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# Solutions for Chapter 2.4: Elementary Statistics: Picturing the World 5th Edition

## Full solutions for Elementary Statistics: Picturing the World | 5th Edition

ISBN: 9780321693624

Solutions for Chapter 2.4

Solutions for Chapter 2.4
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##### ISBN: 9780321693624

Since 33 problems in chapter 2.4 have been answered, more than 12236 students have viewed full step-by-step solutions from this chapter. Chapter 2.4 includes 33 full step-by-step solutions. This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World, edition: 5. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321693624. This expansive textbook survival guide covers the following chapters and their solutions.

Key Statistics Terms and definitions covered in this textbook
• `-error (or `-risk)

In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

• 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

A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

• Binomial random variable

A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

• 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.

• 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

• Conditional probability

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

• 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

• Contour plot

A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

• 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 .

• Cumulative normal distribution function

The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

• 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.

• Defects-per-unit control chart

See U chart

• Error of estimation

The difference between an estimated value and the true value.

• Error sum of squares

In analysis of variance, this is the portion of total variability that is due to the random component in the data. It is usually based on replication of observations at certain treatment combinations in the experiment. It is sometimes called the residual sum of squares, although this is really a better term to use only when the sum of squares is based on the remnants of a model-itting process and not on replication.

• Event

A subset of a sample space.

• 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

• Fractional factorial experiment

A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

• 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

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