Introduction to the practice of statistics
著者
書誌事項
Introduction to the practice of statistics
W.H. Freeman, c1993
2nd ed.
大学図書館所蔵 全15件
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)
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