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. This usually refers to the individual variance components arising from a random or mixed model analysis of variance. The individual components of the total variance that are attributable to speciic sources. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Eficient computer algorithms have been developed for implementing all possible regressions Key Statistics Terms and definitions covered in this textbookĪ method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Chapter Part II: Exploring Relationships Between Variables.Chapter 9: Re-expressing Data: Get It Straight!.Chapter 6: Scatterplots, Association, and Correlation.Chapter 5: The Standard Deviation as a Ruler and the Normal Model.Chapter 4: Understanding and Comparing Distributions.Chapter 3: Displaying and Summarizing Quantitative Data.Chapter 20: More About Tests and Intervals.Chapter 2: Displaying and Describing Categorical Data.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.