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Additivity property of x 2 If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables. Adjusted R 2 A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased. Bayes estimator An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution. Bias An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest. Center line A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart. Completely randomized design (or experiment) A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order. Consistent estimator An estimator that converges in probability to the true value of the estimated parameter as the sample size increases. Continuity correction. A correction factor used to improve the approximation to binomial probabilities from a normal distribution. Control chart A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes. Convolution A 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. Critical value(s) The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment. Discrete uniform random variable A discrete random variable with a inite range and constant probability mass function. Error mean square The error sum of squares divided by its number of degrees of freedom. Error variance The variance of an error term or component in a model. Experiment A series of tests in which changes are made to the system under study Extra sum of squares method A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model. Factorial experiment A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested. Fraction defective In statistical quality control, that portion of a number of units or the output of a process that is defective. Gamma random variable A random variable that generalizes an Erlang random variable to noninteger values of the parameter r Gaussian distribution Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications We believe everything in the internet must be free. So this tool was designed for free download documents from the internet. We are not associated with any website in anyway. We are not responsible for the content. You are self-responsible for your download. © , Amazon.com, Inc. or its affiliates Something went wrong. Wait a moment and try again. by Economic Journal Division HIMA ESP FEB UNPADclick here to download E-BookStatistical Techniques in Business & EconomicsFifteenth EditionDouglas A. Lind, William G. Marchal, Samuel A. WathenChapter 1 : What Is Statistics?Chapter 2 : Describing Data: Frequency Tables, Frequency Distributions, and GraphicPresentationChapter 3 : Describing Data: Numerical MeasuresChapter 4 : Describing Data: Displaying and Exploring DataChapter 5 : A Survey of Probability ConceptsChapter 6 : Discrete Probability DistributionsChapter 7 : Continuous Probability DistributionsChapter 8 : Sampling Methods and the Central Limit TheoremChapter 9 : Estimation and Confidence IntervalsChapter 10 : One-Sample Tests of HypothesisChapter 11 : Two-Sample Tests of HypothesisChapter 12 : Analysis of VarianceChapter 13 : Correlation and Linear RegressionChapter 14 : Multiple Regression AnalysisChapter 15 : Index NumbersChapter 16 : Time Series and ForecastingChapter 17 : Nonparametric Methods: Goodness-of-Fit TestsChapter 18 : Nonparametric Methods: Analysis of Ranked DataChapter 19 : Statistical Process Control and Quality ManagementChapter 20 : An Introduction to Decision Theory
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