 63.1: If samples of a specific size are selected from a population and th...
 63.2: Why do most of the sample means differ somewhat from the population...
 63.3: What is the mean of the sample means?
 63.4: What is the standard deviation of the sample means called? What is ...
 63.5: What does the central limit theorem say about the shape of the dist...
 63.6: What formula is used to gain information about an individual data v...
 63.7: What formula is used to gain information about a sample mean when t...
 63.8: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.9: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.10: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.11: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.12: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.13: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.14: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.15: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.16: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.17: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.18: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.19: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.20: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.21: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.22: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.23: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.24: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.25: For Exercises 8 through 25, assume that the sample is taken from a ...
 63.26: For Exercises 26 and 27, check to see whether the correction factor...
 63.27: For Exercises 26 and 27, check to see whether the correction factor...
 63.28: Breaking Strength of Steel Cable The average breaking strength of a...
 63.29: The standard deviation of a variable is 15. If a sample of 100 indi...
 63.30: In Exercise 29, what size sample is needed to cut the standard erro...
Solutions for Chapter 63: The Normal Distribution
Full solutions for Elementary Statistics: A Step by Step Approach  7th Edition
ISBN: 9780073534978
Solutions for Chapter 63: The Normal Distribution
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Elementary Statistics: A Step by Step Approach was written by Patricia and is associated to the ISBN: 9780073534978. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach, edition: 7. Chapter 63: The Normal Distribution includes 30 full stepbystep solutions. Since 30 problems in chapter 63: The Normal Distribution have been answered, more than 7662 students have viewed full stepbystep solutions from this chapter.

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

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

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.

Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.

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

Continuous distribution
A probability distribution for a continuous random variable.

Contour plot
A twodimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

Contrast
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol 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 incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

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

Dependent variable
The response variable in regression or a designed experiment.

Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.

Distribution function
Another name for a cumulative distribution function.

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.

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.

Experiment
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.

F distribution.
The distribution of the random variable deined as the ratio of two independent chisquare random variables, each divided by its number of degrees of freedom.
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