Introductory StatisticsWeiss Introductory Statistics is intended for a one- or two-semester introductory statistics course. Students learn the core statistical concepts in an applied setting, and can access more advanced topics (multiple regression, ANOVA, and Experimental Design) through chapters available on the WeissStat CD. With advances in technology and new insights into the practice of teaching statistics, the sixth edition can now easily fit the organization and pace of various course syllabi and technologies in use. The book offers a flexible organization of content and has a more diversified emphasis on using technology such as Minitab, the TI-83 Plus graphing calculator, Excel, and the Internet to investigate statistical problems. *NEW All New Design. We have redesigned the text and now feature a four-color format for improved readability and understanding. *NEW What Does It Mean? This feature, which appears throughout the book, presents the meaning and significance of the statistical results in plain, everyday language and emphasizes the importance of interpretation. *NEW Technology Coverage. Students are introduced to technology at the section level with Minitab, Excel, and the TI-83 Plus |
Contents
Descriptive Statistics | 41 |
Descriptive Measures | 101 |
Probability Random Variables | 179 |
Copyright | |
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Common terms and phrases
alternative hypotheses apply approximately assumptions b₁ binomial boxplot column of Table Computer exercise confidence interval data provide sufficient data set data values denote difference displayed equal estimate event evidence to conclude Example graph histogram hypothesis test income independent samples Interpret your result Key Fact Kruskal-Wallis test left-tailed linear median Minitab Minitab output Nissan Zs normal curve normal probability plot normally distributed population null and alternative null hypothesis obtain one-way ANOVA outliers P-value percentage population mean population standard deviation prediction prediction interval Printout probability distribution procedure provide sufficient evidence random sample random variable randomly selected Refer to Exercise regression equation regression line relative-frequency right-tailed sample data sample mean sample standard deviation sampling distribution score significance level simple random sample specified standard normal curve statistical software stem-and-leaf diagram Step sum of squares Suppose t-test test statistic weight Wilcoxon signed-rank test z-score