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Solutions for Chapter 10.5: Elementary Statistics 12th Edition

Full solutions for Elementary Statistics | 12th Edition

ISBN: 9780321836960

Solutions for Chapter 10.5

Solutions for Chapter 10.5
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ISBN: 9780321836960

Elementary Statistics was written by and is associated to the ISBN: 9780321836960. Chapter 10.5 includes 19 full step-by-step solutions. This textbook survival guide was created for the textbook: Elementary Statistics, edition: 12. This expansive textbook survival guide covers the following chapters and their solutions. Since 19 problems in chapter 10.5 have been answered, more than 202656 students have viewed full step-by-step solutions from this chapter.

Key Statistics Terms and definitions covered in this textbook
• 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.

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.

• Average

See Arithmetic mean.

• 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.

• Biased estimator

Unbiased estimator.

• Box plot (or box and whisker plot)

A 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).

• Central tendency

The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

• 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.

• Crossed factors

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

• 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

• Deming

W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

• Design matrix

A matrix that provides the tests that are to be conducted in an experiment.

• Empirical model

A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

• Exhaustive

A property of a collection of events that indicates that their union equals the sample space.

• Exponential random variable

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.

• False alarm

A signal from a control chart when no assignable causes are present

• Geometric random variable

A discrete random variable that is the number of Bernoulli trials until a success occurs.

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