 5.1: In Exercises 1 and 2, use the normal curve to estimate the mean and...
 5.2: In Exercises 1 and 2, use the normal curve to estimate the mean and...
 5.3: In Exercises 3 and 4, use the normal curves shown at the left Which...
 5.4: In Exercises 3 and 4, use the normal curves shown at the left Which...
 5.5: In Exercises 5 and 6, find the area of the indicated region under t...
 5.6: In Exercises 5 and 6, find the area of the indicated region under t...
 5.7: In Exercises 718, find the indicated area under the standard normal...
 5.8: In Exercises 718, find the indicated area under the standard normal...
 5.9: In Exercises 718, find the indicated area under the standard normal...
 5.10: In Exercises 718, find the indicated area under the standard normal...
 5.11: In Exercises 718, find the indicated area under the standard normal...
 5.12: In Exercises 718, find the indicated area under the standard normal...
 5.13: In Exercises 718, find the indicated area under the standard normal...
 5.14: In Exercises 718, find the indicated area under the standard normal...
 5.15: In Exercises 718, find the indicated area under the standard normal...
 5.16: In Exercises 718, find the indicated area under the standard normal...
 5.17: In Exercises 718, find the indicated area under the standard normal...
 5.18: In Exercises 718, find the indicated area under the standard normal...
 5.19: In Exercises 19 and 20, use the following information. The scores f...
 5.20: In Exercises 19 and 20, use the following information. The scores f...
 5.21: In Exercises 2126, find the indicated probability using the standar...
 5.22: In Exercises 2126, find the indicated probability using the standar...
 5.23: In Exercises 2126, find the indicated probability using the standar...
 5.24: In Exercises 2126, find the indicated probability using the standar...
 5.25: In Exercises 2126, find the indicated probability using the standar...
 5.26: In Exercises 2126, find the indicated probability using the standar...
 5.27: In Exercises 2732, the random variable x is normally distributed wi...
 5.28: In Exercises 2732, the random variable x is normally distributed wi...
 5.29: In Exercises 2732, the random variable x is normally distributed wi...
 5.30: In Exercises 2732, the random variable x is normally distributed wi...
 5.31: In Exercises 2732, the random variable x is normally distributed wi...
 5.32: In Exercises 2732, the random variable x is normally distributed wi...
 5.33: In Exercises 33 and 34, find the indicated probabilities. If conven...
 5.34: In Exercises 33 and 34, find the indicated probabilities. If conven...
 5.35: Determine whether any of the events in Exercise 33 are unusual. Exp...
 5.36: Determine whether any of the events in Exercise 34 are unusual. Exp...
 5.37: In Exercises 37 42, use the Standard Normal Table to find the zsco...
 5.38: In Exercises 37 42, use the Standard Normal Table to find the zsco...
 5.39: In Exercises 37 42, use the Standard Normal Table to find the zsco...
 5.40: In Exercises 37 42, use the Standard Normal Table to find the zsco...
 5.41: In Exercises 37 42, use the Standard Normal Table to find the zsco...
 5.42: In Exercises 37 42, use the Standard Normal Table to find the zsco...
 5.43: Find the z@score that has 30.5% of the distributions area to its ri...
 5.44: Find the z@score for which 94% of the distributions area lies betwe...
 5.45: In Exercises 4550, use the following information. On a dry surface,...
 5.46: In Exercises 4550, use the following information. On a dry surface,...
 5.47: In Exercises 4550, use the following information. On a dry surface,...
 5.48: In Exercises 4550, use the following information. On a dry surface,...
 5.49: In Exercises 4550, use the following information. On a dry surface,...
 5.50: In Exercises 4550, use the following information. On a dry surface,...
 5.51: In Exercises 51 and 52, find the mean and standard deviation of the...
 5.52: In Exercises 51 and 52, find the mean and standard deviation of the...
 5.53: In Exercises 53 and 54, use the Central Limit Theorem to find the m...
 5.54: In Exercises 53 and 54, use the Central Limit Theorem to find the m...
 5.55: In Exercises 55 60, find the indicated probabilities and interpret ...
 5.56: In Exercises 55 60, find the indicated probabilities and interpret ...
 5.57: In Exercises 55 60, find the indicated probabilities and interpret ...
 5.58: In Exercises 55 60, find the indicated probabilities and interpret ...
 5.59: In Exercises 55 60, find the indicated probabilities and interpret ...
 5.60: In Exercises 55 60, find the indicated probabilities and interpret ...
 5.61: In Exercises 61 and 62, a binomial experiment is given. Determine w...
 5.62: In Exercises 61 and 62, a binomial experiment is given. Determine w...
 5.63: In Exercises 6368, write the binomial probability in words. Then, u...
 5.64: In Exercises 6368, write the binomial probability in words. Then, u...
 5.65: In Exercises 6368, write the binomial probability in words. Then, u...
 5.66: In Exercises 6368, write the binomial probability in words. Then, u...
 5.67: In Exercises 6368, write the binomial probability in words. Then, u...
 5.68: In Exercises 6368, write the binomial probability in words. Then, u...
 5.69: In Exercises 69 and 70, determine whether you can use a normal dist...
 5.70: In Exercises 69 and 70, determine whether you can use a normal dist...
Solutions for Chapter 5: NORMAL PROBABILITY DISTRIBUTIONS
Full solutions for Elementary Statistics: Picturing the World  6th Edition
ISBN: 9780321911216
Solutions for Chapter 5: NORMAL PROBABILITY DISTRIBUTIONS
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Since 70 problems in chapter 5: NORMAL PROBABILITY DISTRIBUTIONS have been answered, more than 117796 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World , edition: 6. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321911216. Chapter 5: NORMAL PROBABILITY DISTRIBUTIONS includes 70 full stepbystep solutions.

aerror (or arisk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II 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

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

Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability

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.

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.

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare 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

Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.

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.

Critical value(s)
The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

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

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

Estimator (or point estimator)
A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

Event
A subset of a sample space.

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

Fisher’s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Fraction defective
In statistical quality control, that portion of a number of units or the output of a process that is defective.

Gamma function
A function used in the probability density function of a gamma random variable that can be considered to extend factorials

Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.