Mathematical Statistics with ApplicationsThis is the most widely used mathematical statistics text at the top 200 universities in the United States. Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid undergraduate foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. 
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Review: Mathematical Statistics with Applications (Mathematical Statistics (W/ Applications))
User Review  Franklin Colorado  GoodreadsI haven't read several books on this subject, but this one was right for me. Most statistics books are aimed at high school or freshmen non engineers. This is a little harder, although not impossible to follow. Read full review
Review: Mathematical Statistics with Applications (Mathematical Statistics (W/ Applications))
User Review  Vanessa  GoodreadsUsed in a twosemester intro probability and statistics course. Great textbook. Clear examples, and lots of practice problems and solutions. I taught myself a lot straight from the book during my statistics classes. Read full review
Contents
Discrete Random Variables and Their Probability Distributions  83 
Continuous Random Variables and Their Probability  150 
6  175 
Copyright  
32 other sections not shown
Common terms and phrases
accompanying table approximately assigned associated Assume binomial distribution binomial probability binomial probability distribution calculate Chapter confidence interval contains continuous random variable DEFINITION degrees of freedom denote a random denote the number derived difference discrete random variable distribution function distribution with mean elsewhere equal error evidence to indicate Example expected value experiment favor Figure Find the probability frequency histogram hence histogram inference joint density linear matrix mean and variance measurements method momentgenerating function normally distributed null hypothesis number of sample obtained pvalue pair parameters Poisson distribution probability density function probability distribution probability function proportion randomized block design randomly selected rank Refer to Exercise rejection region relative frequency result sample mean sample points sample space Section Show simple events Solution standard deviation sufficient evidence sufficient statistic Suppose test statistic tosses total number treatment trial unbiased estimator variance a2