is the recipient of a distinguished teaching award from Cal Poly, is a Fellow of the American Statistical Association, and has served several terms as an Associate Editor of the “Journal of the American Statistical Association.” In his spare time, he enjoys reading, cooking and eating good food, tennis, and travel to faraway places. He is especially proud of his wife, Carol, a retired elementary school teacher, his daughter Allison, who has held several high-level positions in nonprofit organizations in Boston and New York City, and his daughter Teresa, a high school teacher in Brooklyn.

• 1. Panorama y estadística descriptiva. 2. Probabilidad. 3. Variables aleatorias discretas y probabilidad. 4. Variables aleatorias continuas y distribuciones de probabilidad. 5. Conjunto de distribuciones de probabilidad y muestras aleatorias. 6. Estimación puntual. 7. Intervalo estadístico basado en una muestra individual. 8. Pruebas de hipótesis basadas en una sola muestra. 9. Inferencias basadas en dos muestras. 10. Análisis de varianza. 11. Análisis de varianza multifactorial. 12. Regresión lineal simple y correlación. 13. No lineal y regresión múltiple. 14. Pruebas de bondad de ajuste y análisis de datos categóricos. 15. Procedimientos de libre distribución. 16. Métodos de control de calidad

Jay Devore is Professor Emeritus of Statistics at California Polytechnic State University. He earned his undergraduate degree in Engineering Science from the University of California at Berkeley, spent a year at the University of Sheffield in England, and finished his Ph.D. in statistics at Stanford University. Jay previously taught at the University of Florida and at Oberlin College and has had visiting appointments at Stanford, Harvard, the University of Washington, New York University, and Columbia University. From 1998 to 2006, he served as Chair of the Cal Poly Statistics Department. In addition to this book, Jay has written several other widely used statistics texts for engineers and scientists and a book in applied mathematical statistics. He recently coauthored a text in probability and stochastic processes. He is the recipient of a distinguished teaching award from Cal Poly, is a Fellow of the American Statistical Association, and has served several terms as an Associate Editor of the “Journal of the American Statistical Association.” In his spare time, he enjoys reading, cooking and eating good food, tennis, and travel to faraway places. He is especially proud of his wife, Carol, a retired elementary school teacher, his daughter Allison, who has held several high-level positions in nonprofit organizations in Boston and New York City, and his daughter Teresa, a high school teacher in Brooklyn.

• 1. Panorama y estadística descriptiva. 2. Probabilidad. 3. Variables aleatorias discretas y probabilidad. 4. Variables aleatorias continuas y distribuciones de probabilidad. 5. Conjunto de distribuciones de probabilidad y muestras aleatorias. 6. Estimación puntual. 7. Intervalo estadístico basado en una muestra individual. 8. Pruebas de hipótesis basadas en una sola muestra. 9. Inferencias basadas en dos muestras. 10. Análisis de varianza. 11. Análisis de varianza multifactorial. 12. Regresión lineal simple y correlación. 13. No lineal y regresión múltiple. 14. Pruebas de bondad de ajuste y análisis de datos categóricos. 15. Procedimientos de libre distribución. 16. Métodos de control de calidad