 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? 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: Glass Garbage Generation Asurvey found that the American family gen...
 63.9: College Costs The mean undergraduate cost for tuition, fees, room, ...
 63.10: Teachers Salaries in Connecticut The average teachers salary in Con...
 63.11: Serum Cholesterol Levels The mean serum cholesterol level of a larg...
 63.12: Teachers Salaries in North Dakota The average teachers salary in No...
 63.13: Fuel Efficiency for U.S. Light Vehicles The average fuel efficiency...
 63.14: SAT Scores The national average SAT score (for Verbal and Math) is ...
 63.15: Sodium in Frozen Food The average number of milligrams (mg) of sodi...
 63.16: Cell Phone Lifetimes A recent study of the lifetimes of cell phones...
 63.17: Water Use The Old Farmers Almanac reports that the average person u...
 63.18: Medicare Hospital Insurance The average yearly Medicare Hospital In...
 63.19: Amount of Laundry Washed Each Year Procter & Gamble reported that a...
 63.20: Per Capita Income of Delaware Residents In a recent year, Delaware ...
 63.21: Annual Precipitation The average annual precipitation for a large M...
 63.22: Systolic Blood Pressure Assume that the mean systolic blood pressur...
 63.23: Cholesterol Content The average cholesterol content of a certain br...
 63.24: Ages of Proofreaders At a large publishing company, the mean age of...
 63.25: Weekly Income of Private Industry Information Workers The average w...
 63.26: Life Expectancies In a study of the life expectancy of 500 people i...
 63.27: Home Values Astudy of 800 homeowners in a certain area showed that ...
 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 Central Limit Theorem
Full solutions for Elementary Statistics: A Step by Step Approach 8th ed.  8th Edition
ISBN: 9780073386102
Solutions for Chapter 63: The Central Limit Theorem
Get Full SolutionsThis textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. This expansive textbook survival guide covers the following chapters and their solutions. Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102. Chapter 63: The Central Limit Theorem includes 30 full stepbystep solutions. Since 30 problems in chapter 63: The Central Limit Theorem have been answered, more than 27665 students have viewed full stepbystep solutions from this chapter.

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

Bimodal distribution.
A distribution with two modes

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.

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 (or chisquared) 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.

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

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

Comparative experiment
An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

Conidence level
Another term for the conidence coeficient.

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.

Defectsperunit control chart
See U chart

Density function
Another name for a probability density function

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.

Error of estimation
The difference between an estimated value and the true value.

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.

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

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

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

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