 Chapter Chapter 1: The Role of Statistics and the Data Analysis Process
 Chapter Chapter 10: Hypothesis Testing Using a Single Sample
 Chapter Chapter 11: Comparing Two Populations or Treatments
 Chapter Chapter 12: The Analysis of Categorical Data and GoodnessofFit Tests
 Chapter Chapter 13: Simple Linear Regression and Correlation: Inferential Methods
 Chapter Chapter 14: Multiple Regression Analysis
 Chapter Chapter 15: Analysis of Variance
 Chapter Chapter 2: Collecting Data Sensibly
 Chapter Chapter 3: Graphical Methods for Describing Data
 Chapter Chapter 4: Numerical Methods for Describing Data
 Chapter Chapter 5: Summarizing Bivariate Data
 Chapter Chapter 6: Probability
 Chapter Chapter 7: Random Variables and Probability Distributions
 Chapter Chapter 8: Sampling Variability and Sampling Distributions
 Chapter Chapter 9: Estimation Using a Single Sample
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Analytic study
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

Attribute
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

Bayesâ€™ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Biased estimator
Unbiased estimator.

Bivariate normal distribution
The joint distribution of two normal random variables

Categorical data
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

Conditional probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

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 limits
See Control chart.

Covariance
A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .

Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

Defect
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

Demingâ€™s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

Dependent variable
The response variable in regression or a designed experiment.

Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

Error propagation
An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

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.

Firstorder model
A model that contains only irstorder terms. For example, the irstorder response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irstorder model is also called a main effects model

Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.