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This introduction to the world of statistics draws examples from a broad range of applications, including business, government, medicine, social sciences, biology, and everyday life. The first four chapters present a brief course in exploratory data analysis. The authors place special emphasis on methods for collecting data and offer an elementary treatment of multiple regression. A concluding chapter on the design of comparative experiments links the basic ideas of design to previously discussed methods of analysis. Each chapter and section concludes with review problems. Suitable for undergraduate students, the text requires only one year of high school algebra.
This authoritative treatment was co-written by Frederick Mosteller, one of the twentieth century's preeminent statisticians and the founding chairman of Harvard's Department of Statistics, and Stephen Fienberg, a leader of statistics departments at the University of Minnesota and Carnegie Mellon University and who is internationally known for innovative statistical research and its application to social science and public policy.
This authoritative treatment was co-written by Frederick Mosteller, one of the twentieth century's preeminent statisticians and the founding chairman of Harvard's Department of Statistics, and Stephen Fienberg, a leader of statistics departments at the University of Minnesota and Carnegie Mellon University and who is internationally known for innovative statistical research and its application to social science and public policy.
Corrected reprint of the Addison-Wesley Publishing Company, Reading, Massachusetts, 1983 edition.
statistical research, probability theory, data analysis, introduction to statistics, statistics, math in business, math in government, math in medicine, math in the social sciences, math in biology, exploratory data analysis, methods for collecting data, multiple regression, comparative experiments, review problems, undergraduate math, probability and statistics;beginning statistics; applied statistics; statistical inference; data analysis; regressionDescription
This introduction to the world of statistics draws examples from a broad range of applications, including business, government, medicine, social sciences, biology, and everyday life. The first four chapters present a brief course in exploratory data analysis. The authors place special emphasis on methods for collecting data and offer an elementary treatment of multiple regression. A concluding chapter on the design of comparative experiments links the basic ideas of design to previously discussed methods of analysis. Each chapter and section concludes with review problems. Suitable for undergraduate students, the text requires only one year of high school algebra.
This authoritative treatment was co-written by Frederick Mosteller, one of the twentieth century's preeminent statisticians and the founding chairman of Harvard's Department of Statistics, and Stephen Fienberg, a leader of statistics departments at the University of Minnesota and Carnegie Mellon University and who is internationally known for innovative statistical research and its application to social science and public policy.
This authoritative treatment was co-written by Frederick Mosteller, one of the twentieth century's preeminent statisticians and the founding chairman of Harvard's Department of Statistics, and Stephen Fienberg, a leader of statistics departments at the University of Minnesota and Carnegie Mellon University and who is internationally known for innovative statistical research and its application to social science and public policy.
Corrected reprint of the Addison-Wesley Publishing Company, Reading, Massachusetts, 1983 edition.
statistical research, probability theory, data analysis, introduction to statistics, statistics, math in business, math in government, math in medicine, math in the social sciences, math in biology, exploratory data analysis, methods for collecting data, multiple regression, comparative experiments, review problems, undergraduate math, probability and statistics;beginning statistics; applied statistics; statistical inference; data analysis; regression
