An Introduction to Mathematical Statistics and Its Applications, Volume 1For courses in Mathematical Statistics. Renowned for its high-quality, real-world case studies and examples, this highly structured text is designed to allow students with an established mathematics background to pursue a more rigorous, advanced treatment of probability and statistics. It shows HOW to use statistical methods, WHEN to use them, and reinforces the calculus that students have covered in previous courses. *Cover pages include a chart of densities, moments, and moment generating functions. *Additional simulations and Monte Carlo studies. *Minitab sections - At the end of chapters. *Delineates how one experimental design differs from another and the statistical consequences of those differences. *A complete Solutions Manual in response to user demand. *Uses case studies and practical worked-out examples to motivate statistical reasoning and demonstrate the application of statistical methods to a wide variety of real-world situations. |
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An Introduction to Mathematical Statistics and Its Applications Richard J. Larsen,Morris L. Marx No preview available - 2001 |
Common terms and phrases
approximate average B₁ binomial random variable calculated central limit theorem Chapter chi-square chi-square distribution chips confidence interval decision rule defined Definition degrees of freedom denote the number drawn equal Equation error event EXAMPLE expected value F distribution Figure Find formula fw(w fx(x fz(z given histogram hypothesis test independent joint pdf Let the random Let Y₁ level of significance likelihood method of moments MINITAB moment-generating function normal distribution normal pdf null hypothesis observations outcomes P-value parameter pdf fy(y pdf's Poisson distribution probability function Proof px(k Question random sample ratio recall reject S/Vn sample mean sample space shows standard deviation standard normal Student Study SUBC Suppose Table test statistic Theorem tossed treatment levels trials true two-sample uniform pdf variance versus H₁ W₁ W₂ X₁ Y₂ μ₁ σ²