×
×

# Solutions for Chapter Chapter 8: Producing Data: Sampling

## Full solutions for The Basic Practice of Statistics | 4th Edition

ISBN: 9780716774785

Solutions for Chapter Chapter 8: Producing Data: Sampling

Solutions for Chapter Chapter 8
4 5 0 294 Reviews
31
4
##### ISBN: 9780716774785

The Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785. This expansive textbook survival guide covers the following chapters and their solutions. Since 50 problems in chapter Chapter 8: Producing Data: Sampling have been answered, more than 11090 students have viewed full step-by-step solutions from this chapter. This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4. Chapter Chapter 8: Producing Data: Sampling includes 50 full step-by-step solutions.

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

• Analysis of variance (ANOVA)

A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

• Average run length, or ARL

The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

• Central limit theorem

The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

• Chi-square (or chi-squared) random variable

A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random variable.

• Coeficient of determination

See R 2 .

• Completely randomized design (or experiment)

A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

• Conditional variance.

The variance of the conditional probability distribution of a random variable.

• Conidence level

Another term for the conidence coeficient.

• Contour plot

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

• Control limits

See Control chart.

• Convolution

A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

• 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.

• Design matrix

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

• 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.

• Experiment

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

• Exponential random variable

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

• F-test

Any test of signiicance involving the F distribution. The most common F-tests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.

• Harmonic mean

The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .

×