Introduction to the practice of statistics

書誌事項

Introduction to the practice of statistics

David S. Moore, George P. McCabe

W.H. Freeman, c1993

2nd ed.

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注記

Includes bibliographical references

内容説明・目次

内容説明

Presenting statistics from the point of view of working statisticians the book gives examples and exercises based on real data. This second edition has a refined and reorganized the text. The presentation of key concepts has been clarified and consolidated; notation has been simplified wherever possible; and many new data sets have been added. To offer students the opportunity to apply their knowledge in a realistic context, and in recognition of the utility of statistical software, computer exercises now conclude each chapter. In conjunction with this text there is - an instructor/solution manual (including data disks for the (IBM and MAC), a printed or computerized test bank, transparency masters, minitab manual and a student version of data desk with disk, MAC only.

目次

  • Introduction: what is statistics? Part 1 Looking at data - distributions: displaying distributions - measurement, variation, stemplots, histograms, looking at data, time plots
  • describing distributions - measuring centre, resistant measures of spread, the standard deviation, changing the unit of measurement
  • the normal distributions - density curves, normal distributions, normal distribution calculations, assessing normality. Part 2 Looking at data - relationships: scatterplots - interpreting scatterplots, smoothing scatterplots, categorical explanatory variables
  • least squares regression - fitting a line to data, least-squares regression, residuals, outliers and influential observations
  • an application - exponential growth - the nature of exponential growth, the logarithm transformation, residuals again
  • correlation - computing the correlation, correlation in the regression setting, interpreting correlation and regression
  • relations in categorical data - analyzing two-way tables, Simpson's paradox
  • the question of causation - smoking and lung cancer, establishing causation, Part 3 Producing data: first steps - the need for design, sampling, experiments - exercises
  • design of experiments - comparative experiments, randomization, how to randomize, cautions about experimentation, other experimental designs
  • sampling design - simple random samples, other sampling designs, cautions about sample surveys
  • toward statistical inference - sampling distributions, bias, variability, what about experiments?, conclusion. Part 4 Probability - the study of randomness: the idea of probability, the uses of probability
  • probability models - sample spaces, assigning probabilities, addition and multiplication rules
  • random variables - discrete random variables, continuous random variables
  • means and variances of random variables - the mean of a random variable, the law of large numbers, rules for means, the variance of a random variable, rules for variances
  • probability laws - general addition rules, conditional probabilities and general multiplication rules. Part 5 From probability to inference: counts and proportions - the binomial distributions, binomial probabilities, binomial mean and variance, sample proportions, normal approximations for proportions and counts
  • sample means - the distribution of a sample mean, the central limit theorem
  • control charts - control charts, out-of-control signals. (Part contents)

「Nielsen BookData」 より

詳細情報

  • NII書誌ID(NCID)
    BA20481710
  • ISBN
    • 071672250X
  • LCCN
    92022880
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    New York
  • ページ数/冊数
    xxiii, 854 p.
  • 大きさ
    25 cm
  • 分類
  • 件名
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