 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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`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

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

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Biased estimator
Unbiased estimator.

Bivariate normal distribution
The joint distribution of two normal random variables

Categorical data
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

Central tendency
The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

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

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Contrast
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

Correlation matrix
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the offdiagonal elements rij are the correlations between Xi and Xj .

Deining relation
A subset of effects in a fractional factorial design that deine the aliases in the design.

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

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

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

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

Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

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

Generator
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.