 Chapter Part I: Exploring and Understanding Data
 Chapter 1: Stats Starts Here
 Chapter 10: Understanding Randomness
 Chapter 11: Sample Surveys
 Chapter 12: Experiments and Observational Studies
 Chapter 13: From Randomness to Probability
 Chapter 14: Probability Rules!
 Chapter 15: Random Variables
 Chapter 16: Probability Models
 Chapter 17: Sampling Distribution Models
 Chapter 18: Confidence Intervals for Proportions
 Chapter 19: Testing Hypotheses About Proportions
 Chapter 2: Displaying and Describing Categorical Data
 Chapter 20: More About Tests and Intervals
 Chapter 21: Comparing Two Proportions
 Chapter 22: Inferences About Means
 Chapter 23: Comparing Means
 Chapter 24: Paired Samples and Blocks
 Chapter 25: Comparing Counts
 Chapter 26: Inferences for Regression
 Chapter 27: Analysis of Variance
 Chapter 28: Multiple Regression
 Chapter 3: Displaying and Summarizing Quantitative Data
 Chapter 4: Understanding and Comparing Distributions
 Chapter 5: The Standard Deviation as a Ruler and the Normal Model
 Chapter 6: Scatterplots, Association, and Correlation
 Chapter 7: Linear Regression
 Chapter 8: Regression Wisdom
 Chapter 9: Reexpressing Data: Get It Straight!
 Chapter Part II: Exploring Relationships Between Variables
 Chapter Part III: Gathering Data
Stats Modeling the World 4th Edition  Solutions by Chapter
Full solutions for Stats Modeling the World  4th Edition
ISBN: 9780321854018
Stats Modeling the World  4th Edition  Solutions by Chapter
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Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

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

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

Bivariate distribution
The joint probability distribution of two random variables.

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

Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

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

Control limits
See Control chart.

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).

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

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 region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

Defect
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

Degrees of freedom.
The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

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

Distribution function
Another name for a cumulative distribution function.

Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

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

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.