 Chapter 1: Introduction to Statistics
 Chapter 1.2: Statistical and Critical Thinking
 Chapter 1.3: Types of Data
 Chapter 1.4: Collecting Sample Data
 Chapter 10: Correlation and Regression
 Chapter 10.2: Correlation
 Chapter 10.3: Regression
 Chapter 10.4: Rank Correlation
 Chapter 11: ChiSquare and Analysis of Variance
 Chapter 11.2: GoodnessofFit
 Chapter 11.3: Contingency Tables
 Chapter 11.4: Analysis of Variance
 Chapter 2: Summarizing and Graphing Data
 Chapter 2.2: Frequency Distributions
 Chapter 2.3: Histograms
 Chapter 2.4: Graphs That Enlighten and Graphs That Deceive
 Chapter 3: Statistics for Describing, Exploring, and Comparing Data
 Chapter 3.2: Measures of Center
 Chapter 3.3: Measures of Variation
 Chapter 3.4: Measures of Relative Standing and Boxplots
 Chapter 4: Probability
 Chapter 4.2: Basic Concepts of Probability
 Chapter 4.3: Addition Rule
 Chapter 4.4: Multiplication Rule: Basics
 Chapter 4.5: Multiplication Rule: Complements and Conditional Probability
 Chapter 4.6: Counting
 Chapter 5: Discrete Probability Distributions
 Chapter 5.2: Probability Distributions
 Chapter 5.3: Binomial Probability Distributions
 Chapter 5.4: Parameters for Binomial Distributions
 Chapter 6: Normal Probability Distributions
 Chapter 6.2: The Standard Normal Distribution
 Chapter 6.3: Applications of Normal Distributions
 Chapter 6.4: Sampling Distributions and Estimators
 Chapter 6.5: The Central Limit Theorem
 Chapter 6.6: Assessing Normality
 Chapter 6.7: Normal as Approximation to Binomial
 Chapter 7: Estimates and Sample Sizes
 Chapter 7.2: Estimating a Population Proportion
 Chapter 7.3: Estimating a Population Mean
 Chapter 7.4: Estimating a Population Standard Deviation or Variance
 Chapter 8: Hypothesis Testing
 Chapter 8.2: Basics of Hypothesis Testing
 Chapter 8.3: Testing a Claim About a Proportion
 Chapter 8.4: Testing a Claim about a Mean
 Chapter 8.5: Testing a Claim About a Standard Deviation or Variance
 Chapter 9: Inferences from Two Samples
 Chapter 9.2: Two Proportions
 Chapter 9.3: Two Means: Independent Samples
 Chapter 9.4: Two Dependent Samples (Matched Pairs)
Essentials of Statistics 5th Edition  Solutions by Chapter
Full solutions for Essentials of Statistics  5th Edition
ISBN: 9780321924599
Essentials of Statistics  5th Edition  Solutions by Chapter
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2 k p  factorial experiment
A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

Arithmetic mean
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

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

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

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

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.

Control limits
See Control chart.

Cook’s distance
In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

Correction factor
A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

Deming’s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

Discrete random variable
A random variable with a inite (or countably ininite) range.

Error variance
The variance of an error term or component in a model.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

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 control chart
See P chart

Frequency distribution
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

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