 7.4.1: In a binomial experiment with n trials and probability of success p...
 7.4.2: When adding or subtracting 0.5 from x, we are making a correction f...
 7.4.3: Suppose X is a binomial random variable. To approximate P(X 6 5), c...
 7.4.4: Suppose X is a binomial random variable. To approximate P(3 X 10), ...
 7.4.5: In 514, a discrete random variable is given. Assume the probability...
 7.4.6: In 514, a discrete random variable is given. Assume the probability...
 7.4.7: In 514, a discrete random variable is given. Assume the probability...
 7.4.8: In 514, a discrete random variable is given. Assume the probability...
 7.4.9: In 514, a discrete random variable is given. Assume the probability...
 7.4.10: In 514, a discrete random variable is given. Assume the probability...
 7.4.11: In 514, a discrete random variable is given. Assume the probability...
 7.4.12: In 514, a discrete random variable is given. Assume the probability...
 7.4.13: In 514, a discrete random variable is given. Assume the probability...
 7.4.14: In 514, a discrete random variable is given. Assume the probability...
 7.4.15: In 1520, compute P(x) using the binomial probability formula. Then ...
 7.4.16: In 1520, compute P(x) using the binomial probability formula. Then ...
 7.4.17: In 1520, compute P(x) using the binomial probability formula. Then ...
 7.4.18: In 1520, compute P(x) using the binomial probability formula. Then ...
 7.4.19: In 1520, compute P(x) using the binomial probability formula. Then ...
 7.4.20: In 1520, compute P(x) using the binomial probability formula. Then ...
 7.4.21: OnTime Flights According to American Airlines, Flight 215 from Orl...
 7.4.22: Smokers According to Information Please Almanac, 80% of adult smoke...
 7.4.23: Morality In a recent poll, the Gallup Organization found that 45% o...
 7.4.24: Sneeze According to a study done by Nick Wilson of Otago University...
 7.4.25: Males Living at Home According to the Current Population Survey (In...
 7.4.26: Females Living at Home According to the Current Population Survey (...
 7.4.27: Boys Are Preferred In a Gallup poll, 37% of survey respondents said...
 7.4.28: Liars According to a USA Today Snapshot, 3% of Americans surveyed l...
Solutions for Chapter 7.4: THE NORMAL APPROXIMATION TO THE BINOMIAL PROBABILITY DISTRIBUTION
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 7.4: THE NORMAL APPROXIMATION TO THE BINOMIAL PROBABILITY DISTRIBUTION
Get Full SolutionsThis textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 7.4: THE NORMAL APPROXIMATION TO THE BINOMIAL PROBABILITY DISTRIBUTION includes 28 full stepbystep solutions. Since 28 problems in chapter 7.4: THE NORMAL APPROXIMATION TO THE BINOMIAL PROBABILITY DISTRIBUTION have been answered, more than 153700 students have viewed full stepbystep solutions from this chapter.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

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).

Analytic study
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

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.

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.

Causeandeffect diagram
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

Chance cause
The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

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

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.

Correlation coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

Defectsperunit control chart
See U chart

Eficiency
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

Empirical model
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

Error mean square
The error sum of squares divided by its number of degrees of freedom.

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 modelitting process and not on replication.

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

Forward selection
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

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