Probability and Statistical Inference This user-friendly introduction to the mathematics of probability and statistics (for readers with a background in calculus) uses numerous applications--drawn from biology, education, economics, engineering, environmental studies, exercise science, health science, manufacturing, opinion polls, psychology, sociology, and sports--to help explain and motivate the concepts. A review of selected mathematical techniques is included, and an accompanying CD-ROM contains many of the figures (many animated), and the data included in the examples and exercises (stored in both Minitab compatible format and ASCII). Empirical and Probability Distributions. Probability. Discrete Distributions. Continuous Distributions. Multivariable Distributions. Sampling Distribution Theory. Importance of Understanding Variability. Estimation. Tests of Statistical Hypotheses. Theory of Statistical Inference. Quality Improvement Through Statistical Methods. For anyone interested in the Mathematics of Probability and Statistics. |
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A₁ alternative hypothesis H₁ approximate Assume B₂ ball Bernoulli trials best-fitting line Central Limit Theorem Chebyshev's inequality chi-square chi-square distribution confidence interval continuous type critical region defined degrees of freedom distribution function distribution with mean distribution with p.d.f. equal the number equation Example Exercise Figure given graph H₁ Hence histogram illustration integers joint p.d.f. Let X equal Let X1 linear marginal p.d.f. maximum likelihood estimator moment-generating function mutually independent n₁ n₂ Note null hypothesis observed value order statistics outcomes p-value P₁ P₂ parameters percentiles plot Poisson distribution r₁ r₂ random sample random variable reject relative frequency respectively sample mean sample space Section selected at random SS(E SS(TO standard deviation Suppose Table test the hypothesis tion trials unbiased estimator unknown Var(X weight X₁ X₂ x�(n Y₁ Y₂ yielded zero Σ Σ σ� στ σχ