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# Solutions for Chapter 2.1: Elementary Statistics: A Step By Step Approach 9th Edition ## Full solutions for Elementary Statistics: A Step By Step Approach | 9th Edition

ISBN: 9780073534985 Solutions for Chapter 2.1

Solutions for Chapter 2.1
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##### ISBN: 9780073534985

Since 9 problems in chapter 2.1 have been answered, more than 169018 students have viewed full step-by-step solutions from this chapter. Chapter 2.1 includes 9 full step-by-step solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9. This expansive textbook survival guide covers the following chapters and their solutions. Elementary Statistics: A Step By Step Approach was written by and is associated to the ISBN: 9780073534985.

Key Statistics Terms and definitions covered in this textbook
• Acceptance region

In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

• 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.

• 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.

• Bayes’ theorem

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

• Bernoulli trials

Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

• Block

In experimental design, a group of experimental units or material that is relatively homogeneous. The purpose of dividing experimental units into blocks is to produce an experimental design wherein variability within blocks is smaller than variability between blocks. This allows the factors of interest to be compared in an environment that has less variability than in an unblocked experiment.

• 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.

• 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.

• Control limits

See Control chart.

• Correction factor

A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

• Counting techniques

Formulas used to determine the number of elements in sample spaces and events.

• Design matrix

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

• Distribution free method(s)

Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

• 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.

• Estimate (or point estimate)

The numerical value of a point estimator.

• Exhaustive

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

• 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

• Fraction defective control chart

See P chart

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