This modern text presents the fundamental ideas of probability theory and statistics with an abundance of applications relating to topics such as reliability, queuing theory, and computer performance analysis. Along with thorough coverage of the traditional topics of a first course in statistics, this new text emphasizes modeling, displaying, interpreting, and collecting data for a variety of scientific and engineering applications.

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Early emphasis on data analysis (chapter 1) provides students with a visual representation of data and prepares them to make meaningful statistical inferences based on visual and computational results in later chapters.
Utilization of real data from a variety of sources, such as engineering and computer science, reinforces the relevance of statistics and probability to your students' particular area of academic interest.
Careful data analysis is stressed by the use of a smaller number of data sets. As practicing scientists do in the real world, students learn to apply a variety of statistical techniques to a single data set.
Equal treatment is given to the classical approach and the confidence interval approach to hypothesis testing.

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Introduction to Probability and Statistics for Scientists and Engineers

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