- Chapter Chapter 1: The Role of Statistics and the Data Analysis Process
- Chapter Chapter 10: Hypothesis Testing Using a Single Sample
- Chapter Chapter 11: Comparing Two Populations or Treatments
- Chapter Chapter 12: The Analysis of Categorical Data and Goodness-of-Fit Tests
- Chapter Chapter 13: Simple Linear Regression and Correlation: Inferential Methods
- Chapter Chapter 14: Multiple Regression Analysis
- Chapter Chapter 15: Analysis of Variance
- Chapter Chapter 2: Collecting Data Sensibly
- Chapter Chapter 3: Graphical Methods for Describing Data
- Chapter Chapter 4: Numerical Methods for Describing Data
- Chapter Chapter 5: Summarizing Bivariate Data
- Chapter Chapter 6: Probability
- Chapter Chapter 7: Random Variables and Probability Distributions
- Chapter Chapter 8: Sampling Variability and Sampling Distributions
- Chapter Chapter 9: Estimation Using a Single Sample
Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) 3rd Edition - Solutions by Chapter
Full solutions for Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition
Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition - Solutions by ChapterGet Full Solutions
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.
Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.
Central composite design (CCD)
A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.
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.
Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.
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.
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 .
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).
Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t
An expression sometimes used for nonlinear regression models or polynomial regression models.
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.
A probability distribution for a discrete random variable
Distribution free method(s)
Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).
The variance of an error term or component in a model.
Estimate (or point estimate)
The numerical value of a point estimator.
A series of tests in which changes are made to the system under study
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