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# Solutions for Chapter 2: Looking at DataRelationships

## Full solutions for Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card | 8th Edition

ISBN: 9781464158933

Solutions for Chapter 2: Looking at DataRelationships

Solutions for Chapter 2
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##### ISBN: 9781464158933

This expansive textbook survival guide covers the following chapters and their solutions. Since 178 problems in chapter 2: Looking at DataRelationships have been answered, more than 35913 students have viewed full step-by-step solutions from this chapter. Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card was written by and is associated to the ISBN: 9781464158933. This textbook survival guide was created for the textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card, edition: 8. Chapter 2: Looking at DataRelationships includes 178 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
• Assignable cause

The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

• Categorical data

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

• Chi-square test

Any test of signiicance based on the chi-square distribution. The most common chi-square tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

• Components of variance

The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

• Conditional probability

The probability of an event given that the random experiment produces an outcome in another event.

• Continuous distribution

A probability distribution for a continuous random variable.

• Continuous random variable.

A random variable with an interval (either inite or ininite) of real numbers for its range.

• 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.

• Correlation coeficient

A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

• Crossed factors

Another name for factors that are arranged in a factorial experiment.

• Decision interval

A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.

• Degrees of freedom.

The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

• Designed experiment

An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

• Error mean square

The error sum of squares divided by its number of degrees of freedom.

• Estimate (or point estimate)

The numerical value of a point estimator.

• Exponential random variable

A series of tests in which changes are made to the system under study

• Fixed factor (or fixed effect).

In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

• Fraction defective

In statistical quality control, that portion of a number of units or the output of a process that is defective.

• Fraction defective control chart

See P chart

• 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.

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