- 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: Chi-Square and Analysis of Variance
- Chapter 11.2: Goodness-of-Fit
- 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
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
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
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.
Another term for the conidence coeficient.
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control 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 in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.
See Control chart.
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.
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.
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.
The variance of an error term or component in a model.
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 pair-wise hypothesis tests of treatment means in an experiment to determine which means differ.
Fraction defective control chart
See P chart
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on
A function used in the probability density function of a gamma random variable that can be considered to extend factorials