See ExperimentĪ study in which a sample from a population is used to make inference to the population. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.Īn experiment in which the tests are planned in advance and the plans usually incorporate statistical models. Also called the variance-covariance matrix. The main diagonal elements of the matrix are the variances of the random variables and the off-diagonal elements are the covariances between Xi and Xj. Large values of Cook’s distance indicate that the observation is inluential.Ī square matrix that contains the variances and covariances among a set of random variables, say, X1, X X 2 k, , …. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. The variance of the conditional probability distribution of a random variable.Ī correction factor used to improve the approximation to binomial probabilities from a normal distribution.Ī random variable with an interval (either inite or ininite) of real numbers for its range.Ī method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions. The mean of the conditional probability distribution of a random variable. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.
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The individual components of the total variance that are attributable to speciic sources. The CCD is the most widely used design for itting a second-order model. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The joint distribution of two normal random variablesĪ graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).Ī second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. See ProbabilityĪn equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).Ī discrete random variable that equals the number of successes in a ixed number of Bernoulli trials. Key Statistics Terms and definitions covered in this textbookĪ set of rules that probabilities deined on a sample space must follow.
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Chapter 19: Testing Hypotheses About Proportions.Chapter 18: Confidence Intervals for Proportions.Chapter 17: Sampling Distribution Models.Chapter 13: From Randomness to Probability.Chapter 12: Experiments and Observational Studies.Chapter Part I: Exploring and Understanding Data.