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Fundamentals of Statistical Thinking: Tools and Applications

Fundamentals of Statistical Thinking: Tools and Applications - Yuly Koshevnik

Fundamentals of Statistical Thinking: Tools and Applications


Written for students with basic experience in college algebra and applied calculus, Fundamentals of Statistical Thinking: Tools and Applications familiarizes readers with fundamental concepts in statistical thinking in order to prepare them for specialized management courses such as econometrics and quantitative analysis.

The book is organized into four sections, each of which focuses on a common tool used in application. Chapters 1 through 4 discuss data analysis and summaries, with an emphasis on descriptive statistics and visualization. In Chapters 5 through 8 students learn about probability models and sampling distributions. Chapters 9 and 10 deal with statistical inferences, while Chapters 11 and 12 provide further applications for categorical data and simple linear regression models. Graphical illustrations support the written text and each chapter concludes with a visual summary.

Rooted in over ten years of classroom experience at both the undergraduate and graduate levels, Fundamentals of Statistical Thinking helps readers understand the importance of the main technical tools of statistical decision making, and explains when they can most appropriately be used for applied studies.

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953.74Lei

953.74Lei

1059.71 Lei

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Written for students with basic experience in college algebra and applied calculus, Fundamentals of Statistical Thinking: Tools and Applications familiarizes readers with fundamental concepts in statistical thinking in order to prepare them for specialized management courses such as econometrics and quantitative analysis.

The book is organized into four sections, each of which focuses on a common tool used in application. Chapters 1 through 4 discuss data analysis and summaries, with an emphasis on descriptive statistics and visualization. In Chapters 5 through 8 students learn about probability models and sampling distributions. Chapters 9 and 10 deal with statistical inferences, while Chapters 11 and 12 provide further applications for categorical data and simple linear regression models. Graphical illustrations support the written text and each chapter concludes with a visual summary.

Rooted in over ten years of classroom experience at both the undergraduate and graduate levels, Fundamentals of Statistical Thinking helps readers understand the importance of the main technical tools of statistical decision making, and explains when they can most appropriately be used for applied studies.

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