- 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: Re-expressing 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
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.
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.
The joint probability distribution of two random variables.
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.
See Control chart.
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).
Formulas used to determine the number of elements in sample spaces and events.
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 off-diagonal elements are the covariances between Xi and Xj . Also called the variance-covariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.
A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.
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.
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.
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.